Ford: restore upstream control when the experimental toggle is off

Select the feedback controller on any Ford CAN FD vehicle when its Sunnylink toggle is enabled. Cover startup priority, toggle restarts, and downstream CAN publication across all six current CAN FD platforms; update the settings description and drive-test documentation.

Validation: 612 tests passed, 178 skipped, and 9146 subtests passed. Ruff and git diff checks passed. Offline validation only.

.gitattributes

@@ -9,6 +9,7 @@
 *.ttf filter=lfs diff=lfs merge=lfs -text
 *.otf filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
+openpilot/selfdrive/assets/sounds/milestone.wav -filter -diff -merge -text
 
 openpilot/selfdrive/car/tests/test_models_segs.txt filter=lfs diff=lfs merge=lfs -text
 openpilot/common/hardware/comma/updater filter=lfs diff=lfs merge=lfs -text

docs/ford_c1_carryover.md

@@ -0,0 +1,102 @@
+# Ford C1 correction carryover experiment
+
+The feedback controller at `5fbb583e5` can retain a correction from an earlier
+turn that outweighs the new base C1. The measured curvature can already be
+opposite the desired curvature, yet total C1 continues to request the old
+direction while the integral works back toward zero.
+
+This experiment keeps the existing 1:1 feedback strength and adds a conditional
+reset of that correction. It is a command-policy experiment, not a demonstrated
+improvement in physical steering response.
+
+## Release rule
+
+All of the following must be true on a valid, active cycle:
+
+- Feedback is enabled and a fresh steering publication advances measurement time.
+- Base C1 is nonzero by at least one DBC step (0.0005 rad).
+- Both target C0 and the slewed C0 request agree with base C1's direction,
+  by at least one DBC step (0.01 m).
+- Measured steering-derived curvature points opposite the desired curvature.
+- The accumulated correction prevents total C1 from requesting the base direction:
+  the sum of base C1 and correction is zero or opposite base C1.
+
+The stored correction is then set to zero before the usual feedback increment.
+The final C1 command still passes through its existing ±0.5 rad amplitude and
+0.5 rad/s slew limits. The reset cannot directly jump the transmitted command.
+The DBC steps reject requests smaller than one representable step; they are
+not new strength multipliers. This reset policy is itself an engineering choice.
+
+There is no reset simply because steering error crosses zero, or because C1
+and its correction have opposite signs. Matched curvature, neutral/conflicting
+C0, a correction that does not outweigh base C1, and repeated measurements all
+preserve normal integration. The condition can apply to small steering
+corrections as well as large turns; it has no turn-size or speed threshold.
+
+No previous-turn direction or timer is stored. Agreement between current path
+requests and disagreement with measured curvature are the confirmation. This
+does not establish which part of the combined C0/C1 request a PSCM physically
+needs. In particular, when C0 still points into the previous turn, this rule
+deliberately leaves the integral alone.
+
+## Preserved behavior and diagnostics
+
+C0's 7 m mapping, its limits, the base C1 mapping, upstream curvature limiting,
+the original integral strength, driver/PSCM arbitration, C2=C3=0 and the 100 Hz
+sender are unchanged. No fitted PSCM model, proportional term or gain schedule
+is added. There are still three values used by the command law: C0, C1 and
+the correction. A diagnostic-only `carryover_release_count` is added and resets
+with the controller. It is included in the existing periodic diagnostic event.
+
+The same default-off Sunnylink toggle selects this version. Its diagnostic
+identity is `model-action-c1-feedback-v2`. See the [drive-test instructions](ford_model_action_drive_test.md).
+
+## Offline evidence
+
+The two mirrored command-regression tests failed before the change. After
+building correction through actual feedback, the old controller still requested
+the old C1 direction 0.4 s into a reversal. Both tests now pass with the original
+output slew. Additional tests cover holding a steady curve, small error
+crossings, neutral and conflicting C0, representable command boundaries,
+freshness, driver override and PSCM limits. Integration tests execute the actual
+controlsd selection and upstream limiter, Float32 publication and Ford CAN
+builder, using both model and maneuver-plan requests and both turn directions.
+
+The combined suite passes **567 tests and 9,146 subtests**, with the same 178
+inherited/unsupported safety-test skips as the original feedback validation.
+The randomized checks include mirrored inputs, zero-error compatibility, and
+comparison against the exact previous controller from cloned pre-update states.
+
+Frozen b8 replay triggers 11 releases; b9 triggers 14. Activation and C0 match
+the previous controller exactly on every reconstructed cycle. In b9, most
+releases concern small corrections; one follows the large turn around 13:28.
+The C0/C1 disagreement at 14:36 is preserved. Numerical details and source
+hashes are in `ford_c1_carryover_validation.json`.
+
+At the release around 13:28, the candidate C1 crosses into the requested
+direction 0.255 s earlier than the previous controller on identical frozen
+inputs. This is a command zero-crossing comparison, not a measured improvement
+in the truck's steering response. The lab checks total 669,343 Float32/CAN
+round trips, in addition to the integration tests.
+
+Replay preserves recorded model requests and measured motion. A difference
+between candidate and baseline commands can persist because the recorded
+steering does not respond to the changed command. Replay cannot predict wheel
+angles, centering, oscillation, or how much earlier the vehicle would unwind.
+No device build, boot, installation or physical validation was performed.
+
+## Reproduction
+
+Use the branch's native dependencies and pinned opendbc revision
+`c21a9013700734dd20b09e05aa68329ad8cc20f9`. The route commands require the existing
+full-rlog b8/b9 extracts and the baseline Git revision. Run:
+
+```sh
+export PYTHONDONTWRITEBYTECODE=1
+export PYTHONPATH=.:opendbc_repo
+python -m pytest -q -p no:cacheprovider openpilot/selfdrive/controls/tests/test_ford_*.py tools/ford_pscm_lab openpilot/selfdrive/car/tests/test_ford_pscm_status.py openpilot/sunnypilot/sunnylink/tests openpilot/common/tests/test_params.py opendbc_repo/opendbc/car/ford/tests/test_ford.py opendbc_repo/opendbc/safety/tests/test_ford.py
+python -m tools.ford_pscm_lab.feedback_replay stress --cycles 200000 --output .cache/ford_c1_carryover/stress.json
+python -m tools.ford_pscm_lab.stress_model_action --cycles 200000 --seed 20260907 --opendbc-revision c21a9013700734dd20b09e05aa68329ad8cc20f9 --output .cache/ford_c1_carryover/zero_error_stress.json
+python -m tools.ford_pscm_lab.feedback_replay route .cache/ford_routeb8 --baseline 5fbb583e592d30de266f8160a5d6b9c620c97f56 --output .cache/ford_c1_carryover/routeb8
+python -m tools.ford_pscm_lab.feedback_replay route .cache/ford_routeb9 --baseline 5fbb583e592d30de266f8160a5d6b9c620c97f56 --output .cache/ford_c1_carryover/routeb9
+```

docs/ford_c1_carryover_validation.json

@@ -0,0 +1,177 @@
+{
+  "created_at_utc": "2026-09-10T14:00:37.853762+00:00",
+  "scope": "Conditional release of accumulated C1 correction; offline command behavior only, no predicted vehicle response.",
+  "baseline_commit": "5fbb583e592d30de266f8160a5d6b9c620c97f56",
+  "baseline_source_sha256": "4499defbb7fc5ddf5029ca42c549f0935b0758b08818c5bf0490fb52221f9a34",
+  "deployment_target": {
+    "repository": "sunnypilot/sunnypilot",
+    "branch": "hiimisaac-dev"
+  },
+  "hypothesis": "model-action-c1-feedback-v2",
+  "calibration_approved": false,
+  "toggle": {
+    "key": "FordModelActionController",
+    "default_enabled": false,
+    "activation": "Existing controlsd startup selection"
+  },
+  "release_rule": "Fresh enabled feedback; target and slewed C0 agree with base C1 by >= one DBC step; measured curvature is opposite; stored correction makes total C1 zero or opposite base. Clear correction, then apply original integration and output slew.",
+  "engineering_choices": "Conditional reset policy, using existing DBC steps (0.01 m, 0.0005 rad) to confirm nonzero commands. Original 1:1 integral strength is unchanged.",
+  "preserved": [
+    "C0 mapping and limits",
+    "Base C1 mapping",
+    "Original integral strength",
+    "Final C1 amplitude and slew limits",
+    "Driver and PSCM arbitration",
+    "Upstream selection and limiting",
+    "100 Hz sender",
+    "C2=C3=0"
+  ],
+  "panda_safety_changed": false,
+  "opendbc_submodule_changed": false,
+  "opendbc_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9",
+  "controller_size": {
+    "total_lines": 194,
+    "code_lines_excluding_blanks_comments_docstrings": 131,
+    "core_command_state_values": 3,
+    "core_diagnostic_counters": 1
+  },
+  "tests": {
+    "combined_suite": "567 passed, 178 skipped, 9146 subtests passed in 6.45s",
+    "safety_skips": "Same 178 inherited or unsupported variants recorded in ford_c1_feedback_validation.json.",
+    "regression": "Two mirrored carryover command tests fail on the exact baseline class and pass in the candidate suite.",
+    "ruff_changed_python": "pass",
+    "ty_controller": "pass",
+    "settings_compiler_check": "pass",
+    "carryover_controlsd_to_can_frames": 1120,
+    "existing_feedback_controlsd_to_can_frames": 1010,
+    "integration_scope": "Actual source selection, upstream limiting, controller, Float32 publication, Ford sender, both plan sources and signs, all counters and checksums."
+  },
+  "routes": {
+    "b8": {
+      "cycles": 160431,
+      "active_cycles": 68217,
+      "validity_and_c0_match_baseline_exactly": true,
+      "c1_changed_cycles": 6065,
+      "max_abs_c1_change_rad": 0.09250000000000003,
+      "can_round_trips": 160431,
+      "timing_limit": "Controls publication time proxies the computation clock; full SubMaster checks are unavailable.",
+      "reference_limit": "Uses exact consumed model publication as reference; b8 and b9 have no maneuver-plan messages.",
+      "carryover_release_count": 11,
+      "input_sha256": {
+        "route.npz": "6f5dd369b70eaed4b95b28c8b25c9f2e9b830fa07a334881a185505481667c8b",
+        "model_paths.npz": "939af6cf7e74251d8842581cc078d26d9fbfd22a0d7817cb0e368697d419b615",
+        "metadata.json": "73b439132d1de37ec187b544c04d2b05c80965065515a4b7dec29ba57ae37e7c"
+      }
+    },
+    "b9": {
+      "cycles": 90774,
+      "active_cycles": 86474,
+      "validity_and_c0_match_baseline_exactly": true,
+      "c1_changed_cycles": 15208,
+      "max_abs_c1_change_rad": 0.10400000000000004,
+      "can_round_trips": 90774,
+      "timing_limit": "Controls publication time proxies the computation clock; full SubMaster checks are unavailable.",
+      "reference_limit": "Uses exact consumed model publication as reference; b8 and b9 have no maneuver-plan messages.",
+      "carryover_release_count": 14,
+      "input_sha256": {
+        "route.npz": "b07c789d8155335f5d120d0262fced6e4d5803fe767b0ff49b6413dce4140b5c",
+        "model_paths.npz": "6b1f87897c050273fdc05af051307a049b6fc3a93072e7cda1721195ce7c3861",
+        "metadata.json": "9ce452220cab61b81883f32fc2fcaf5db6c78a674cb255a49cc77d5029580fee"
+      }
+    }
+  },
+  "command_timing_example": {
+    "event": {
+      "time_s": 808.286646083,
+      "correction_before_rad": -0.13089810321135922,
+      "correction_after_rad": 0.0,
+      "base_c1_rad": 0.06412824021622576,
+      "desired_angle_deg": -24.17155647277832,
+      "actual_angle_deg": -0.30000001192092896,
+      "speed_m_s": 11.804088592529297,
+      "baseline_c0_c1": [
+        0.15000000000000036,
+        -0.06600000000000006
+      ],
+      "candidate_c0_c1": [
+        0.15000000000000036,
+        -0.062000000000000055
+      ]
+    },
+    "scope": "Command zero crossing on identical frozen recorded inputs; not wheel response.",
+    "baseline_c1_rightward_at_s": 808.67241324,
+    "candidate_c1_rightward_at_s": 808.4169884780001,
+    "command_crossing_advance_s": 0.25542476199984776
+  },
+  "feedback_stress": {
+    "cycles": 200000,
+    "mirrored_updates": 200000,
+    "can_round_trips": 200000,
+    "carryover_release_count": 946,
+    "baseline_revision": "5fbb583e592d30de266f8160a5d6b9c620c97f56",
+    "baseline_source_sha256": "4499defbb7fc5ddf5029ca42c549f0935b0758b08818c5bf0490fb52221f9a34",
+    "exact_unchanged_state_and_commands_without_release": 199054,
+    "checks": "Mirror symmetry, reset/override, amplitude, slew, correction bounds, carryover direction/confirmation, integration, PSCM limits, CAN.",
+    "scope": "Numerical software invariants only; no model of vehicle motion.",
+    "calibration_approved": false,
+    "controller_sha256": "6f40a05977253987a2c96e74c8c18d912367ed1e55630558ed7b28d52576e552"
+  },
+  "zero_error_stress": {
+    "seed": 20260907,
+    "random_cycles": 200000,
+    "mirrored_core_updates": 200000,
+    "invalid_or_inactive_resets": 3537,
+    "field_boundary_cases": 18138,
+    "float32_can_round_trips": 218138,
+    "analytic_targets_scalar_slew_and_mirror_checks_pass": true,
+    "direct_raw_float32_packing_matches_host_output": true,
+    "max_continuous_step_c0_c1": [
+      0.40000000000000147,
+      0.05000000000000002
+    ],
+    "calibration_approved": false,
+    "scope": "Zero-error numerical construction: measured equals requested curvature. No PSCM response claims.",
+    "opendbc_import_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9"
+  },
+  "total_lab_float32_can_round_trips": 669343,
+  "source_sha256": {
+    "openpilot/selfdrive/controls/lib/ford_model_action.py": "6f40a05977253987a2c96e74c8c18d912367ed1e55630558ed7b28d52576e552",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_feedback.py": "04935fb941a795cb243870a4c03f7073c68147b01da3cedf2872476aa5fb798e",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_adapter.py": "e2e98d3a0a531235abd032fc4d3564796613ad51ff6ba22a230c48e36f6f6848",
+    "openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py": "90fb42ce580f0085e349467086a2eef28c2512c671755d0771f6331d30b19035",
+    "tools/ford_pscm_lab/feedback_replay.py": "9bf145fbff6ed685aec2c0e5d0584e2dc7ff831021f15110f939e8a94c93280b",
+    "tools/ford_pscm_lab/stress_model_action.py": "0b25188edf2b248ebe741173ce02ce75bd59f1f39fd5bd909d41a3dca2294aa8",
+    "tools/ford_pscm_lab/model_action_replay.py": "af97c665f342c66b1be2502e188c63e6f3ee106d0a0d5e80997bc3040373ff9f",
+    "docs/ford_c1_carryover.md": "e8d08375963efc6d1ae6ce503bb580ba00cfa90adb71c941d56fe6e3701d5cbb",
+    "docs/ford_c1_feedback.md": "1b440a03082e5cec264a1d6693833ed0a7e07b6c6e2122f8e4455c5971121b57",
+    "docs/ford_model_action_drive_test.md": "7ac5ca0faf9690a23e7058d09b55f23e21e2ba74666001cacb56b67e8d8b4376",
+    "openpilot/selfdrive/controls/controlsd.py": "2b7e246f00bccce3a2bb9f6f44009ca77690cadb8527cd2bdfe855e9ad72ad1e",
+    "opendbc_repo/opendbc/car/ford/carcontroller.py": "b2d327a1833fb1f0d09ee17f54c9c8d45517fa29beb04a4543cfbf1b43f1a65e",
+    "opendbc_repo/opendbc/safety/modes/ford.h": "1d9d996292d6697ab4f02d55fae348d6aca1df94a07f7bdae48b68971b91afe7",
+    "openpilot/sunnypilot/sunnylink/settings_ui.json": "7d38f315a7c5ce6d46d01a06f7eaddd4933f85639e5325ff71fdce22866ef401"
+  },
+  "artifact_sha256": {
+    ".cache/ford_c1_carryover/tests.txt": "cd65146df93632e4a2c1e086781e1da4673db7d038c7e673124f227efefbb567",
+    ".cache/ford_c1_carryover/baseline_regression.txt": "4469873f95ccf45a376a27fed05be3bdad5f808af7ceca472c6e2cb9d973eb7f",
+    ".cache/ford_c1_carryover/stress.json": "7a8d20d7abd7cf444f55b7316e8bedbed0fbe8e9587e09f90d5b1946c3c2e98c",
+    ".cache/ford_c1_carryover/zero_error_stress.json": "09e64eaac35df4ec324b41fabdc8baf91931106ac98b89c1ca71f4c8bf8796a4",
+    ".cache/ford_c1_carryover/timing.json": "0d18ed4164803adedbbd660fe024f4c28de8eb7921caa60659346ff386d3847f",
+    ".cache/ford_c1_carryover/routeb8/report.json": "d2c6f767cef29a74e292b6a16263d2da13b8c302e4653e419b0e232e1aaf762e",
+    ".cache/ford_c1_carryover/routeb8/commands.npz": "89b5c3474940b61afce060111c27fd9bad9e24d703c59fca61adf4ce10473df3",
+    ".cache/ford_c1_carryover/routeb9/report.json": "e3ff7bfa70e770eca763b125c283fd8a1d509ef1b6e7f26a81c398aca89a87da",
+    ".cache/ford_c1_carryover/routeb9/commands.npz": "e4f5f341146e2897a479baf222d678fd16352c8da931876a2471c3719faf9edf"
+  },
+  "test_environment": {
+    "python": "/Users/ibpersonal/dev/sunnypilot/.venv/bin/python",
+    "PYTHONPATH": ".:opendbc_repo:.cache/ford_v6/test_deps",
+    "PYTHONDONTWRITEBYTECODE": "1",
+    "LOG_ROOT": "/private/tmp/ford-carryover-logs",
+    "PARAMS_ROOT": "/private/tmp/ford-carryover-params"
+  },
+  "limitations": [
+    "Frozen replay preserves recorded requests and measured motion; changed commands do not establish changed wheel angles, centering or stability.",
+    "C0/C1 agreement is a reset-policy choice, not an identified relationship between PSCM input and wheel angle.",
+    "The rule can release small corrections and does not promise unchanged centering during transients.",
+    "No device build, boot, installation or physical validation was performed."
+  ]
+}

docs/ford_c1_feedback.md

@@ -0,0 +1,129 @@
+# Ford C1 feedback experiment
+
+This document records the original feedback change at `5fbb583e5`. The current
+version retains its feedback law and adds [conditional carryover release](ford_c1_carryover.md).
+The validation counts below describe the original change; current results are
+recorded in `ford_c1_carryover_validation.json`.
+
+The restored original v1 can leave a steering error while C0 and C1 still have
+room. Its command law does not directly correct measured steering error. This
+experiment keeps that mapping and adds one accumulated C1 correction:
+
+```text
+error = selected_limited_desired_curvature - measured_curvature
+correction += error * speed * elapsed_measurement_time
+C1_target = original_model_C1 + correction
+```
+
+Curvature (1/m) multiplied by traveled distance (m) gives heading mismatch in
+radians. Applying that mismatch to C1 at **1:1 is an explicit feedback-strength
+choice**. Dimensional consistency does not prove that every PSCM responds
+correctly to that strength. There is no fitted PSCM response model or new
+tunable multiplier.
+
+For example, at 20 m/s, a constant curvature shortfall of 0.001/m adds 0.02 rad
+to C1 over one second when the output can accept it. When measured curvature
+matches the request, the correction holds. If the vehicle turns more than
+requested, the correction moves in the unwind direction. Changing the model
+request still changes the base immediately, subject to the existing slew.
+
+## Preserved mapping and limits
+
+- C0 is the current model path's lateral offset at 7 m of arc distance, holding
+  the available endpoint for shorter paths; its limits remain ±5.11 m and 4 m/s.
+- Base C1 is `max(7 m, speed × 1 s) × selected_limited_desired_curvature`, clipped
+  to ±0.5 rad. Final C1 uses the same ±0.5 rad and 0.5 rad/s limits as v1.
+- C2 and C3 are zero. Sign conversion, Float32/CAN rounding, upstream curvature
+  limiting and the 100 Hz sender retain their existing behavior.
+
+The core holds three values: unquantized C0, unquantized C1 and the correction.
+Zero error from a reset leaves the correction at zero and preserves the old
+command arithmetic exactly. There is no separate percentage or distance cap
+on the correction.
+
+## Feedback measurement, timing and limits
+
+The measurement is `controlsd.curvature`, computed from measured steering
+angle with the existing live vehicle parameters. It matches the curvature
+used for the desired-versus-actual steering comparison. It is not an independent
+measurement of tire slip or the vehicle's actual ground path. CAN yaw remains
+an input-health gate and does not drive this feedback.
+
+The adapter integrates only elapsed time between fresh `carState` publications.
+The first publication after reset integrates zero time. Duplicate timestamps
+integrate zero; a fresh timestamp accounts for the elapsed measurement interval.
+Output slew continues on valid control cycles. Existing service-age, speed,
+model-geometry and clock-order gates remain, with the same finite/range check
+also applied to measured curvature. Disengagement or invalid input clears all
+three core states.
+
+The correction cannot accumulate farther into an unavailable C1 amplitude or
+slew request. Increments that move back toward the available output remain
+allowed. Moving the base request does not itself rewrite the correction.
+
+Fresh PSCM status means a valid message whose original CAN receipt timestamp
+is within the existing −5 to +150 ms age allowance. Reached-limit status (2)
+prevents extra accumulation in the measured turn direction. An old correction
+opposing that direction can return to zero; it cannot be trapped below the
+base request by the limit flag. Unwind and base model changes remain available.
+Close-to-limit status (1) does not block feedback. Missing or stale status
+does not gate it; local amplitude and slew anti-windup still apply.
+
+Driver steering-pressed, torque above the existing 1 Nm allowance, nonfinite
+torque, or fresh driver-limit status (3) clears the correction. Fresh denied
+or inactive PSCM status also clears it. The base model request continues
+through existing engagement and driver arbitration; clearing the correction
+does not bypass the final output slew.
+
+## Offline evidence and reproduction
+
+`ford_c1_feedback_validation.json` records the source hashes and completed
+checks. Tests exercise build, hold, unwind, saturation, limit flags, immediate
+driver input, stale and repeated measurements, invalid inputs and both signs.
+Integration tests execute actual controlsd selection and limiting, Float32
+publication, CarControlSP conversion and the Ford CarController CAN builder.
+Randomized runs check feedback invariants separately from zero-error
+compatibility with the original independent scalar oracle.
+
+The combined suite passes **511 tests and 9,146 subtests**. Its 178 skips are
+in inherited safety base classes or unsupported safety-test variants. Ruff,
+the controller's Ty check and settings compilation pass. Feedback stress,
+zero-error stress and the b8 replay total **578,569 Float32/CAN round trips**;
+the integration test separately verifies 1,010 transmitted packet constructions,
+including every counter and checksum. No packets are sent to hardware.
+
+The b8 replay retains recorded desired/measured curvature, model publications,
+driver input and PSCM flags. It compares candidate commands with the restored
+v1 at `a7d70e2b0890184636827351e4789d866f2a7c97`. All 160,431 reconstructed
+activation decisions and C0 commands match. C1 changes on 58,106 cycles.
+At 4:12.493, for example, reconstructed host C1 changes from −0.1625 to
+−0.2035 rad; at 3:56.250 it changes from −0.1280 to −0.1080 rad. These are
+changes to commands on frozen measurements, not predicted wheel angles.
+
+Controls publication time proxies the unlogged computation clock, and the
+full SubMaster health state cannot be reconstructed. This route uses the
+consumed model publication as its reference and has no maneuver-plan messages.
+Replay cannot show whether this feedback fixes weak turns, hanging turns or
+oscillation. A new drive is needed to measure those outcomes.
+
+Use the branch's native dependencies and pinned opendbc revision
+`c21a9013700734dd20b09e05aa68329ad8cc20f9`:
+
+```sh
+export PYTHONDONTWRITEBYTECODE=1
+export PYTHONPATH=.:opendbc_repo
+python -m pytest -q -p no:cacheprovider openpilot/selfdrive/controls/tests/test_ford_*.py tools/ford_pscm_lab openpilot/selfdrive/car/tests/test_ford_pscm_status.py openpilot/sunnypilot/sunnylink/tests openpilot/common/tests/test_params.py opendbc_repo/opendbc/car/ford/tests/test_ford.py opendbc_repo/opendbc/safety/tests/test_ford.py
+python openpilot/sunnypilot/sunnylink/tools/compile_settings_ui.py --check
+python -m tools.ford_pscm_lab.feedback_replay stress --cycles 200000 --output .cache/ford_c1_feedback/feedback_stress.json
+python -m tools.ford_pscm_lab.stress_model_action --cycles 200000 --seed 20260907 --opendbc-revision c21a9013700734dd20b09e05aa68329ad8cc20f9 --output .cache/ford_c1_feedback/zero_error_stress.json
+python -m tools.ford_pscm_lab.feedback_replay route .cache/ford_routeb8 --output .cache/ford_c1_feedback/routeb8
+```
+
+The last command requires the existing full-rlog b8 extract (`route.npz`,
+`model_paths.npz`, `metadata.json`), identified by hashes in the validation
+record. The historical route90/95 replay deliberately sets measured curvature
+equal to requested curvature to check zero-error compatibility; it does not
+exercise recorded steering feedback.
+
+Enable using the [existing Sunnylink toggle](ford_model_action_drive_test.md).
+The diagnostic identity is `model-action-c1-feedback-v1`.

docs/ford_c1_feedback_validation.json

@@ -0,0 +1,258 @@
+{
+  "created_at_utc": "2026-09-09T14:45:33.853345+00:00",
+  "baseline_commit": "a7d70e2b0890184636827351e4789d866f2a7c97",
+  "deployment_target": {
+    "repository": "sunnypilot/sunnypilot",
+    "branch": "hiimisaac-dev"
+  },
+  "scope": "C1 measured-curvature feedback on restored original v1. Offline software validation only; no predicted or measured physical improvement.",
+  "calibration_approved": false,
+  "toggle": {
+    "key": "FordModelActionController",
+    "default_enabled": false,
+    "activation": "Existing startup selection after offroad-to-onroad cycle"
+  },
+  "feedback_law": "correction += (desired_curvature - measured_curvature) * speed * elapsed_measurement_time, subject to output and PSCM anti-windup",
+  "feedback_strength": "Explicit 1:1 heading-error-to-C1 choice; no fitted PSCM plant or new tunable multiplier",
+  "preserved": [
+    "C0 mapping and limits",
+    "C2=C3=0",
+    "C1 final amplitude and slew limits",
+    "100 Hz sender",
+    "upstream selection and limiting"
+  ],
+  "panda_safety_changed": false,
+  "opendbc_submodule_changed": false,
+  "opendbc_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9",
+  "controller_size": {
+    "total_lines": 181,
+    "code_lines_excluding_blanks_comments_docstrings": 123,
+    "core_persistent_values": 3,
+    "adapter_timestamps": 3
+  },
+  "tests": {
+    "combined_suite": "511 passed, 178 skipped, 9146 subtests passed in 5.14s",
+    "suite_log_sha256": "001ef6633b22513317593dd8debc160a0ca8aaf78ea53418c5f7a50c370cc818",
+    "ruff_changed_python": "pass",
+    "ty_controller": "pass",
+    "settings_compiler_check": "pass",
+    "safety_skip_reasons": [
+      "SKIPPED [145] ../../../../dev/sunnypilot/.venv/lib/python3.12/site-packages/_pytest/unittest.py:523: Skipped",
+      "SKIPPED [9] opendbc_repo/opendbc/safety/tests/common.py:64: Safety mode implements no _user_regen_msg",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:51: Skipping test because MADS button is not supported",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:254: Skipping test because MADS button is not supported",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:67: Skipping test because _acc_state_msg is not implemented for this car",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:165: Skipping test because MADS button is not supported",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:165: Skipping test because ACC main is not supported",
+      "SKIPPED [3] opendbc_repo/opendbc/safety/tests/mads_common.py:411: MADS button not supported",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:378: CAN FD only",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:361: CAN FD only",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:351: CAN FD only",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:327: CAN FD only",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:341: CAN FD only",
+      "SKIPPED [1] opendbc_repo/opendbc/safety/tests/test_ford.py:320: CAN FD only"
+    ],
+    "safety_native_build": "Pinned safety C source is compiled locally by libsafety_py before testing.",
+    "controlsd_to_can_feedback_integration_frames": 1010,
+    "integration_checks": "Both signs: build, hold, unwind, rebuild, immediate driver override; actual 100 Hz sender, counter, checksum, fields and publication. Separate integration tests validate PSCM service forwarding.",
+    "regression_test_evidence": [
+      "Nonzero-error integration failed with zero correction before implementing feedback.",
+      "Both sign tests failed when a reached limit trapped an old opposing correction; they pass after allowing return to zero."
+    ]
+  },
+  "route_b8": {
+    "baseline_revision": "a7d70e2b0890184636827351e4789d866f2a7c97",
+    "baseline_source_sha256": "8f3bc5d68e0051776f614a2ccffae84a88f7898dc95bdc12c23dcfe10dfe676a",
+    "cycles": 160431,
+    "active_cycles": 68217,
+    "validity_and_c0_match_original_v1_exactly": true,
+    "status_counts": {
+      "inactive": 92214,
+      "active": 68217
+    },
+    "feedback_enabled_seconds": 598.256888772994,
+    "pscm_limit_2_seconds": 12.139079590997426,
+    "c1_changed_cycles": 58106,
+    "max_abs_c1_change_rad": 0.29800000000000004,
+    "max_abs_correction_rad": 0.29816844327770786,
+    "can_round_trips": 160431,
+    "timing_limit": "Controls publication time proxies the computation clock; full SubMaster checks are unavailable.",
+    "reference_limit": "Uses exact consumed model publication as reference; the b8 route has no maneuver-plan messages.",
+    "example_points": [
+      {
+        "time_s": 130.9368894940053,
+        "old_c0_c1": [
+          -0.7400000000000002,
+          -0.18700000000000006
+        ],
+        "candidate_c0_c1": [
+          -0.7400000000000002,
+          -0.22899999999999998
+        ],
+        "correction_rad": -0.042171663052515254,
+        "feedback_enabled": true,
+        "pscm_limited": false
+      },
+      {
+        "time_s": 235.3960996990063,
+        "old_c0_c1": [
+          -2.04,
+          -0.40449999999999997
+        ],
+        "candidate_c0_c1": [
+          -2.04,
+          -0.4145
+        ],
+        "correction_rad": -0.00989648519895422,
+        "feedback_enabled": true,
+        "pscm_limited": true
+      },
+      {
+        "time_s": 236.25034470800165,
+        "old_c0_c1": [
+          -1.46,
+          -0.128
+        ],
+        "candidate_c0_c1": [
+          -1.46,
+          -0.10799999999999998
+        ],
+        "correction_rad": 0.01990758350705991,
+        "feedback_enabled": true,
+        "pscm_limited": false
+      },
+      {
+        "time_s": 252.49320156300382,
+        "old_c0_c1": [
+          -0.6699999999999999,
+          -0.16249999999999998
+        ],
+        "candidate_c0_c1": [
+          -0.6699999999999999,
+          -0.20350000000000001
+        ],
+        "correction_rad": -0.040907632902654506,
+        "feedback_enabled": true,
+        "pscm_limited": false
+      },
+      {
+        "time_s": 674.430371745002,
+        "old_c0_c1": [
+          0.4299999999999997,
+          0.128
+        ],
+        "candidate_c0_c1": [
+          0.4299999999999997,
+          0.1345
+        ],
+        "correction_rad": 0.00639271291315417,
+        "feedback_enabled": true,
+        "pscm_limited": false
+      },
+      {
+        "time_s": 1534.5190040400048,
+        "old_c0_c1": [
+          2.62,
+          0.5
+        ],
+        "candidate_c0_c1": [
+          2.62,
+          0.5
+        ],
+        "correction_rad": 0.0,
+        "feedback_enabled": true,
+        "pscm_limited": true
+      },
+      {
+        "time_s": 1562.5074677500015,
+        "old_c0_c1": [
+          -0.1200000000000001,
+          -0.051000000000000045
+        ],
+        "candidate_c0_c1": [
+          -0.1200000000000001,
+          -0.046499999999999986
+        ],
+        "correction_rad": 0.004453988923883501,
+        "feedback_enabled": true,
+        "pscm_limited": false
+      }
+    ]
+  },
+  "route_input_sha256": {
+    "route.npz": "6f5dd369b70eaed4b95b28c8b25c9f2e9b830fa07a334881a185505481667c8b",
+    "model_paths.npz": "939af6cf7e74251d8842581cc078d26d9fbfd22a0d7817cb0e368697d419b615",
+    "metadata.json": "73b439132d1de37ec187b544c04d2b05c80965065515a4b7dec29ba57ae37e7c"
+  },
+  "feedback_stress": {
+    "cycles": 200000,
+    "mirrored_updates": 200000,
+    "can_round_trips": 200000,
+    "checks": "Mirror symmetry, reset/override, amplitude, slew, correction bounds, integration direction/size, PSCM anti-windup, CAN fields.",
+    "scope": "Numerical software invariants only; no model of vehicle motion.",
+    "calibration_approved": false,
+    "controller_sha256": "4499defbb7fc5ddf5029ca42c549f0935b0758b08818c5bf0490fb52221f9a34"
+  },
+  "zero_error_stress": {
+    "seed": 20260907,
+    "random_cycles": 200000,
+    "mirrored_core_updates": 200000,
+    "invalid_or_inactive_resets": 3537,
+    "field_boundary_cases": 18138,
+    "float32_can_round_trips": 218138,
+    "analytic_targets_scalar_slew_and_mirror_checks_pass": true,
+    "direct_raw_float32_packing_matches_host_output": true,
+    "max_continuous_step_c0_c1": [
+      0.40000000000000147,
+      0.05000000000000002
+    ],
+    "calibration_approved": false,
+    "scope": "Zero-error numerical construction: measured equals requested curvature. No PSCM response claims.",
+    "opendbc_import_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9"
+  },
+  "total_lab_float32_can_round_trips": 578569,
+  "artifact_sha256": {
+    ".cache/ford_c1_feedback/routeb8/report.json": "648887eebb76260a60f7c0f0d9aaac83d0f1c06b443e28bc6fdf296bad4526c0",
+    ".cache/ford_c1_feedback/routeb8/commands.npz": "1aef98365572b3fb3cb8ba2a93cf30041ff3be133718d469145b710f2c94dc32",
+    ".cache/ford_c1_feedback/feedback_stress.json": "abf4e7bccc1e460008cc7450fcd92e9b2a6108bd71e53a01bdc24e31e5b5ad32",
+    ".cache/ford_c1_feedback/zero_error_stress.json": "2a3f284e10e5054205a788cce59bcf57bd837e13afff327457244141ba5522f0",
+    ".cache/ford_c1_feedback/safety_skip_reasons.txt": "5384c82b07b7cc20c6b22b8e94246cb104d53f8866af02b28fda7d4138cf377f"
+  },
+  "native_params": {
+    "library_sha256": "270bf43241cf7c02cc432cf78ec9411a62d7653ca445695efe785ae82241aa09",
+    "sources_match_original_rebuild_record": true,
+    "provenance": "Same locally rebuilt native library and source hashes recorded in ford_model_action_drive_test_validation.json; verified for this run."
+  },
+  "test_environment": {
+    "python": "/Users/ibpersonal/dev/sunnypilot/.venv/bin/python",
+    "PYTHONPATH": ".:opendbc_repo:.cache/ford_v6/test_deps",
+    "LOG_ROOT": "/private/tmp/ford-feedback-logs",
+    "PARAMS_ROOT": "/private/tmp/ford-feedback-params",
+    "PYTHONDONTWRITEBYTECODE": "1"
+  },
+  "source_sha256": {
+    "docs/ford_c1_feedback.md": "c1bc7f24c5ebe28679b4a04d09085d7b937926e63a38d43a3abfac93dfcfa0f9",
+    "docs/ford_model_action_candidate.md": "20cd8d10008cd796cc8719f5795ee80f50d8133d6e7684fb057a78fb05323fbe",
+    "docs/ford_model_action_drive_test.md": "7860ae26a61682aff86743ba302eb23c8f271d5700a2e616da1b6b38d438b57d",
+    "opendbc_repo/opendbc/car/vehicle_model.py": "ddc2a93d9c2b2ef6c9a913a5aef4c51e2bc387db1f7640473657e5ade4e50fac",
+    "openpilot/selfdrive/controls/controlsd.py": "2b7e246f00bccce3a2bb9f6f44009ca77690cadb8527cd2bdfe855e9ad72ad1e",
+    "openpilot/selfdrive/controls/lib/drive_helpers.py": "916bcd83c2a909a89795da58c7c43d7b168c9b82e1a6d281484bae45c667c01e",
+    "openpilot/selfdrive/controls/lib/ford_model_action.py": "4499defbb7fc5ddf5029ca42c549f0935b0758b08818c5bf0490fb52221f9a34",
+    "openpilot/selfdrive/controls/lib/ford_path.py": "383538fc7cdae3bc28dffb71fe12ac5f3f9866ffbe6adfb7457f3593e9fc903a",
+    "openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py": "84113b1b7800c868117af0034278f53a1a6153c7bb5fadc1ea45958e62c4f0d0",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action.py": "cbe1b2aa1961deba3a42e1d82f5f75ae0c3d7a219428dea5f50cb70e1b27fd11",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_adapter.py": "c7f5ffd650e804e6e02fa12d435e0867b56b13a49c3d9fa511993188d5cb625a",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_feedback.py": "f7a956c082a246d9506e21adbf348cbdc7f94d5342d832841058c71f7e264eeb",
+    "openpilot/sunnypilot/selfdrive/controls/controlsd_ext.py": "7a13dc5ce49b40e27e05e62cdb9ef1bb764de8ed8167f7e982d54a4dffe97ed4",
+    "openpilot/sunnypilot/sunnylink/settings_ui.json": "7d38f315a7c5ce6d46d01a06f7eaddd4933f85639e5325ff71fdce22866ef401",
+    "openpilot/sunnypilot/sunnylink/settings_ui_src/pages/vehicle.yaml": "410e306958ece12e49fc114707741c57a2dd927c6ba3410e160834e52a759ea9",
+    "tools/ford_pscm_lab/feedback_replay.py": "ca552217953f3cce35da0b1666252fd43b6f8ab6c067e5c9102da8ea8d97c2f3",
+    "tools/ford_pscm_lab/model_action_replay.py": "af97c665f342c66b1be2502e188c63e6f3ee106d0a0d5e80997bc3040373ff9f",
+    "tools/ford_pscm_lab/stress_model_action.py": "0b25188edf2b248ebe741173ce02ce75bd59f1f39fd5bd909d41a3dca2294aa8"
+  },
+  "limitations": [
+    "Frozen route replay changes commands only; it cannot establish tracking, unwind response or closed-loop stability.",
+    "Measured curvature uses the existing steering-angle vehicle model; it is not an independent ground-path measurement.",
+    "No full device build, device boot, installation or road validation was performed."
+  ]
+}

docs/ford_c1_overflow.md

@@ -0,0 +1,131 @@
+# Ford base-heading overflow experiment
+
+This records the overflow implementation and validation at `b81c00f5b`.
+The later [toggle-off restoration](ford_upstream_fallback.md) updates selection
+and the opendbc sender while preserving the enabled experiment's command law.
+
+The Lightning ca route recorded controller `959ae3d6e`. Its large turns included
+flat C1 requests at ±0.5 rad while C0 still had available range. Those were
+nonzero, active commands, but increasing base heading above the C1 limit was
+discarded. Other apparent pauses followed reductions in the selected model
+request; this change continues to follow those reductions.
+
+The new experiment allocates clipped-away **base heading** to C0 using the
+existing 7 m reference. It does not allocate the accumulated feedback correction.
+This is a hypothesis about command allocation, not a measured improvement in
+PSCM response or a claim that C0 and C1 are physically interchangeable.
+
+## Command rule
+
+Using the selected, upstream-limited desired curvature:
+
+```text
+raw_base_c1 = max(7 m, speed × 1 s) × desired_curvature
+base_c1 = clip(raw_base_c1, -0.5 rad, +0.5 rad)
+extra_c0 = 7 m × (raw_base_c1 - base_c1)
+c0_target = clip(model_y_at_7m + extra_c0, -5.11 m, +5.11 m)
+```
+
+The combined C0 target still passes through the existing 4 m/s slew limit.
+C1 retains its existing feedback, ±0.5 rad amplitude and 0.5 rad/s slew limits.
+C2 and C3 remain zero. Short model paths retain their existing endpoint hold.
+
+Before amplitude/slew limits, the allocation preserves the linear reference
+`C0 + 7*C1` for the base request. This is a single-reference identity; it does
+not preserve the entire path or predict steering torque. The 7 m reference is
+an existing engineering choice. No fitted plant, new tunable strength multiplier,
+timer or stored overflow is added. The existing 1:1 feedback strength remains.
+
+Extra C0 falls with raw base heading and its target becomes zero at the C1 cap.
+The output can take longer to return because of its existing slew state. There
+is no guarantee that increasing C0 makes every PSCM turn better or release sooner.
+
+## Preserved integration
+
+The conditional correction release still requires **original model C0** and
+applied C0 to confirm base C1's direction. Added overflow cannot itself substitute
+for model confirmation. Changed applied C0 can nevertheless affect release
+timing in some histories. Driver/PSCM arbitration, service freshness, resets,
+upstream curvature limiting, Float32 publication and the 100 Hz sender remain.
+No opendbc dependency or Panda safety change is made.
+
+The existing default-off Sunnylink toggle selects this version on any Ford
+CAN FD vehicle. Diagnostic identity is `model-action-c1-feedback-v3`.
+`offset_overflow` records extra target meters before C0 amplitude and slew;
+`offset_request` continues to record the actual continuous C0 state.
+See the [drive-test instructions](ford_model_action_drive_test.md).
+
+## Offline evidence
+
+The focused overflow regressions initially produced 28 failures and 18 passes
+against the prior controller. They now pass. They cover both signs, several
+speeds, the heading threshold, combined C0 clipping, short paths, release,
+feedback-only saturation, driver/PSCM feedback gates and independent model
+confirmation. Twelve integration cases send 4,800 frames through actual
+controlsd selection/limiting, Float32 publication and Ford CAN packing on all
+six listed Ford CAN FD platforms, checking counters and checksums.
+
+The combined suite passes **670 tests and 9,146 subtests**, with 178 inherited
+or unsupported safety-test skips. Both 200,000-cycle randomized runs pass,
+including mirrored inputs, independent scalar target/slew checks, feedback
+invariants, comparison with the exact prior controller from cloned states,
+and 18,138 exhaustive field/Float32 boundary cases. These checks and the ca
+replay total **745,586 Float32/CAN round trips**, in addition to integration tests.
+
+Frozen ca replay covers 327,448 control cycles across all 55 extracted segments.
+Activation is identical; C1, C2 and C3 are identical on every cycle. C0 differs
+for 855 cycles (8.607 s), concentrated in the large turns and their slew tails.
+The extra target is present for 7.359 s. Before the first overflow, every command
+matches the prior controller. All disabled cycles have zero commands.
+
+At the same recorded peak-request timestamps, absolute packed C0 changes as follows:
+
+| Segment | Previous C0 | Candidate C0 | C1 magnitude, both |
+| --- | ---: | ---: | ---: |
+| 10 | 3.90 m | 5.11 m | 0.50 rad |
+| 31 | 2.85 m | 3.08 m | 0.50 rad |
+| 35 | 3.67 m | 5.11 m | 0.50 rad |
+| 52 | 3.11 m | 3.42 m | 0.50 rad |
+
+The candidate reaches the existing C0 cap for 2.054 s. These are reconstructed
+commands on original inputs, not newly transmitted commands or predicted wheel
+angles. Segment 52's output is still slewing at the selected timestamp.
+
+Every overflow episode returns to the previous C0 output without a reset or
+another overflow interrupting the comparison. After overflow first becomes
+zero, the longest output tails are **0.475 s in segment 10** and **0.712 s in
+segment 35**. This is the added slew tail relative to the prior command, not
+the truck's physical release delay. It is a material behavior to inspect during
+controlled evaluation: more pull through capped turns may also add hanging
+on exit. Ordinary requests below the cap retain the original target mapping.
+
+The recorded model, vehicle motion, driver input and PSCM flags remain fixed.
+Replay cannot establish resulting tracking, centering, torque or stability.
+The route has no maneuver-plan messages; the replay uses the consumed model
+reference and recorded selected curvature. Computation time is approximated
+by control publication time, and full SubMaster health checks are unavailable.
+No device build, boot or installation is performed offline.
+
+## Reproduction
+
+Numeric results and source hashes are in `ford_c1_overflow_validation.json`.
+Use native project dependencies and pinned opendbc
+`c21a9013700734dd20b09e05aa68329ad8cc20f9`. The ca replay requires the existing
+full-rlog extract (`route.npz`, `model_paths.npz`, `metadata.json`).
+The following commands apply to this version; earlier validation documents
+record their named historical controllers.
+
+```sh
+export PYTHONDONTWRITEBYTECODE=1
+export PYTHONPATH=.:opendbc_repo
+python -m pytest -q -p no:cacheprovider openpilot/selfdrive/controls/tests/test_ford_*.py tools/ford_pscm_lab openpilot/selfdrive/car/tests/test_ford_pscm_status.py openpilot/sunnypilot/sunnylink/tests openpilot/common/tests/test_params.py opendbc_repo/opendbc/car/ford/tests/test_ford.py opendbc_repo/opendbc/safety/tests/test_ford.py
+python -m tools.ford_pscm_lab.feedback_replay stress --cycles 200000 --output .cache/ford_c1_overflow/stress.json
+python -m tools.ford_pscm_lab.stress_model_action --cycles 200000 --seed 20260910 --opendbc-revision c21a9013700734dd20b09e05aa68329ad8cc20f9 --output .cache/ford_c1_overflow/zero_error_stress.json
+python -m tools.ford_pscm_lab.feedback_replay route .cache/ford_routeca --baseline 959ae3d6e76c479f48e081c060b0f3569a6f15f4 --output .cache/ford_c1_overflow/routeca
+python openpilot/sunnypilot/sunnylink/tools/compile_settings_ui.py --check
+```
+
+For slew-tail analysis, in the replay's `commands.npz` find each nonzero run of
+`offset_overflow`. From its first zero sample, measure until packed candidate
+and baseline C0 agree within 1e-8 m, stopping separately at another overflow or
+inactive cycle. Sum sample durations capped at 30 ms for weighted time totals.

docs/ford_c1_overflow_validation.json

@@ -0,0 +1,307 @@
+{
+  "created_at_utc": "2026-09-10T22:04:22.589047+00:00",
+  "scope": "Base heading overflow allocated to C0; frozen-input command verification only, no vehicle response prediction.",
+  "baseline_commit": "959ae3d6e76c479f48e081c060b0f3569a6f15f4",
+  "baseline_source_sha256": "47fff1fd1bd7e65ca6d6b437fa9d2e8a864d421622d9efdfe0fe04b927c6d972",
+  "deployment_target": {
+    "repository": "sunnypilot/sunnypilot",
+    "branch": "hiimisaac-dev"
+  },
+  "hypothesis": "model-action-c1-feedback-v3",
+  "calibration_approved": false,
+  "toggle": {
+    "key": "FordModelActionController",
+    "default_enabled": false,
+    "eligibility": "Any Ford CAN FD",
+    "activation": "Existing controlsd startup selection"
+  },
+  "command_rule": "extra C0 = 7 m * (raw base C1 - clip(raw base C1, -0.5, 0.5)); add to original model C0, then existing C0 amplitude/slew limits.",
+  "engineering_choices": "Single-reference linear allocation at existing 7 m. No new tuning parameter or stored overflow. Does not establish physical C0/C1 interchangeability. Existing 1:1 integral feedback strength remains.",
+  "output_limits": {
+    "c0_m": [
+      -5.11,
+      5.11
+    ],
+    "c1_rad": [
+      -0.5,
+      0.5
+    ],
+    "c0_slew_m_s": 4.0,
+    "c1_slew_rad_s": 0.5,
+    "c2": 0.0,
+    "c3": 0.0
+  },
+  "preserved": [
+    "Upstream reference selection/limiting",
+    "Driver and PSCM arbitration",
+    "Freshness/reset gates",
+    "C1 feedback law",
+    "Original model C0 required for carryover confirmation",
+    "100 Hz CAN sender",
+    "Float32 publication"
+  ],
+  "controller_command_state_values": 3,
+  "controller_diagnostic_counters": 1,
+  "controller_total_lines": 200,
+  "opendbc_submodule_changed": false,
+  "panda_safety_changed": false,
+  "opendbc_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9",
+  "tests": {
+    "combined_suite": "670 passed, 178 skipped, 9146 subtests passed in 5.77s",
+    "safety_skips": "Inherited or unsupported variants; unchanged from prior feedback validations.",
+    "new_core_regressions": "Before implementation: 28 failed, 18 passed; after: all 46 pass.",
+    "overflow_controlsd_to_can_cases": 12,
+    "overflow_controlsd_to_can_frames": 4800,
+    "integration_scope": "All six listed CAN FD platforms; both signs; selected upstream-limited request, release, limits, Float32 publication, decoded commands, zero C2/C3, active mode, counters, checksums.",
+    "ruff_changed_python": "pass",
+    "ty_controller": "pass",
+    "git_diff_check": "pass",
+    "settings_compiler_check": "pass"
+  },
+  "stress": {
+    "cycles": 200000,
+    "mirrored_updates": 200000,
+    "can_round_trips": 200000,
+    "carryover_release_count": 864,
+    "baseline_revision": "959ae3d6e76c479f48e081c060b0f3569a6f15f4",
+    "baseline_source_sha256": "47fff1fd1bd7e65ca6d6b437fa9d2e8a864d421622d9efdfe0fe04b927c6d972",
+    "exact_unchanged_state_and_commands_without_overflow": 56061,
+    "checks": "Mirror symmetry, reset/override, amplitude, slew, correction bounds, carryover direction/confirmation, integration, PSCM limits, CAN.",
+    "scope": "Numerical software invariants only; no model of vehicle motion.",
+    "calibration_approved": false
+  },
+  "zero_error_stress": {
+    "seed": 20260910,
+    "random_cycles": 200000,
+    "mirrored_core_updates": 200000,
+    "invalid_or_inactive_resets": 3537,
+    "field_boundary_cases": 18138,
+    "float32_can_round_trips": 218138,
+    "analytic_targets_scalar_slew_and_mirror_checks_pass": true,
+    "direct_raw_float32_packing_matches_host_output": true,
+    "max_continuous_step_c0_c1": [
+      0.4000000000000019,
+      0.05000000000000002
+    ],
+    "calibration_approved": false,
+    "scope": "Zero-error numerical construction: measured equals requested curvature. No PSCM response claims.",
+    "opendbc_import_head": "c21a9013700734dd20b09e05aa68329ad8cc20f9"
+  },
+  "route_ca": {
+    "baseline_revision": "959ae3d6e76c479f48e081c060b0f3569a6f15f4",
+    "baseline_source_sha256": "47fff1fd1bd7e65ca6d6b437fa9d2e8a864d421622d9efdfe0fe04b927c6d972",
+    "calibration_approved": false,
+    "cycles": 327448,
+    "active_cycles": 118756,
+    "validity_matches_baseline_exactly": true,
+    "status_counts": {
+      "inactive": 208692,
+      "active": 118756
+    },
+    "c0_matches_baseline_exactly": false,
+    "c0_changed_cycles": 855,
+    "max_abs_c0_change_m": 2.2,
+    "offset_overflow_seconds": 7.359375754000212,
+    "max_abs_offset_overflow_target_m": 2.867466852068901,
+    "feedback_enabled_seconds": 1128.448330694985,
+    "pscm_limit_2_seconds": 1.5229074359986043,
+    "c1_changed_cycles": 0,
+    "max_abs_c1_change_rad": 0.0,
+    "max_abs_correction_rad": 0.13238253764709199,
+    "can_round_trips": 327448,
+    "timing_limit": "Controls publication time proxies the computation clock; full SubMaster checks are unavailable.",
+    "reference_limit": "Uses exact consumed model publication as reference; selected maneuver-plan messages are not reconstructed.",
+    "carryover_release_count": 32
+  },
+  "route_ca_release": {
+    "scope": "Describe candidate command tails on frozen ca measurements, not wheel response.",
+    "changed_c0_seconds": 8.606610047996583,
+    "overflow_target_seconds": 7.359375754000212,
+    "changed_c0_without_current_overflow_seconds": 1.4386431469993113,
+    "candidate_c0_at_cap_seconds": 2.054423716999736,
+    "baseline_c0_at_cap_seconds": 0.0,
+    "all_c1_c2_c3_match_baseline_exactly": true,
+    "all_pre_overflow_commands_match_baseline_exactly": true,
+    "all_inactive_commands_zero": true,
+    "windows": [
+      {
+        "start_s": 645.4515506280004,
+        "last_overflow_s": 647.9591778859995,
+        "duration_s": 2.5175176129996544,
+        "extra_target_peak_m": 2.867466852068901,
+        "c0_change_peak_m": 2.2,
+        "post_overflow_tail_s": 0.4753179760009516,
+        "tail_end_s": 648.444386217001,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 1896.7594062080007,
+        "last_overflow_s": 1897.0382758169999,
+        "duration_s": 0.29005605599923,
+        "extra_target_peak_m": 0.16229432076215744,
+        "c0_change_peak_m": 0.16999999999999993,
+        "post_overflow_tail_s": 0.0,
+        "tail_end_s": 1897.0494622639999,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 1897.3739526980007,
+        "last_overflow_s": 1897.4413651220002,
+        "duration_s": 0.0802515539999149,
+        "extra_target_peak_m": 0.049945808947086334,
+        "c0_change_peak_m": 0.04999999999999982,
+        "post_overflow_tail_s": 0.0,
+        "tail_end_s": 1897.4542042520006,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 1897.492552009,
+        "last_overflow_s": 1897.681751143,
+        "duration_s": 0.19981637000091723,
+        "extra_target_peak_m": 0.10685679316520691,
+        "c0_change_peak_m": 0.11000000000000032,
+        "post_overflow_tail_s": 0.01193945599879953,
+        "tail_end_s": 1897.7043078349998,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 1897.743499225,
+        "last_overflow_s": 1897.7842587169998,
+        "duration_s": 0.05174380599964934,
+        "extra_target_peak_m": 0.04502199590206146,
+        "c0_change_peak_m": 0.040000000000000036,
+        "post_overflow_tail_s": 0.011911696001334349,
+        "tail_end_s": 1897.807154727001,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 1897.9437203819998,
+        "last_overflow_s": 1899.2943476260007,
+        "duration_s": 1.361525778000214,
+        "extra_target_peak_m": 0.22848158329725266,
+        "c0_change_peak_m": 0.22999999999999954,
+        "post_overflow_tail_s": 0.021877274999496876,
+        "tail_end_s": 1899.3271234349995,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 2146.154050938001,
+        "last_overflow_s": 2146.185627021001,
+        "duration_s": 0.04039318899958744,
+        "extra_target_peak_m": 0.045987628400325775,
+        "c0_change_peak_m": 0.050000000000000266,
+        "post_overflow_tail_s": 0.034061254000334884,
+        "tail_end_s": 2146.228505381001,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 2146.2950925490004,
+        "last_overflow_s": 2146.5387542179997,
+        "duration_s": 0.25293986199903884,
+        "extra_target_peak_m": 0.21167446672916412,
+        "c0_change_peak_m": 0.17999999999999972,
+        "post_overflow_tail_s": 0.040063559001282556,
+        "tail_end_s": 2146.5880959700007,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 2146.6577708509994,
+        "last_overflow_s": 2148.3543101739997,
+        "duration_s": 1.7074812410010054,
+        "extra_target_peak_m": 2.0555079206824303,
+        "c0_change_peak_m": 1.58,
+        "post_overflow_tail_s": 0.7118495689992415,
+        "tail_end_s": 2149.0771016609997,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 3121.067818462001,
+        "last_overflow_s": 3121.8665919270006,
+        "duration_s": 0.8071899679998751,
+        "extra_target_peak_m": 0.5380096957087517,
+        "c0_change_peak_m": 0.5099999999999998,
+        "post_overflow_tail_s": 0.06879738699899463,
+        "tail_end_s": 3121.943805817,
+        "tail_ended_by": "matches baseline"
+      },
+      {
+        "start_s": 3122.0664172689994,
+        "last_overflow_s": 3122.105900957,
+        "duration_s": 0.05046031700112508,
+        "extra_target_peak_m": 0.008371405303478241,
+        "c0_change_peak_m": 0.010000000000000231,
+        "post_overflow_tail_s": 0.02107719199921121,
+        "tail_end_s": 3122.1379547779998,
+        "tail_ended_by": "matches baseline"
+      }
+    ],
+    "example_points": [
+      {
+        "segment": 10,
+        "time_s": 646.7503591629993,
+        "baseline_c0_m": 3.9000000000000004,
+        "candidate_c0_m": 5.11,
+        "extra_c0_target_m": 2.867466852068901,
+        "baseline_c1_rad": 0.5,
+        "candidate_c1_rad": 0.5
+      },
+      {
+        "segment": 31,
+        "time_s": 1898.0837712450011,
+        "baseline_c0_m": -2.8499999999999996,
+        "candidate_c0_m": -3.079999999999999,
+        "extra_c0_target_m": -0.22848158329725266,
+        "baseline_c1_rad": -0.5,
+        "candidate_c1_rad": -0.5
+      },
+      {
+        "segment": 35,
+        "time_s": 2147.4098699660008,
+        "baseline_c0_m": 3.67,
+        "candidate_c0_m": 5.11,
+        "extra_c0_target_m": 2.0555079206824303,
+        "baseline_c1_rad": 0.5,
+        "candidate_c1_rad": 0.5
+      },
+      {
+        "segment": 52,
+        "time_s": 3121.239466367,
+        "baseline_c0_m": 3.11,
+        "candidate_c0_m": 3.42,
+        "extra_c0_target_m": 0.5380096957087517,
+        "baseline_c1_rad": 0.5,
+        "candidate_c1_rad": 0.5
+      }
+    ]
+  },
+  "route_ca_input_sha256": {
+    "route.npz": "ae9d46770eaf0dbbac6af86aebc926320eed0cf114eb43d5f78b0676e8e0dbf9",
+    "model_paths.npz": "bf17deb442383aaa79432566cd382df24a1bbbbd0521d0cafab956618f5bdd96",
+    "metadata.json": "a759d5cdf878df8b05d91db637b1935b6b4bdd87af96f0f256b67e7d809b3525"
+  },
+  "lab_can_round_trips_excluding_integration": 745586,
+  "validation_environment": {
+    "python": "/Users/ibpersonal/dev/sunnypilot/.venv/bin/python",
+    "PYTHONPATH": ".:opendbc_repo:.cache/ford_v6/test_deps",
+    "PYTHONDONTWRITEBYTECODE": "1",
+    "LOG_ROOT": "/private/tmp/ford-overflow-logs",
+    "PARAMS_ROOT": "/private/tmp/ford-overflow-params"
+  },
+  "source_sha256": {
+    "openpilot/selfdrive/controls/lib/ford_model_action.py": "90269d748d55558bf2495d3b4afcfd7429f373108df1f9259e154d1b92184262",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_overflow.py": "9086434d2b76ab51f69ef08c4f0033c4eaa1950083cc9cce4b34279eb17c5b1b",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_adapter.py": "dc552f3088b7e437a928f349989b74c4e7772d2a88b14a93e933ea8b8344d23b",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action.py": "4e82101463c5d83f6b1f72ba4918c2b37731bc2db6ec7e29e6b402ea67276db2",
+    "openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py": "6b73e70b120527275a9e4e3dff07dd7d19648da517402187d57a90ba09b017eb",
+    "tools/ford_pscm_lab/feedback_replay.py": "7c65515d37aac900eaaef8451a7d643b72c566a2366651f843de2ffca5f24b8d",
+    "tools/ford_pscm_lab/stress_model_action.py": "cec2619285dd41274562ac035ee8ea0a389269a0c4ef1b62efa6252ad1a714aa",
+    "openpilot/sunnypilot/sunnylink/settings_ui_src/pages/vehicle.yaml": "3ae6b16a8c267ab181e00f4b59be8b65134480bec26c8c039bcbae88cb745feb",
+    "openpilot/sunnypilot/sunnylink/settings_ui.json": "ba803819751b304e82936a95902afae63ff88e16e64988622715a7b713f3b982"
+  },
+  "limitations": [
+    "Recorded vehicle motion does not react to changed commands.",
+    "Computation time proxies and service-check reconstruction limits apply.",
+    "C0 slew can leave extra command after overflow stops; maximum observed tail 0.712 s.",
+    "No device build, boot, installation, road tracking or physical stability validation."
+  ]
+}

docs/ford_model_action_candidate.md

@@ -0,0 +1,155 @@
+# Offline Ford selected-action candidate
+
+This document and `ford_model_action_validation.json` record the offline
+stage committed as `7ca3c6e3b`. The candidate is now available behind a
+separate default-off Sunnylink toggle; see
+[drive-test setup and validation](ford_model_action_drive_test.md).
+The counts, source hashes and selector status below describe that earlier
+stage. The current experiment adds [measured-curvature C1 feedback](ford_c1_feedback.md)
+to this original mapping; the historical no-feedback description below is
+not the current controller specification.
+
+The decision is `C0 = current model y(7 m)`,
+`C1 = max(7 m, speed × 1 s) × selected upstream-limited desiredCurvature`,
+with C2=C3=0. The 7 m station and one-second scale are engineering choices,
+not identified PSCM gains. `calibration_approved=false`.
+
+`openpilot/selfdrive/controls/lib/ford_model_action.py` contains the core
+and a separate adapter compatible with the existing controlsd call.
+At that stage, the production selector, v8 implementation, settings, opendbc
+submodule and Panda safety remained unchanged. Tests injected the adapter
+offline; there was no production setting. No hardware or CAN transmission
+occurs in the lab tools.
+
+## Construction and integration
+
+Only the unquantized C0 and C1 slew positions persist in the core.
+Each field is clipped independently (±5.11 m / ±0.5 rad), slewed independently
+(4 m/s / 0.5 rad/s), then packed using the existing Float32/sign-negation
+rounding contract (0.01 m / 0.0005 rad). Heading overflow is not transferred
+to C0. No yaw integral, blend, additional curvature contribution, reference
+filter, turn modes, or 10 m C1 cap is introduced.
+
+The selected standalone implementation from worktree 3548 is the provenance
+for this law. Its two-state packer has been moved into the library core so
+the controller does not depend on experimental lab code. Invalid numeric
+types, overflowing arc geometry and malformed paths reset the core instead
+of throwing or retaining a command.
+
+Arc stations use cumulative model x/y distance, not forward x. As in the
+reviewed standalone core, a path ending before 7 m holds its available
+endpoint instead of extrapolating. This matters: route95 contains 44 active
+cycles with 5.45–6.94 m of path at 2.78–3.46 m/s. A tested strict 7 m
+coverage gate would have introduced disengagements and was removed. There
+is no speed-dependent C0 horizon beyond this existing endpoint behavior.
+
+The adapter retains the existing input age allowance (−5 to +150 ms),
+speed domain (0.3–55 m/s), yaw sanity bound (±3 rad/s), selected curvature
+sanity bound (±1/m), and control interval (2–100 ms). It rejects backward
+model/measurement timestamps and invalid services. Repeated timestamps may
+continue slew, but geometry is validated again on each tick. Disengagement,
+invalid inputs and timing faults clear all command and adapter timing state.
+The first valid tick after reset uses 10 ms, as v8 does.
+
+controlsd still owns reference selection, upstream curvature limiting,
+service health and engagement. Tests execute its actual source-selection
+and limiter code, its Ford call, Float32 publication in ControlsExt, conversion
+to CarControlSP, and the pinned Ford CarController's in-memory CAN builder.
+Both model-action and maneuver-planner selection are covered, including
+disabling latActive after invalid output. Only the test chooses the adapter.
+
+Yaw is not an input to the control law. The adapter checks it solely for the
+inherited invalid-input policy. Driver override and optional PSCM status
+do not modify the candidate base; existing engagement and downstream driver
+arbitration remain responsible for authorization, as with v8's base request.
+
+## Offline evidence
+
+The checked-in `ford_model_action_validation.json` records the completed
+checks and source hashes. Full arrays and detailed reports are generated
+locally under `.cache/ford_model_action/`; original route files are read-only.
+
+Completed validation: **264 Ford tests and 150 subtests pass**, including
+120 new core/adapter/replay-validator cases. The candidate module has 100%
+statement and branch coverage (78 statements, 24 branches). Ruff and Ty pass.
+The 200,000-cycle numerical stress test also checks 200,000 mirrored core
+updates and 18,138 field-boundary cases. Across route and stress runs,
+485,238 Float32/CAN round trips pass. Eight deliberately injected faults
+(heading gain/cap, erased C0, wrong C0 slew, retained invalid state, stale
+model acceptance, model clock rollback and reversed C0 sign) are all caught
+by the tests. Mutation runs replace code only inside isolated Python
+processes; production source files are never modified by those probes.
+
+Independent Standards and Spec reviews reported zero findings. The full
+suite's Params setting test uses an existing local native library from
+worktree 3548 after checking relevant source files are byte-identical;
+its hash and provenance are in the manifest. That library is an ignored
+test dependency, not part of this change. This is the full relevant Ford
+suite, not the hardware-dependent test suite for every openpilot subsystem.
+
+The replay has two separate passes:
+
+* Core compatibility uses the archived eligibility mask and requires exact
+  equality with the independently implemented `action_heading` commands.
+* Adapter reconstruction derives eligibility from recorded service streams
+  independently of the archived output mask. It retains original timestamps,
+  gaps and consumed model frames. Controls publication time proxies the
+  unlogged computation clock, and complete SubMaster health is unavailable.
+
+All 54,738 route95 and 78,812 route90 core cycles match exactly, including
+37,614 and 73,055 active cycles. The adapter preserves those active counts.
+Its 59 / 19 changed commands arise solely from the fresh 10 ms engagement
+tick instead of the archived harness's preceding publication interval;
+the replay checks that attribution on every cycle. Maximum differences are
+0.01 m / 0.001 rad (95) and 0.02 m / 0.002 rad (90).
+
+Every core and adapter replay output is round-tripped through Float32 and
+the real CAN packer/parser, including zero C2/C3, signs, mode and counter.
+Continuous field slew and quantization allowance are checked separately
+from immediate invalid-command resets. The original driver-clean cohorts,
+speed strata and command RMS are reproduced without redoing the encoder search.
+
+The numerical stress harness uses analytic rotated paths, scalar slew
+arithmetic, mirrored requests, irregular intervals and invalid-input resets.
+It also sweeps every representable host field value and the Float32 values
+immediately below, at and above every half-quantum boundary. Direct CAN
+packing of the continuous state must agree with the host's quantized output.
+The unit tests cover releases, reversals, clipping, service freshness,
+clock resets, malformed inputs, endpoint fallback and actual integration.
+
+## Limits of the result
+
+On turns at ≥15 m/s, candidate C0 RMS is 79%/81% below v8 on routes95/90,
+while C1 is 33%/41% higher. Those are command changes, not evidence of
+equivalent steering authority. The PSCM's independent C0/C1 response remains
+unknown. Replay cannot establish physical model following, strong turns,
+centering, overshoot, oscillation or closed-loop stability.
+
+The release probe is intentionally explicit: a model bend can increase
+while selected curvature decreases. At 20 m/s, one synthetic probe changes
+C0/C1 from 0.24 m / 0.10 rad to 0.49 m / 0.08 rad. Zero selected curvature
+sets the C1 target to zero but does not erase a nonzero current model C0.
+Removing a yaw-integral tail does not prove that physical overshoot is solved.
+No additional release policy or unsupported plant model is added to hide
+that uncertainty.
+
+## Reproduce
+
+From this worktree, use the logged construction dependency explicitly:
+
+```sh
+export PYTHONDONTWRITEBYTECODE=1
+export PYTHONPATH=.:/Users/ibpersonal/.codex/worktrees/b926/sunnypilot/opendbc_repo
+PY=/Users/ibpersonal/dev/sunnypilot/.venv/bin/python
+EVIDENCE=/Users/ibpersonal/.codex/worktrees/3548/sunnypilot/analysis/controller_search_20260904
+$PY -m pytest -q -p no:cacheprovider openpilot/selfdrive/controls/tests/test_ford_*.py tools/ford_pscm_lab openpilot/selfdrive/car/tests/test_ford_pscm_status.py
+$PY -m tools.ford_pscm_lab.model_action_replay "$EVIDENCE/route95" --output .cache/ford_model_action/route95
+$PY -m tools.ford_pscm_lab.model_action_replay "$EVIDENCE/route90" --output .cache/ford_model_action/route90
+$PY -m tools.ford_pscm_lab.stress_model_action --cycles 200000 --seed 20260907 --output .cache/ford_model_action/stress.json
+```
+
+The route replay refuses an opendbc revision other than
+`72a775d35e54c21ff5c5798acef22016eedcc0a7`. Stress defaults to this pin and
+also accepts an explicitly required commit with `--opendbc-revision` for
+deployment checks. A mismatch still fails. This historical pin reproduces
+logged construction; it does not change the merge's submodule pointer.

docs/ford_model_action_drive_test.md

@@ -0,0 +1,72 @@
+# Ford selected-action drive-test branch
+
+The current experiment adds [measured-curvature C1 feedback](ford_c1_feedback.md)
+and [conditional correction release](ford_c1_carryover.md) to the restored
+original v1 mapping, with [base C1 overflow allocated to C0](ford_c1_overflow.md).
+It is selectable on **any Ford CAN FD vehicle**
+through the existing persistent, default-off Sunnylink
+toggle. Offline checks establish software behavior; physical tracking,
+turn-exit behavior and closed-loop stability remain unvalidated.
+
+## Select and restore
+
+1. Install branch `hiimisaac-dev` from `sunnypilot/sunnypilot` using the device's
+   normal branch-switch process and allow its build to finish.
+2. While offroad, open Sunnylink device settings → Vehicle → Ford and enable
+   **Selected-Action Path Tracking (Experimental)** (`FordModelActionController`).
+3. Complete a real offroad-to-onroad cycle. Selection occurs when `controlsd`
+   starts; a stored toggle change or disengagement alone cannot swap an active
+   controller. Initial physical evaluation remains controlled testing.
+
+The startup event `Ford path controller selected` should report
+`FordModelActionController`. Periodic `Ford C2-free path tracking` events
+identify **`hypothesis=model-action-c1-feedback-v3`**. They report desired and
+measured curvature, base heading, accumulated correction, applied heading,
+feedback timing and driver/PSCM gating. `carryover_release_count` counts
+conditional releases since the last controller reset; it does not control
+steering. `offset_overflow` reports the extra C0 target in meters before C0
+amplitude and slew limits. `calibration_approved=false` remains.
+
+Turning the toggle off and completing another offroad-to-onroad cycle restores
+**upstream Ford curvature control**: 20 Hz steering messages, limited mode on
+CAN FD, zero C0/C1/C3, and upstream curvature limiting and platform-specific
+overshoot handling. Stored observer or retired controller settings cannot select
+a custom controller. The observer toggle is no longer exposed. The experiment
+only runs on Ford CAN FD vehicles; legacy Ford uses upstream control as well.
+See [toggle-off validation](ford_upstream_fallback.md).
+
+## Wiring and validation
+
+`controlsd` supplies the selected, upstream-limited desired curvature and the
+measured steering-derived curvature already used in its tracking diagnostics.
+Fresh steering publications advance C1 feedback. Repeated publications may
+advance output slew but cannot integrate the same elapsed interval twice.
+Driver override clears the correction. A fresh PSCM reached-limit flag stops
+extra outward accumulation while preserving unwind and base model changes.
+With fresh feedback, the controller can discard an opposing correction when
+it prevents C1 from following the direction shared by original model C0, applied C0
+and base C1, while measured curvature is still opposite. Neutral or conflicting
+C0 and matched curvature preserve the correction. Final output slew still applies.
+
+C0 starts with the original 7 m model-path mapping. When the raw base heading
+exceeds ±0.5 rad, C0 additionally receives 7 m times the clipped-away heading.
+Accumulated C1 feedback does not spill into C0. The extra target returns to zero
+as the base heading falls below the cap; applied C0 still follows its 4 m/s slew.
+C2 and C3 remain zero. The
+existing output limits, 100 Hz custom sender and Float32 publication remain in
+place. An explicit selection flag distinguishes upstream mode from an invalid
+experimental command; invalid experimental input cannot switch to upstream.
+The opendbc sender restores upstream behavior when that flag is false.
+
+See [the overflow specification and validation](ford_c1_overflow.md) and
+`ford_c1_overflow_validation.json` for current evidence and reproduction
+commands. The carryover specification and `ford_c1_carryover_validation.json`
+record the previous experiment. `ford_c1_feedback_validation.json` records the initial feedback
+version at `5fbb583e5`. `ford_model_action_validation.json` and
+`ford_model_action_drive_test_validation.json` are historical records for the
+original offline candidate and its first wiring, respectively; their counts
+and coverage are not claims about the current version.
+
+The full hardware build and device boot are not performed by these offline
+checks. Pushing the branch does not install it on the device or change its
+stored toggle.

docs/ford_model_action_drive_test_validation.json

@@ -0,0 +1,145 @@
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docs/ford_model_action_validation.json

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+    "tools/ford_pscm_lab/model_action_replay.py": "c114c479bd22e4fc61a3e8d3ee7fae5d71d1d80ec4b952faad8f8f3692fb1508",
+    "tools/ford_pscm_lab/stress_model_action.py": "a78a50eed1f801f3b096d694ab8c2fd70804b6c250465b4152f38d83770a982b",
+    "tools/ford_pscm_lab/test_model_action_replay.py": "09d024c59d44b83ec081d6416d0f946a7719a73f22213af1f4ddc03dc4e6f4ac"
+  },
+  "artifacts": {
+    "directory": ".cache/ford_model_action",
+    "route_reports": [
+      "route95/report.json",
+      "route90/report.json"
+    ],
+    "stress_report": "stress.json",
+    "mutation_report": "mutations/report.json",
+    "test_log": "ford_suite.txt"
+  }
+}

docs/ford_upstream_fallback.md

@@ -0,0 +1,89 @@
+# Ford toggle-off upstream restoration
+
+`FordModelActionController` is the only setting that can select custom Ford
+steering. It defaults false. With it false or absent, no custom path controller
+is created and normal lateral-control curvature passes unchanged to the Ford
+sender. A stored `FordPscmObserver` or retired virtual-angle setting cannot
+override that choice. The observer toggle is removed from Sunnylink; its stored
+parameter remains readable for compatibility but has no selection effect.
+
+Selection remains fixed for the lifetime of controlsd. Sunnylink changes require
+a real offroad-to-onroad cycle, as before. The startup diagnostic reports
+`controller=upstream` when the experiment is not selected.
+
+## Sender behavior
+
+The new `fordLateralPath.enabled` field conveys startup selection independently
+of `valid`. Its default is false. The sender uses custom mode only when this
+field is true on a Ford CAN FD vehicle. This prevents invalid model geometry
+or disengagement in the selected experiment from choosing a different controller.
+
+Toggle-off restores the upstream Ford sender:
+
+- 20 Hz steering messages on both CAN FD and legacy Ford.
+- CAN FD limited mode 1 while active, mode 0 while inactive, with upstream ramp
+  type 0, counters and checksums.
+- C0, C1 and C3 zero; C2 follows upstream actuator curvature.
+- Upstream curvature amplitude/rate limits and the measured-curvature error
+  clamp above 9 m/s.
+- Upstream anti-overshoot handling for Bronco Sport and F-150 MK14.
+
+The reference is the upstream implementation already merged into this branch,
+opendbc `f95f996f5917dcbbf2e32fe51b606a24cf836af6`. Its Ford sender differs from
+the locally available comma opendbc `3e92d112129507debe45364891954db70238997a`
+only in sunnypilot's additional `CP_SP`/`CC_SP` interface arguments. This change
+restores that implementation; it does not upgrade unrelated upstream code.
+
+Toggle-on retains the previous custom 100 Hz sender, mode 2, ramp type 3 and
+existing path limits. The model-action controller's command law and diagnostic
+identity `model-action-c1-feedback-v3` are unchanged. Legacy Ford always uses
+upstream control. The opendbc dependency is now
+`64aa61b9b3fd26e70a7caa915acab207ff3cd64a`. No Panda safety code is changed;
+its existing limited-mode checks already use 20 Hz curvature limits.
+
+## Validation
+
+- Combined Ford, Sunnylink, parameter, logging, replay-tool and Ford safety
+  suite: **683 passed, 178 existing skips, 9,145 subtests passed**.
+- Real startup → controlsd → Float32 publication → conversion → Ford sender:
+  14 new toggle-off cases, covering all six CAN FD platforms plus legacy
+  Escape, with both stored observer settings. They preserve the upstream
+  actuator output, including when custom model geometry is missing, and verify
+  20 Hz cadence, engage/disengage/reengage, zero path terms, mode, ramp,
+  counters and checksums across 4,200 control cycles / 840 steering messages.
+- The existing toggle-on, stale-input, invalid-input and 100 Hz integration
+  regressions continue to pass.
+- Additional Ford interface fuzz checks: **11 passed**, 60 generated examples
+  each, with real Cap'n Proto conversion and car-interface application. The
+  initially missing neural-network-data dependency was initialized at the
+  repository's existing pin `03cac2d30e111e0689c0429cb8c1fe6cb5a905af`.
+- Packet equivalence: **55,000 toggle-off cycles across all 11 Ford platforms**
+  match the pinned upstream sender exactly. **30,000 toggle-on cycles across
+  six CAN FD platforms** match the previous custom sender exactly. All 90,305
+  outgoing packets and returned actuator values match, including invalid paths,
+  inactive periods, both turn directions and speed boundaries. Disabled
+  selection also ignores deliberately nonzero, valid custom path fields.
+- Ruff, controller type check, generated Sunnylink schema check and diff
+  whitespace checks pass.
+
+The packet comparison loads the exact old controller **and its old CAN builder**
+from trusted local Git sources. It does not compare two aliases of the modified
+code. Results and source hashes are in `ford_upstream_fallback_validation.json`.
+No device build, boot or physical steering validation is claimed.
+
+## Reproduction
+
+Use the pinned opendbc dependency and native project dependencies:
+
+```sh
+export PYTHONDONTWRITEBYTECODE=1
+export PYTHONPATH=.:opendbc_repo
+python -m pytest -q -p no:cacheprovider openpilot/selfdrive/controls/tests/test_ford_*.py tools/ford_pscm_lab openpilot/selfdrive/car/tests/test_ford_pscm_status.py openpilot/sunnypilot/sunnylink/tests openpilot/common/tests/test_params.py opendbc_repo/opendbc/car/ford/tests/test_ford.py opendbc_repo/opendbc/safety/tests/test_ford.py
+FUZZ_SEED=20260911 python -m pytest -q -p no:cacheprovider openpilot/selfdrive/car/tests/test_car_interfaces.py -k FORD
+python -m tools.ford_pscm_lab.upstream_fallback_check --cycles 5000 --output .cache/ford_upstream_fallback/equivalence.json
+python openpilot/sunnypilot/sunnylink/tools/compile_settings_ui.py --check
+```
+
+The comparison requires both pinned baseline commits in the local opendbc Git
+object store. The previous overflow/replay records describe their historical
+source hashes; the comparison here establishes unchanged toggle-on sender output.

docs/ford_upstream_fallback_validation.json

@@ -0,0 +1,190 @@
+{
+  "created_at_utc": "2026-09-11T16:11:23.341760+00:00",
+  "scope": "Default-off upstream Ford control, including CAN sender; exact software comparison only.",
+  "parent_commit": "b81c00f5b9c3658d72675ec3ee0ac07e0ef14807",
+  "opendbc_commit": "64aa61b9b3fd26e70a7caa915acab207ff3cd64a",
+  "target": {
+    "repository": "sunnypilot/sunnypilot",
+    "branch": "hiimisaac-dev"
+  },
+  "selection": {
+    "param": "FordModelActionController",
+    "default": false,
+    "off": "upstream",
+    "on": "Ford CAN FD model-action v3",
+    "activation": "Existing controlsd startup; real offroad-to-onroad cycle",
+    "observer_setting": "Ignored for control selection; no longer exposed in Sunnylink",
+    "sender_field": "fordLateralPath.enabled defaults false, independent of valid"
+  },
+  "custom_command_law_ast_matches_parent": [
+    "_packed",
+    "_finite",
+    "encode_model_action",
+    "ModelActionController",
+    "FordModelActionController"
+  ],
+  "tests": {
+    "combined": "683 passed, 178 skipped, 9145 subtests passed in 9.61s",
+    "additional_ford_interface_fuzz": "11 passed, 258 non-Ford deselected in 8.15s; 60 examples per Ford platform",
+    "fuzz_seed": 20260911,
+    "dependency_setup": "Initialized existing neural-network-data pin 03cac2d30e111e0689c0429cb8c1fe6cb5a905af after missing-model-data failure.",
+    "new_toggle_off_integration_cases": 14,
+    "new_integration_cycles": 4200,
+    "new_steering_frames": 840,
+    "ruff_changed_python": "pass",
+    "ty_controller": "pass",
+    "settings_compiler_check": "pass",
+    "diff_check": "pass"
+  },
+  "packet_equivalence": {
+    "scope": "Compare all outgoing Ford packets with pinned upstream and custom senders.\n\nUses trusted local Git sources, identical synthetic inputs, and the actual CAN\npackers. Establishes software equivalence, not physical steering performance.\n",
+    "seed": 20260911,
+    "upstream_revision": "f95f996f5917dcbbf2e32fe51b606a24cf836af6",
+    "previous_custom_revision": "c21a9013700734dd20b09e05aa68329ad8cc20f9",
+    "upstream_source_sha256": {
+      "opendbc/car/ford/fordcan.py": "8b3c74bff68146cf9f97d17203b7deebb9254561d9591a4a92d978bf01808a75",
+      "opendbc/car/ford/carcontroller.py": "c7e590c13cfe2434d77d6224359d659bb5092a3fdd65b12c7d8d9eddfb3deada"
+    },
+    "previous_custom_source_sha256": {
+      "opendbc/car/ford/fordcan.py": "5b73c568149bde299f71f92f034f3032a94ecae4ee4bae8af938f34ef9590062",
+      "opendbc/car/ford/carcontroller.py": "b2d327a1833fb1f0d09ee17f54c9c8d45517fa29beb04a4543cfbf1b43f1a65e"
+    },
+    "results": [
+      {
+        "fingerprint": "FORD_BRONCO_SPORT_MK1",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 5665
+      },
+      {
+        "fingerprint": "FORD_ESCAPE_MK4",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 5665
+      },
+      {
+        "fingerprint": "FORD_ESCAPE_MK4_5",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_ESCAPE_MK4_5",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      },
+      {
+        "fingerprint": "FORD_EXPLORER_MK6",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 5665
+      },
+      {
+        "fingerprint": "FORD_EXPEDITION_MK4",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_EXPEDITION_MK4",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      },
+      {
+        "fingerprint": "FORD_F_150_MK14",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_F_150_MK14",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      },
+      {
+        "fingerprint": "FORD_F_150_LIGHTNING_MK1",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_F_150_LIGHTNING_MK1",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      },
+      {
+        "fingerprint": "FORD_FOCUS_MK4",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 5665
+      },
+      {
+        "fingerprint": "FORD_MAVERICK_MK1",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 5665
+      },
+      {
+        "fingerprint": "FORD_MUSTANG_MACH_E_MK1",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_MUSTANG_MACH_E_MK1",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      },
+      {
+        "fingerprint": "FORD_RANGER_MK2",
+        "custom_enabled": false,
+        "cycles": 5000,
+        "identical_packets": 3165
+      },
+      {
+        "fingerprint": "FORD_RANGER_MK2",
+        "custom_enabled": true,
+        "cycles": 5000,
+        "identical_packets": 7165
+      }
+    ],
+    "total_cycles": 85000,
+    "total_identical_packets": 90305,
+    "candidate_source_sha256": {
+      "opendbc/car/ford/carcontroller.py": "6d33f288de87e3baa69e9161b1b85367dc1d8542c06c3d3a9ce2d1f2347dbd30",
+      "opendbc/car/ford/fordcan.py": "0e241f19f152df897b294d4562bfd729dbfcbc56bcc9770379f76922f2864cb8",
+      "opendbc/car/structs.py": "82ecc4de1e5fda486d68fcf67903098dd083a56b78e65866744f42d5fb97b385"
+    },
+    "checker_sha256": "1d33a07cc5e6188c6d1b5de2a2a603efaee691d25d91b7bcd843ab4909753ae1"
+  },
+  "source_sha256": {
+    "openpilot/selfdrive/controls/lib/ford_model_action.py": "167ae5a01fdd7ea014e6ad3fe9d0b6e31c67de8ba057ec5ecf18ab38fc16353f",
+    "openpilot/selfdrive/controls/controlsd.py": "c9b68431d212178ae2177b16ddba4cf023ece84c7c0ea8a1db02a2527dc27aba",
+    "openpilot/cereal/custom.capnp": "c877eac4a77ea4cb42447edcf38da4baf20708e8993124852234008e0a084664",
+    "openpilot/sunnypilot/selfdrive/controls/controlsd_ext.py": "45bfaafa9a96d3ccbb56f34ec0b9a71abb7cd7f01e7e80620796d13c222e4720",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_selection.py": "3dc4f7236937358aad09b544577a796e47c15dbc96607739ff0874b900d55089",
+    "openpilot/selfdrive/controls/tests/test_ford_model_action_adapter.py": "073b16ffa611d654b954711f9e4f24df95477dfc0c09e75eff89d02eb29d7f2a",
+    "openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py": "5b082f3c1f6dc596a40a2011c71928debeb04fa70af36841f6f9a237a9ca439e",
+    "openpilot/sunnypilot/sunnylink/settings_ui_src/pages/vehicle.yaml": "e37a662618b6ccd2620ac355b4cc40a2253707bb4ba1d5d4631fdc89fd01a800",
+    "openpilot/sunnypilot/sunnylink/settings_ui.json": "36ac7f6177de2679d35c5f7f77234336e17a8632d31b195f40aec6014efb8577",
+    "openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py": "53a3f1f807c638661c8ef60b5dc5c28ecf5604a9d35b610b8e4a5f5d1d99eedb",
+    "tools/ford_pscm_lab/feedback_replay.py": "860aff9fd00d26b2bd7c2b627286918d3b52c25cc31b0b0768a51fc55b0df37e"
+  },
+  "validation_environment": {
+    "python": "/Users/ibpersonal/dev/sunnypilot/.venv/bin/python",
+    "PYTHONPATH": ".:opendbc_repo:.cache/ford_v6/test_deps",
+    "PYTHONDONTWRITEBYTECODE": "1",
+    "LOG_ROOT": "/private/tmp/ford-upstream-logs",
+    "PARAMS_ROOT": "/private/tmp/ford-upstream-params"
+  },
+  "panda_safety_changed": false,
+  "limitations": [
+    "No full device build, boot, installation or physical steering validation.",
+    "Upstream means the pinned upstream implementation merged into this branch, not an upgrade to unrelated latest source."
+  ]
+}

docs/ford_virtual_angle_experiment.md

@@ -0,0 +1,327 @@
+# Ford C2-free model-pose tracking with measured feedback
+
+This experiment is retired. Its implementation, setting and dedicated tests
+were removed from the selected-action drive-test branch. For current setup,
+see [Ford selected-action drive testing](ford_model_action_drive_test.md).
+The material below is historical; it does not describe an available toggle.
+
+Hypothesis `model-pose-c0-c1-feedback-v8` retains the model-pose C0/C1 base
+and adds two guarded release policies. When measured turning exceeds both
+current and delayed requests, a separate output guard prevents same-direction
+C0/C1 growth, including while feedback history rebuilds after driver input.
+When turning instead falls below both requests and is no longer increasing,
+bounded C1 tracking can use remaining release-entry command headroom.
+Existing opposing-bias recovery still stops at zero bias. Geometry, blending,
+feedback gain, slew rates and field limits are unchanged; C2/C3 remain zero.
+
+This is an experimental outer controller around the multivariable PSCM.
+Its geometry does not define a calibrated C0/C1-to-wheel mapping or an angle
+servo. V8 has offline validation only. Command replay cannot establish the
+truck's response, closed-loop stability, or an overshoot improvement.
+
+## Evidence and scope
+
+Route80 ran v3 and contains both sustained under-response and over-response.
+Representative eligible windows had median CAN response/request ratios of
+0.78, 1.77 and 0.69 with a declared 0.2-second comparison interval. These
+are descriptive tracking ratios, not identified controller gains.
+
+V4 replaced separate model-heading C1 with selected-curvature C1 and reduced
+heading demand in several large maneuvers. The user subsequently reported
+weak turning and steering repeatedly stopping near 85 degrees. Older logs
+contain larger wheel angles; the inspected host code has no fixed 85-degree
+wheel stop, although upstream curvature limits depend on speed.
+
+Route83 had the Sunnylink toggle on, but omitted EPS firmware responses.
+The former firmware gate selected the default `FordPathController`; replay
+reproduced its recorded C0/C1/C2 requests. Its favorable turns are evidence
+for the existing model-pose construction, not validation of v5 or v6.
+V6 reuses that construction while replacing its remaining C2 request with
+C0/C1 geometry. Removing C2 changes the request received by the PSCM, so
+matching large C0/C1 commands does not guarantee matching vehicle motion.
+
+Route8a ran v6 and was reported as the best drive. Route8e ran v7 throughout
+with the experiment enabled; it includes entry lag and excessive turning
+while requests release. Fixed-input v6/v7 replay produced identical commands
+in the main reversal and over-response examples, so the v7 recovery change
+does not directly explain their command behavior. In the over-response
+example, model C0/C1 grew while selected curvature fell and driver resets
+repeatedly removed feedback history. Another exit remained deficient after
+opposing bias reached zero. These observations motivate the v8 guards; they
+do not isolate an EPS transfer function or demonstrate the proposed response.
+
+## Base request
+
+controlsd selects valid `lateralManeuverPlan.desiredCurvature`, otherwise
+`modelV2.action.desiredCurvature`, after the existing curvature limiter.
+This action already includes upstream delay handling; it receives no extra
+response advance here.
+
+The model contribution uses the existing allocator's raw forward pose and
+bounded short-pose correction. `_model_pose` advances 0.1 seconds, retains
+the model's remaining forward geometry, and separately corrects the short
+pose using measured curvature and its recent change. Its offset preview is
+up to 7 m and its heading preview is up to max(7 m, speed × 1 s), bounded by
+available path length. This raw pose is not passed through a second model
+filter. The filtered, ego-aligned reference remains available for comparison
+and the existing geometry-validity checks.
+
+```text
+share(k) = clip((k - 0.006/m) / (0.012/m - 0.006/m), 0, 1)
+aligned = desired_curvature × model_forward_heading > 0
+model_share = min(share(abs(desired_curvature)), share(model_curvature_demand))
+              if aligned, otherwise 0
+model_pair = existing_pose_encoder(model_pose, model_share, C2=0)
+
+remaining_curvature = desired_curvature × (1 - model_share)
+L0 = max(8 m, speed × 1 s)
+L1 = max(7 m, speed × 1 s)
+curvature_C0 = 0.5 × remaining_curvature × L0²
+curvature_C1 = remaining_curvature × L1
+C0_base = clip(model_pair.C0 + curvature_C0, ±5.11 m)
+C1_base = clip(model_pair.C1 + curvature_C1, ±0.5 rad)
+```
+
+`model_curvature_demand` is the larger absolute curvature implied by the
+forward offset and heading previews. The share uses the existing allocator's
+0.006–0.012/m thresholds. Both model and action must request a substantial
+turn in the same direction before model pose supplies the full base.
+Small, flat, opposed or zero requests use the curvature contribution; zero
+action produces a zero base. Partial shares combine both contributions.
+The existing pose encoder retains its quantization and field-allocation rules.
+The residual-curvature lift is geometric, not a claim of EPS equivalence to C2.
+
+The inherited pose encoder allocates heading overflow using its asymmetric
+limits (+0.5235/−0.5 rad), before the symmetric final ±0.5 rad
+heading bound. On clipped tails, this can leave mirrored C0 requests differing
+by up to 0.0235 rad × 7 m = 0.1645 m. The favorable comparison anchors lie
+below that heading cap; full model-base odd symmetry is not claimed.
+
+## Measured feedback and limits
+
+```text
+past_request = selected curvature held at or before (measurement_time - delay)
+yaw_error = measured_speed × past_request - measured_yaw_rate
+bias_trial = released_bias + feedback_gain × yaw_error × measurement_dt
+C1_unconstrained = clip(C1_base + accepted_bias, ±0.5 rad)
+C1_target = temporary_backoff_ceiling(C1_unconstrained) if backoff_active
+            otherwise C1_unconstrained
+```
+
+Measured yaw is negated Ford CAN yaw, matching the control sign convention.
+The historical request uses zero-order hold; it never interpolates toward a
+future publication. Nominal comparison delay is `CP.steerActuatorDelay`
+(0.2 seconds on the source vehicle). Feedback compares against selected
+curvature, not curvature inferred from the model-pose coefficients.
+
+| Quantity | Value |
+|---|---:|
+| C0 / C1 final bounds | ±5.11 m / ±0.5 rad |
+| Independent C0 / C1 slew | 4 m/s / 0.5 rad/s |
+| Feedback integration scale | 1.0 |
+| Feedback minimum speed | 2 m/s |
+| Maximum PSCM/core input age | 150 ms |
+| Allowed timestamp lead | 5 ms |
+| Release comparison tolerance | one C1 wire quantum, 0.0005 rad |
+
+The integration scale, preview distances and blend thresholds are effective
+gains; none establishes stability. No wheel-response gain is fitted.
+Zero yaw error retains acquired bias while an eligible turn continues.
+Host anti-windup admits reachable correction within the combined C1 field
+and slew limits. Feedback overflow is not transferred into C0.
+
+The release logic scales bias as the bounded base decreases and resets on
+zero/reversal. When delayed curvature still represents a stronger or opposing
+request, or PSCM reports LimitReached, new integration is normally frozen.
+One exception permits measured-error backoff: measured turning must exceed
+both the delayed and current selected yaw requests in the base's direction,
+and total heading must still have the base's sign. Exceeding only an older,
+smaller request during turn-in does not qualify. The accepted increment may
+only reduce that existing total toward zero; it cannot grow the request or
+carry it through zero. Existing host field and slew limits still apply.
+
+The existing release-recovery exception requires fresh valid PSCM status with
+limit below 2, retained bias opposing the base, and both current and delayed
+requests aligned with that base. Measured turning must be below both requests
+in their direction. It then uses the current yaw deficit × the existing
+feedback gain × measurement interval to unwind only the opposing bias toward
+zero. The increment is clipped so recovery cannot cross zero bias or create
+demand beyond the existing base. Common host anti-windup still limits what
+can be accepted. A separate release-tracking exception is described below;
+other constrained cases remain frozen. PSCM limit 2 never permits either
+request-increasing exception.
+The no-new-bias restriction applies to `release_recovery`. It does not apply
+to the separate bounded `release_tracking` branch. Once release ends,
+ordinary eligible integration can add correction beyond the base as before;
+its existing limits and guards are unchanged.
+
+`release_recovery` and `feedback_recovery_active=true` indicate that the
+recovery branch actually changed bias on that update. If host anti-windup
+blocks the entire increment, the status remains `host_limit` and the flag is
+false. Recovery is evaluated only on fresh measurements; the flag is false
+on repeated-measurement updates and after reset.
+
+Diagnostics distinguish `release_backoff` and `pscm_backoff`; a release takes
+precedence when both conditions apply. While `feedback_backoff_active` is
+true, total C1 is also capped at the preceding continuous heading request in
+the current request direction and at zero in the opposite direction. This
+ceiling affects the output only: it is not stored or projected into bias.
+The measured-error increment can still update bias under the normal limits,
+but a changing model base does not create persistent integral suppression.
+The ceiling persists between repeated measurements; C1 cannot grow or reverse
+while it applies. The next fresh measurement clears it unless backoff is
+again warranted. It does not cap C0, and normal feedback has its own rules
+outside backoff. Independent slew remains 0.5 rad/s for C1 and 4 m/s for C0.
+Backoff still compares against the delayed reference, so response lag remains.
+Reducing a request does not demonstrate that physical overshoot is resolved.
+
+## V8 release guard and tracking
+
+`ReleaseGuard` retains selected-request history independently of feedback
+bias history. Driver-related feedback resets do not erase that reference,
+but the guard still requires current fresh valid PSCM status, no current
+driver override, and the existing input and speed eligibility. Invalid core
+input or disengagement resets its history with the controller.
+
+During release, measured yaw must exceed both the current and delay-matched
+requests in the requested turn direction. Only then does the guard cap
+same-direction C0/C1 growth at each preceding continuous request. Terms
+already reducing the turn, including an opposing C0 centering offset, remain
+available. The guard follows base allocation and C1 feedback, so changing
+model geometry cannot bypass it. Its ceilings affect outputs, never stored
+bias. No scalar-curvature cap replaces strong model geometry during turn-in
+or undertracking. Existing independent slew and field limits still apply.
+
+`release_tracking` addresses an eligible release deficit once bias is zero
+or already in the base's direction. Both current and delayed requests must
+align with that base, measured turning must be below both, and measured
+curvature must not be rising in the turn direction across the response
+interval by more than one C1 wire quantum after scaling by heading preview.
+Fresh valid PSCM status with limit below 2 is required. The current yaw deficit
+uses the existing integration gain and measurement interval;
+new C1 tracking increments are limited by command headroom captured at
+release entry, tapered with remaining desired curvature. The allowance is
+`max(0, entry_command_magnitude - abs(base)) × min(1, abs(desired) / entry_reference)`
+above the current base; any existing same-direction bias consumes it first.
+This limits new tracking integration, not the existing model base or bias.
+Only that additional allowance is tapered; strong model geometry remains
+available. A brief pause does not reacquire a higher entry
+ceiling; a full response interval without release ends the retained episode.
+Common host anti-windup, field and slew bounds still apply. Opposing bias
+continues through `release_recovery`, which stops at zero, before any separate
+tracking exception can be considered.
+
+Neither exception relaxes the PSCM LimitReached growth restriction. The
+reference delay and finite response time remain; these output policies are
+command-construction changes, not evidence of improved physical tracking.
+
+## PSCM status and driver handling
+
+card publishes `Lane_Assist_Data3_FD1` in `carStateSP.fordPscmStatus`, retaining
+the original CAN receipt timestamp. Republishing carStateSP or receiving
+unrelated frames cannot refresh it. The opendbc submodule is unchanged.
+
+Feedback requires valid fresh status, InProgress lateral state (2), capability
+LimitedModeAvailable or ExtendedModeAvailable (1 or 2), and no denial.
+Missing, malformed, stale, backward-timestamped, denied or unavailable status
+clears feedback bias/history and disables the separate release guard,
+leaving the base subject to its core validity gates.
+LimitReached (2) permits only the bounded request-reducing backoff described
+above and otherwise freezes integration. LimitWithDriverActive (3) clears
+feedback. Backoff still requires fresh, valid, InProgress status with an
+available capability and no denial. These generic PSCM reports do not identify
+a specific torque or rate limit.
+
+`steeringPressed`, raw torque above the existing Ford driver allowance, or
+nonfinite torque clear feedback. Below 2 m/s feedback also clears. A fresh
+feedback reference interval is required after override; the independent
+release guard can use retained valid request history once its current gates
+are satisfied. Base requests retain normal
+PSCM driver arbitration while lateral control remains authorized; an unset
+override flag cannot rule out subthreshold driver influence.
+
+## Gates and Sunnylink selection
+
+Core model/action/car-state freshness, finite-value, clock and speed checks
+remain in place. Invalid core inputs reset both commands and clear latActive.
+Raw model geometry is validated on every update, including repeated model
+timestamps; an invalid raw path cannot reuse the cached valid reference.
+Missing PSCM status disables feedback, not an otherwise valid base request.
+
+Vehicle → Ford → **C2-Free Path Tracking (Experimental)** retains the
+`FordVirtualAngleController` key, default-off setting and offroad/onroad cycle
+requirement. Enabled selects v8 on Ford CAN FD `FORD_F_150_LIGHTNING_MK1`
+regardless of missing or different EPS firmware-query results. Other platforms
+retain their existing controller. V8 takes priority over PSCM Coefficient
+Observer while selected; disabling and cycling offroad/onroad restores the
+previous selection. Controller selection does not force lateral engagement.
+
+The analyzed firmware is `RL38-14D003-AA`; removing the eligibility check
+is not validation of other firmware. No live device setting is changed.
+
+## Diagnostics and verification
+
+The 5 Hz `Ford C2-free path tracking` event keeps its name and identifies v8.
+`model_offset_base` / `model_heading_base` report the already weighted and
+encoded model contribution; `curvature_offset_base` / `curvature_heading_base`
+report the residual-curvature contribution. `model_share` and `base_guard`
+identify model-pose, blended, curvature-only, opposed-model and zero-request
+cases. `heading_base` is the bounded pre-feedback C1. `offset_target` and
+`heading_target` are the final targets after the independent release guard;
+`offset_target_unguarded` and `heading_target_unguarded` retain the inputs to
+that guard. The latter C1 already includes its normal feedback/backoff policy.
+
+The event retains source timestamps, measured curvature/yaw, final commands,
+slew scales, feedback bias/status/history, raw torque and PSCM status/age.
+`feedback_backoff_active` records the persistent heading ceiling, including
+cycles whose feedback status is `no_new_measurement`.
+`release_guard_active` and `release_guard_reference_curvature` expose the
+independent C0/C1 guard and its retained delayed reference.
+`feedback_release_tracking_active`, `feedback_release_ceiling` and
+`feedback_curvature_delta` identify accepted release
+tracking, the total-heading threshold used to admit new bias, and the
+measured-curvature change across the response interval (1/m). The tracking
+flag is true only when the branch accepts a bias change on a new measurement;
+it is false on repeated measurements. The ceiling/trend fields can describe
+an evaluated condition even when no increment is accepted.
+`feedback_recovery_active` records an accepted recovery increment on this
+update only; it does not persist between measurements.
+`feedback_yaw_error` retains its delayed-reference meaning. Recovery instead
+uses current error, reconstructed from logged `desired_curvature`,
+synchronized car-state speed and `yaw_rate`; those two errors can differ.
+During backoff or the independent release guard, `heading_target` can be lower in the request direction than
+the bounded sum of `heading_base` and `heading_bias`, because the temporary
+ceiling is not part of the stored bias.
+`model_heading_target` remains a filtered comparison reference; it is not the
+weighted model contribution. `angleState.saturated` is not an EPS-limit signal.
+
+Validation must cover large recorded maneuvers, flat-model centering, both
+turn directions, model/action disagreement, share transitions, release and
+reversal, release/limit backoff without growth or zero crossing, status/driver
+resets, reference causality, bounds, slew and CAN packing with C2/C3 zero.
+Recovery checks cover both directions, stopping at zero bias, repeated
+measurements, current-and-delayed agreement, and rejection at PSCM limit 2.
+Old v3/v4 command-equality expectations do not define
+v8 success. Guard checks also cover driver reset/history rebuilding,
+same-direction growth, opposing coefficients, repeated measurements,
+undertracking and invalid-status inhibition. Tracking checks cover delayed
+curvature trends and tapered release-entry headroom. Historical v5–v7 replay
+results remain historical observations.
+
+The v8 recorded-input fixture contains 15,273 cycles with 4,879 selected
+evidence samples. Base allocation and output eligibility match v7. In the
+clean deficient exit, median absolute C1 changes from 0.0665 to 0.0845 rad
+while C0 stays unchanged. The growth guard also acts while feedback history
+rebuilds; the largest over-growth witness includes nearby driver input and
+is excluded from the strict autonomous tracking score. Both good comparison
+curves in that fixture retain their median requests, and the older large-turn
+fixtures retain their required command scale.
+
+On the earlier good drive, one comparison curve retains extra C1 after
+eligible release tracking: median magnitude changes from 0.121 to 0.128 rad.
+In its 103–110 s interval, tracking increments occur only while measured
+turning falls short, with a median current response/request ratio of 0.895.
+Acquired bias can persist after matching, as with ordinary integral feedback.
+This collateral command change remains a reason to compare new vehicle logs.
+Replay fixes recorded motion and planner outputs, so enabled vehicle logs
+are still required to assess tracking error, oscillation and interventions.

openpilot/cereal/custom.capnp

@@ -383,6 +383,7 @@ struct CarControlSP @0xa5cd762cd951a455 {
   leadOne @2 :LeadData;
   leadTwo @3 :LeadData;
   intelligentCruiseButtonManagement @4 :IntelligentCruiseButtonManagement;
+  fordLateralPath @5 :FordLateralPath;
 
   struct Param {
     key @0 :Text;
@@ -403,6 +404,15 @@ struct CarControlSP @0xa5cd762cd951a455 {
   }
 }
 
+struct FordLateralPath {
+  pathOffset @0 :Float32;     # c0 [m]
+  pathAngle @1 :Float32;      # c1 [rad]
+  curvature @2 :Float32;      # c2 [1/m]
+  curvatureRate @3 :Float32;  # c3 [1/m^2]
+  valid @4 :Bool;
+  enabled @5 :Bool;          # Startup-selected custom controller; independent of command validity.
+}
+
 struct BackupManagerSP @0xf98d843bfd7004a3 {
   backupStatus @0 :Status;
   restoreStatus @1 :Status;
@@ -447,6 +457,16 @@ struct BackupManagerSP @0xf98d843bfd7004a3 {
 
 struct CarStateSP @0xb86e6369214c01c8 {
   speedLimit @0 :Float32;
+  fordPscmStatus @1 :FordPscmStatus;
+
+  struct FordPscmStatus {
+    valid @0 :Bool;
+    canMonoTime @1 :UInt64;  # Last accepted Lane_Assist_Data3_FD1 CAN receipt, not carStateSP publication time.
+    lateralState @2 :UInt8;  # LatCtlSte_D_Stat
+    limit @3 :UInt8;  # LatCtlLim_D_Stat: generic lateral limit, not a torque/rate diagnosis.
+    capability @4 :UInt8;  # LatCtlCpblty_D_Stat
+    denied @5 :Bool;  # LaActDeny_B_Actl
+  }
 }
 
 struct LiveMapDataSP @0xf416ec09499d9d19 {
@@ -470,7 +490,30 @@ struct ModelDataV2SP @0xa1680744031fdb2d {
   }
 }
 
-struct CustomReserved10 @0xcb9fd56c7057593a {
+struct AssistedDrivingMilestoneState @0xcb9fd56c7057593a {
+  enabled @0 :Bool;
+  madsDistanceMeters @1 :Float64;
+  fullAssistDistanceMeters @2 :Float64;
+  event @3 :Event;
+
+  struct Event {
+    id @0 :UInt64;
+    category @1 :Category;
+    distanceMeters @2 :Float64;
+    previousDistanceMeters @3 :Float64;
+    unit @4 :Unit;
+  }
+
+  enum Category {
+    none @0;
+    mads @1;
+    fullAssist @2;
+  }
+
+  enum Unit {
+    imperial @0;
+    metric @1;
+  }
 }
 
 struct CustomReserved11 @0xc2243c65e0340384 {

openpilot/cereal/log.capnp

@@ -2642,7 +2642,7 @@ struct Event {
     carStateSP @114 :Custom.CarStateSP;
     liveMapDataSP @115 :Custom.LiveMapDataSP;
     modelDataV2SP @116 :Custom.ModelDataV2SP;
-    customReserved10 @136 :Custom.CustomReserved10;
+    assistedDrivingMilestoneState @136 :Custom.AssistedDrivingMilestoneState;
     customReserved11 @137 :Custom.CustomReserved11;
     customReserved12 @138 :Custom.CustomReserved12;
     customReserved13 @139 :Custom.CustomReserved13;

openpilot/cereal/services.py

@@ -90,6 +90,7 @@ _services: dict[str, tuple] = {
   "carParamsSP": (True, 0.02, 1),
   "carControlSP": (True, 100., 10),
   "carStateSP": (True, 100., 10),
+  "assistedDrivingMilestoneState": (True, 10., 1),
   "liveMapDataSP": (True, 1., 1),
   "modelDataV2SP": (True, 20., None, QueueSize.BIG),
   "liveLocationKalman": (True, 20.),

openpilot/common/params.cc

@@ -97,6 +97,10 @@ Params::Params(const std::string &path) {
 }
 
 Params::~Params() {
+  flushNonBlockingWrites();
+}
+
+void Params::flushNonBlockingWrites() {
   if (future.valid()) {
     future.wait();
   }

openpilot/common/params.h

@@ -75,6 +75,7 @@ public:
     return put(key.c_str(), val ? "1" : "0", 1);
   }
   void putNonBlocking(const std::string &key, const std::string &val);
+  void flushNonBlockingWrites();
   inline void putBoolNonBlocking(const std::string &key, bool val) {
     putNonBlocking(key, val ? "1" : "0");
   }

openpilot/common/params.py

@@ -73,6 +73,7 @@ params_get = _bind("params_get", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool],
 params_get_bool = _bind("params_get_bool", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool], ctypes.c_bool)
 params_put = _bind("params_put", [ParamsHandle, ctypes.c_char_p, ctypes.c_char_p, ctypes.c_size_t, ctypes.c_bool], ctypes.c_int)
 params_put_bool = _bind("params_put_bool", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool, ctypes.c_bool], ctypes.c_int)
+params_flush = _bind("params_flush", [ParamsHandle])
 params_remove = _bind("params_remove", [ParamsHandle, ctypes.c_char_p], ctypes.c_int)
 params_get_path = _bind("params_get_path", [ParamsHandle, ctypes.c_char_p, ctypes.c_size_t], ParamsBuffer)
 params_keys_size = _bind("params_keys_size", [ParamsHandle], ctypes.c_size_t)
@@ -178,6 +179,10 @@ class Params:
   def put_bool(self, key, val, block=False):
     params_put_bool(self.p, self.check_key(key), val, block)
 
+  def flush(self):
+    """Wait for all prior nonblocking writes from this Params instance."""
+    params_flush(self.p)
+
   def remove(self, key):
     params_remove(self.p, self.check_key(key))
 

openpilot/common/params_c.cc

@@ -133,6 +133,12 @@ int params_put_bool(ParamsHandle *handle, const char *key, bool value, bool bloc
   });
 }
 
+void params_flush(ParamsHandle *handle) noexcept {
+  translate_exceptions([&]() {
+    handle->params.flushNonBlockingWrites();
+  });
+}
+
 int params_remove(ParamsHandle *handle, const char *key) noexcept {
   return translate_exceptions(-1, [&]() {
     return handle->params.remove(key);
@@ -162,12 +168,15 @@ ParamsBuffer params_key_at(ParamsHandle *handle, size_t index) noexcept {
 
 size_t params_keys_by_flag(ParamsHandle *handle, uint32_t flag, ParamsBuffer *out, size_t out_size) noexcept {
   return translate_exceptions(size_t{0}, [&]() {
-    auto filtered = handle->params.allKeys(static_cast<ParamKeyFlag>(flag));
+    size_t count = 0;
-    size_t count = std::min(filtered.size(), out_size);
+    for (const auto &key : handle->keys) {
-    for (size_t i = 0; i < count; i++) {
+      if (flag == ALL || (handle->params.getKeyFlag(key) & flag)) {
-      out[i] = return_string(filtered[i]);
+        // Each buffer borrows a different string, stable for the handle's lifetime.
+        if (count < out_size) out[count] = {key.data(), key.size()};
+        ++count;
+      }
     }
-    return filtered.size();
+    return count;
   });
 }
 

openpilot/common/params_keys.h

@@ -143,6 +143,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
 
     // --- sunnypilot params --- //
     {"ApiCache_DriveStats", {PERSISTENT, JSON}},
+    {"AssistedDrivingMilestonesEnabled", {PERSISTENT | BACKUP, BOOL, "1"}},
+    {"AssistedDrivingMilestoneState", {PERSISTENT, JSON, "{}"}},
     {"AutoLaneChangeBsmDelay", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"AutoLaneChangeTimer", {PERSISTENT | BACKUP, INT, "0"}},
     {"BlinkerLateralReengageDelay", {PERSISTENT | BACKUP, INT, "0"}},  // seconds
@@ -163,6 +165,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DevUIInfo", {PERSISTENT | BACKUP, INT, "0"}},
     {"EnableCopyparty", {PERSISTENT | BACKUP, BOOL}},
     {"EnableGithubRunner", {PERSISTENT | BACKUP, BOOL}},
+    {"FullAssistDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
     {"GreenLightAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"GithubRunnerSufficientVoltage", {CLEAR_ON_MANAGER_START , BOOL}},
     {"HasAcceptedTermsSP", {PERSISTENT, STRING, "0"}},
@@ -172,7 +175,9 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"IsDevelopmentBranch", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsReleaseSpBranch", {CLEAR_ON_MANAGER_START, BOOL}},
     {"LastGPSPositionLLK", {PERSISTENT, STRING}},
+    {"LastDriveAssistedDrivingSummary", {PERSISTENT, JSON, "{}"}},
     {"LeadDepartAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"MadsDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
     {"MaxTimeOffroad", {PERSISTENT | BACKUP, INT, "1800"}},
     {"ModelRunnerTypeCache", {CLEAR_ON_ONROAD_TRANSITION, INT}},
     {"OffroadMode", {CLEAR_ON_MANAGER_START, BOOL}},
@@ -232,6 +237,8 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"BackupManager_RestoreVersion", {PERSISTENT, STRING}},
 
     // sunnypilot car specific params
+    {"FordPscmObserver", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"FordModelActionController", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"HyundaiLongitudinalTuning", {PERSISTENT | BACKUP, INT, "0"}},
     {"SubaruStopAndGo", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"SubaruStopAndGoManualParkingBrake", {PERSISTENT | BACKUP, BOOL, "0"}},

openpilot/common/tests/test_params.py

@@ -106,6 +106,13 @@ class TestParams(OpenpilotTestCase):
     assert q.get("CarParams") is None
     assert q.get("CarParams", True) == b"1"
 
+  def test_flush_non_blocking_writes(self):
+    self.params.put("DongleId", "first")
+    self.params.put("DongleId", "last")
+    self.params.flush()
+
+    assert self.params.get("DongleId") == "last"
+
   def test_params_all_keys(self):
     keys = Params().all_keys()
 
@@ -126,6 +133,16 @@ class TestParams(OpenpilotTestCase):
     assert self.params.get("LiveParametersV2") is None
     assert self.params.get("LiveParametersV2", return_default=True) is None
 
+  def test_filtered_keys_are_distinct_registered_strings(self):
+    registered = set(self.params.all_keys())
+    for flag in (ParamKeyFlag.PERSISTENT, ParamKeyFlag.BACKUP, ParamKeyFlag.CLEAR_ON_MANAGER_START):
+      filtered = self.params.all_keys(flag)
+      assert len(filtered) > 1
+      assert len(filtered) == len(set(filtered))
+      assert set(filtered) <= registered
+      assert all(key.decode('utf-8') for key in filtered)
+      assert self.params.all_keys(flag) == filtered
+
   def test_params_get_type(self):
     # json
     self.params.put("ApiCache_FirehoseStats", {"a": 0}, block=True)

openpilot/selfdrive/car/card.py

@@ -21,6 +21,7 @@ from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.helpers import convert_carControlSP, convert_to_capnp
+from openpilot.selfdrive.car.ford_pscm_status import populate_ford_pscm_status
 
 from openpilot.sunnypilot.mads.helpers import set_alternative_experience, set_car_specific_params
 from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
@@ -198,6 +199,7 @@ class Car:
     # Update carState from CAN
     CS, CS_SP = self.CI.update(can_list)
     CS_SP = convert_to_capnp(CS_SP)
+    populate_ford_pscm_status(self.CP, self.CI.can_parsers, CS_SP, CS.canValid)
 
     # Update radar tracks from CAN
     RD: structs.RadarDataT | None = self.RI.update(can_list)

openpilot/selfdrive/car/ford_pscm_status.py

@@ -0,0 +1,36 @@
+"""Publish the Ford PSCM's actual CAN status without changing opendbc structs."""
+import math
+
+from opendbc.car import Bus
+from opendbc.car.ford.values import FordFlags
+
+
+MESSAGE = 'Lane_Assist_Data3_FD1'
+SIGNALS = ('LatCtlSte_D_Stat', 'LatCtlLim_D_Stat', 'LatCtlCpblty_D_Stat', 'LaActDeny_B_Actl')
+
+
+def populate_ford_pscm_status(CP, can_parsers, CS_SP, can_valid):
+  if CP.brand != 'ford' or not CP.flags & FordFlags.CANFD:
+    return
+  status = CS_SP.init('fordPscmStatus')
+  parser = can_parsers.get(Bus.pt)
+  if parser is None:
+    return
+  values = parser.vl.get(MESSAGE, {})
+  timestamps = parser.ts_nanos.get(MESSAGE, {})
+  if any(signal not in values or signal not in timestamps for signal in SIGNALS):
+    return
+  received = timestamps[SIGNALS[0]]
+  if received <= 0 or any(timestamps[signal] != received for signal in SIGNALS):
+    return
+  decoded = [values[signal] for signal in SIGNALS]
+  if any(not math.isfinite(value) or int(value) != value or not 0 <= value <= maximum
+         for value, maximum in zip(decoded, (7, 3, 3, 1), strict=True)):
+    return
+  status.canMonoTime = received
+  status.lateralState, status.limit, status.capability = map(int, decoded[:3])
+  status.denied = bool(decoded[3])
+  # CI.update already checked all parser validity. Reading can_valid again here
+  # would advance the parser's invalid-message counter a second time per tick.
+  # Age is evaluated by the feedback consumer using this original CAN timestamp.
+  status.valid = bool(can_valid)

openpilot/selfdrive/car/helpers.py

@@ -63,5 +63,6 @@ def convert_carControlSP(struct: capnp.lib.capnp._DynamicStructReader) -> struct
   struct_dataclass.intelligentCruiseButtonManagement = structs.IntelligentCruiseButtonManagement(
     **remove_deprecated(struct_dict.get('intelligentCruiseButtonManagement', {}))
   )
+  struct_dataclass.fordLateralPath = structs.FordLateralPath(**remove_deprecated(struct_dict.get('fordLateralPath', {})))
 
   return struct_dataclass

openpilot/selfdrive/car/tests/test_ford_pscm_status.py

@@ -0,0 +1,109 @@
+import ast
+from pathlib import Path
+from types import SimpleNamespace
+import unittest
+
+from openpilot.cereal import custom
+from openpilot.selfdrive.car.ford_pscm_status import MESSAGE, SIGNALS, populate_ford_pscm_status
+from openpilot.selfdrive.car.helpers import convert_to_capnp
+from opendbc.can import CANPacker, CANParser
+from opendbc.car import Bus, structs
+from opendbc.car.ford.values import FordFlags
+
+
+class TestFordPscmStatus(unittest.TestCase):
+  def setUp(self):
+    self.cp = SimpleNamespace(brand='ford', flags=FordFlags.CANFD)
+    self.packer = CANPacker('ford_lincoln_base_pt')
+    self.parser = CANParser('ford_lincoln_base_pt', [(MESSAGE, 33), ('Yaw_Data_FD1', 100)], 0)
+
+  def update_status(self, timestamp, *, lateral_state=2, limit=0, capability=2, denied=False):
+    status = self.packer.make_can_msg(MESSAGE, 0, dict(zip(SIGNALS, (lateral_state, limit, capability, denied), strict=True)))
+    yaw = self.packer.make_can_msg('Yaw_Data_FD1', 0, {'VehYaw_W_Actl': 0.1})
+    self.parser.update([(timestamp, [status, yaw])])
+
+  def publish(self, *, can_valid=True):
+    state_sp = convert_to_capnp(structs.CarStateSP(speedLimit=13.5))
+    populate_ford_pscm_status(self.cp, {Bus.pt: self.parser}, state_sp, can_valid)
+    return state_sp
+
+  def test_decodes_status_and_preserves_receipt_time_across_other_can_messages(self):
+    self.update_status(1_000_000_000, limit=2, capability=1, denied=True)
+    original = self.publish()
+    self.assertEqual(original.speedLimit, 13.5)
+    status = original.fordPscmStatus
+    self.assertTrue(status.valid)
+    self.assertEqual(status.canMonoTime, 1_000_000_000)
+    self.assertEqual((status.lateralState, status.limit, status.capability, status.denied), (2, 2, 1, True))
+
+    # carStateSP may publish at 100 Hz while this 33 Hz message is absent. New
+    # unrelated CAN must not freshen the timestamp of an old PSCM status.
+    yaw = self.packer.make_can_msg('Yaw_Data_FD1', 0, {'VehYaw_W_Actl': .2})
+    self.parser.update([(1_080_000_000, [yaw])])
+    copied = self.publish().fordPscmStatus
+    self.assertEqual(copied.canMonoTime, 1_000_000_000)
+    self.assertEqual((copied.limit, copied.capability, copied.denied), (2, 1, True))
+
+    self.update_status(1_090_000_000, lateral_state=3, limit=3, capability=2)
+    next_state = self.publish()
+    with custom.CarStateSP.from_bytes(next_state.to_bytes()) as decoded:
+      latest = decoded.fordPscmStatus
+      self.assertTrue(latest.valid)
+      self.assertEqual(latest.canMonoTime, 1_090_000_000)
+      self.assertEqual((latest.lateralState, latest.limit, latest.capability, latest.denied), (3, 3, 2, False))
+
+  def test_absent_parser_unseen_message_and_invalid_can_do_not_claim_valid_status(self):
+    state = custom.CarStateSP.new_message()
+    populate_ford_pscm_status(self.cp, {}, state, True)
+    self.assertFalse(state.fordPscmStatus.valid)
+    self.assertEqual(state.fordPscmStatus.canMonoTime, 0)
+    self.assertFalse(self.publish().fordPscmStatus.valid)
+    self.update_status(1_000_000_000)
+    invalid = self.publish(can_valid=False).fordPscmStatus
+    self.assertFalse(invalid.valid)
+    self.assertEqual(invalid.canMonoTime, 1_000_000_000)
+
+  def test_mixed_timestamps_or_malformed_status_cannot_enable_feedback(self):
+    self.update_status(1_000_000_000)
+    self.parser.ts_nanos[MESSAGE][SIGNALS[-1]] = 990_000_000
+    self.assertFalse(self.publish().fordPscmStatus.valid)
+    self.parser.ts_nanos[MESSAGE][SIGNALS[-1]] = 1_000_000_000
+    for value in (float('nan'), -1, 1.5, 4):
+      self.parser.vl[MESSAGE]['LatCtlLim_D_Stat'] = value
+      self.assertFalse(self.publish().fordPscmStatus.valid)
+
+  def test_other_vehicles_and_legacy_messages_default_to_unavailable(self):
+    for cp in (SimpleNamespace(brand='toyota'), SimpleNamespace(brand='ford', flags=0)):
+      state = custom.CarStateSP.new_message(speedLimit=10.)
+      populate_ford_pscm_status(cp, {}, state, True)
+      self.assertFalse(state.fordPscmStatus.valid)
+      self.assertEqual(state.fordPscmStatus.canMonoTime, 0)
+      self.assertEqual(state.speedLimit, 10.)
+    # Old recordings/readers have no appended status pointer; defaults must
+    # remain unavailable rather than interpreting zeroed enums as fresh data.
+    self.assertFalse(custom.CarStateSP.new_message().fordPscmStatus.valid)
+
+  def test_actual_card_update_populates_status_after_dataclass_conversion(self):
+    self.update_status(1_000_000_000, limit=1)
+    source_path = Path(__file__).resolve().parents[1] / 'card.py'
+    source = ast.parse(source_path.read_text())
+    car_class = next(n for n in source.body if isinstance(n, ast.ClassDef) and n.name == 'Car')
+    method = next(n for n in car_class.body if isinstance(n, ast.FunctionDef) and n.name == 'state_update')
+    statements = method.body
+    first = next(i for i, n in enumerate(statements) if isinstance(n, ast.Assign) and ast.unparse(n.value) == 'self.CI.update(can_list)')
+    last = next(i for i, n in enumerate(statements) if isinstance(n, ast.Expr) and isinstance(n.value, ast.Call)
+                and isinstance(n.value.func, ast.Name) and n.value.func.id == 'populate_ford_pscm_status')
+    self.assertGreater(last, first)
+    code = compile(ast.Module(body=statements[first:last + 1], type_ignores=[]), str(source_path), 'exec')
+    ci = SimpleNamespace(update=lambda _: (SimpleNamespace(canValid=True), structs.CarStateSP(speedLimit=11.)),
+                         can_parsers={Bus.pt: self.parser})
+    environment = {'self': SimpleNamespace(CP=self.cp, CI=ci), 'can_list': [], 'convert_to_capnp': convert_to_capnp,
+                   'populate_ford_pscm_status': populate_ford_pscm_status}
+    exec(code, environment)
+    self.assertTrue(environment['CS_SP'].fordPscmStatus.valid)
+    self.assertEqual(environment['CS_SP'].fordPscmStatus.canMonoTime, 1_000_000_000)
+    self.assertEqual(environment['CS_SP'].fordPscmStatus.limit, 1)
+
+
+if __name__ == '__main__':
+  unittest.main()

openpilot/selfdrive/controls/controlsd.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 import math
+import time
 from numbers import Number
 
 from openpilot.cereal import log
@@ -13,6 +14,8 @@ from openpilot.common.swaglog import cloudlog
 from opendbc.car.car_helpers import interfaces
 from opendbc.car.vehicle_model import VehicleModel
 from openpilot.selfdrive.controls.lib.drive_helpers import clip_curvature
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController, select_model_action_controller
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl
 from openpilot.selfdrive.controls.lib.latcontrol_pid import LatControlPID
 from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle, STEER_ANGLE_SATURATION_THRESHOLD
@@ -44,7 +47,7 @@ class Controls(ControlsExt):
     self.CI = interfaces[self.CP.carFingerprint](self.CP, self.CP_SP)
 
     self.sm = messaging.SubMaster(['lateralDelay', 'vehicleParameters', 'lateralTorqueParameters', 'modelV2', 'selfdriveState',
-                                   'extrinsicsCalibration', 'deviceMotion', 'longitudinalPlan', 'lateralManeuverPlan', 'carState', 'carOutput',
+                                   'extrinsicsCalibration', 'deviceMotion', 'longitudinalPlan', 'lateralManeuverPlan', 'carState', 'carStateSP', 'carOutput',
                                    'driverMonitoringState', 'onroadEvents', 'driverAssistance'] + self.sm_services_ext,
                                   poll='selfdriveState')
     self.pm = messaging.PubMaster(['carControl', 'controlsState'] + self.pm_services_ext)
@@ -52,6 +55,12 @@ class Controls(ControlsExt):
     self.steer_limited_by_safety = False
     self.curvature = 0.0
     self.desired_curvature = 0.0
+    self.ford_path_controller = select_model_action_controller(self.CP, self.params.get_bool("FordModelActionController"))
+    self.ford_model_action = isinstance(self.ford_path_controller, FordModelActionController)
+    if self.CP.brand == "ford":
+      cloudlog.event("Ford path controller selected",
+                     controller=type(self.ford_path_controller).__name__ if self.ford_model_action else "upstream")
+    self.ford_path = FordPath()
 
     self.pose_calibrator = PoseCalibrator()
     self.calibrated_pose: Pose | None = None
@@ -155,6 +164,28 @@ class Controls(ControlsExt):
       actuators.curvature = float(lateral_output)
     else:
       actuators.steeringAngleDeg = float(lateral_output)
+    if self.CP.brand == "ford":
+      ford_model = model_v2 if self.sm.valid['modelV2'] else None
+      if self.ford_model_action:
+        reference_service = 'lateralManeuverPlan' if self.sm.valid['lateralManeuverPlan'] else 'modelV2'
+        self.ford_path = self.ford_path_controller.update(
+          ford_model, self.desired_curvature, current_curvature=self.curvature, yaw_rate=-CS.yawRate, speed=CS.vEgo, now=time.monotonic(),
+          measurement_time=self.sm.logMonoTime['carState'] * 1e-9,
+          model_time=self.sm.logMonoTime['modelV2'] * 1e-9,
+          reference_time=self.sm.logMonoTime[reference_service] * 1e-9,
+          active=CC.latActive, valid=CS.canValid and self.sm.all_checks(['carState', 'vehicleParameters', 'modelV2', reference_service]),
+          driver_pressed=CS.steeringPressed, driver_torque=CS.steeringTorque,
+          pscm_status=self.sm['carStateSP'].fordPscmStatus if self.sm.valid['carStateSP'] else None,
+        )
+        if not self.ford_path.valid:
+          CC.latActive = False
+        if self.sm.frame % 20 == 0:
+          cloudlog.event("Ford C2-free path tracking", model_mono_time=self.sm.logMonoTime['modelV2'],
+                         measurement_mono_time=self.sm.logMonoTime['carState'],
+                         reference_service=reference_service, reference_mono_time=self.sm.logMonoTime[reference_service],
+                         measured_curvature=self.curvature,
+                         **self.ford_path_controller.diagnostics)
+        actuators.curvature = float(self.ford_path.curvature)
     # Ensure no NaNs/Infs
     for p in ACTUATOR_FIELDS:
       attr = getattr(actuators, p)

openpilot/selfdrive/controls/lib/ford_model_action.py

@@ -0,0 +1,200 @@
+"""Experimental Ford C2-free controller with measured-curvature C1 feedback.
+
+Selected only by its explicit toggle. The 7 m station and one-second scale are
+engineering choices. Feeding integrated heading mismatch into C1 at 1:1 is an
+explicit feedback-strength choice, not an identified PSCM model or calibration.
+Opposed correction may be released when both path commands confirm the turn.
+Base heading clipped by C1 is allocated to C0 at the existing 7 m reference.
+"""
+import math
+import struct
+
+import numpy as np
+
+from opendbc.car.ford.values import CarControllerParams, FordFlags
+from openpilot.selfdrive.controls.lib.ford_path import FordPath, _model_path
+
+
+OFFSET_STATION_M = 7.0
+HEADING_TIME_S = 1.0
+CALIBRATION_APPROVED = False
+
+
+def _packed(value, resolution, offset):
+  """Mirror Float32 carControlSP and sign-reversed CANPacker rounding."""
+  value = struct.unpack("f", struct.pack("f", value))[0]
+  return -(math.floor((-value - offset) / resolution + 0.5) * resolution + offset)
+
+
+def _finite(*values):
+  try:
+    return all(math.isfinite(value) for value in values)
+  except (TypeError, ValueError, OverflowError):
+    return False
+
+
+def encode_model_action(model, desired_curvature, speed):
+  """Encode y(7) and max(7, v*1s)*selected limited curvature.
+
+  Preserve the reviewed core's endpoint hold when the path ends before 7 m.
+  This samples the available geometry; it does not extrapolate an unseen path.
+  """
+  if not _finite(desired_curvature, speed) or not .3 <= speed <= 55 or abs(desired_curvature) > 1:
+    return FordPath()
+  try:
+    path = _model_path(model)
+  except OverflowError:
+    return FordPath()
+  if path is None or not all(_finite(*values) for values in path):
+    return FordPath()
+  station, _, lateral, _ = path
+  c0 = float(np.interp(min(OFFSET_STATION_M, station[-1]), station, lateral))
+  c1 = max(OFFSET_STATION_M, speed*HEADING_TIME_S)*desired_curvature
+  return FordPath(True, c0, c1, 0., 0.) if _finite(c0, c1) else FordPath()
+
+
+class ModelActionController:
+  """Unquantized C0/C1 slew positions and one C1 feedback correction.
+
+  Feedback integrates requested minus measured curvature over traveled distance.
+  Freshness, measurement cadence and driver/PSCM arbitration belong to the caller.
+  """
+  __slots__ = ('c0', 'c1', 'correction', 'carryover_release_count')
+
+  def __init__(self):
+    self.reset()
+
+  def reset(self):
+    self.c0 = self.c1 = self.correction = 0.
+    self.carryover_release_count = 0  # Diagnostic only; never feeds the command law.
+
+  def update(self, model, desired_curvature, *, current_curvature, speed, dt, active=True, valid=True,
+             feedback_dt=None, feedback_enabled=True, pscm_limited=False):
+    feedback_dt = dt if feedback_dt is None else feedback_dt
+    if (not active or not valid or not _finite(dt, feedback_dt, current_curvature) or not .002 <= dt <= .1
+        or not 0. <= feedback_dt <= .15 or abs(current_curvature) > 1.):
+      self.reset()
+      return FordPath()
+    target = encode_model_action(model, desired_curvature, speed)
+    if not target.valid:
+      self.reset()
+      return FordPath()
+    base_c1 = float(np.clip(target.path_angle, -.5, .5))
+    # Preserve the linear path reference at 7 m when the base heading clips.
+    # This is instantaneous geometry, not stored error or C1 feedback spill.
+    c0 = float(np.clip(target.path_offset + OFFSET_STATION_M*(target.path_angle-base_c1), -5.11, 5.11))
+    self.c0 += float(np.clip(c0-self.c0, -4.*dt, 4.*dt))
+    lower = max(-.5, self.c1-.5*dt)
+    upper = min(.5, self.c1+.5*dt)
+    if not feedback_enabled:
+      self.correction = 0.
+    else:
+      direction = math.copysign(1., base_c1)
+      # Release only correction that prevents C1 from requesting the direction
+      # shared by model C0, slewed C0 and base C1, while measured steering is
+      # still opposite. One DBC step confirms each request is nonzero. Matched
+      # steering, neutral/conflicting centering and duplicate samples retain I.
+      if (feedback_dt > 0. and abs(base_c1) >= .0005 and current_curvature*direction < 0.
+          and min(target.path_offset*direction, self.c0*direction) >= .01
+          and (base_c1+self.correction)*direction <= 0.):
+        self.correction = 0.
+        self.carryover_release_count += 1
+      increment = (desired_curvature-current_curvature)*speed*feedback_dt
+      # LimitReached inhibits only extra demand in the measured turn direction.
+      # Opposing correction and changes to the model request remain available.
+      direction = current_curvature if current_curvature else self.c1
+      if pscm_limited and increment*direction > 0.:
+        # An old opposing correction may return to zero; don't trap it below
+        # the base request just because the PSCM now reports a limit.
+        increment = float(np.clip(increment, min(-self.correction, 0.), max(-self.correction, 0.)))
+      # Integrate only as far as this cycle's amplitude/slew envelope permits.
+      # If the base moved outside that envelope, allow increments toward it;
+      # never rewrite existing correction merely because the base changed.
+      request = base_c1+self.correction
+      self.correction += float(np.clip(increment, min(lower-request, 0.), max(upper-request, 0.)))
+    c1 = float(np.clip(base_c1+self.correction, -.5, .5))
+    self.c1 += float(np.clip(c1-self.c1, -.5*dt, .5*dt))
+    return FordPath(True, _packed(self.c0, .01, -5.12), _packed(self.c1, .0005, -.5), 0., 0.)
+
+
+class FordModelActionController:
+  """Input adapter for the opt-in selected-action controller.
+
+  controlsd owns upstream selection/limiting and service health. This adapter
+  checks ages and clock order, then supplies elapsed time to the three-state
+  core. Feedback advances once per fresh steering measurement; repeated samples
+  can still advance output slew. Raw model geometry is checked on every cycle.
+
+  CAN yaw remains a health gate, not the feedback measurement. Driver override
+  clears the correction. Fresh PSCM limits only inhibit outward integration;
+  neither a limit nor a repeated measurement freezes the model request.
+  """
+  def __init__(self):
+    self.core = ModelActionController()
+    self.reset()
+
+  def reset(self, status='inactive'):
+    self.core.reset()
+    self.last_time = self.last_measurement_time = self.last_model_time = None
+    self.diagnostics = {'status': status, 'hypothesis': 'model-action-c1-feedback-v3',
+                        'calibration_approved': CALIBRATION_APPROVED, 'command': (0., 0., 0., 0.)}
+
+  def update(self, model, desired_curvature, *, current_curvature, yaw_rate, speed, now, measurement_time, model_time,
+             reference_time, active, valid=True, driver_pressed=False, driver_torque=0., pscm_status=None):
+    reason = None
+    if not active:
+      reason = 'inactive'
+    elif not valid:
+      reason = 'invalid_service'
+    elif not _finite(desired_curvature, current_curvature, yaw_rate, speed, now, measurement_time, model_time, reference_time):
+      reason = 'nonfinite'
+    elif not all(-.005 <= now - timestamp <= .15 for timestamp in (measurement_time, model_time, reference_time)):
+      reason = 'stale_input'
+    elif not .3 <= speed <= 55 or abs(yaw_rate) > 3 or abs(desired_curvature) > 1 or abs(current_curvature) > 1:
+      reason = 'input_range'
+    if reason is not None:
+      self.reset(reason)
+      return FordPath()
+
+    dt = .01 if self.last_time is None else now - self.last_time
+    feedback_dt = 0. if self.last_measurement_time is None else measurement_time-self.last_measurement_time
+    if not .002 <= dt <= .1 or not 0. <= feedback_dt <= .15 or (
+      self.last_model_time is not None and model_time < self.last_model_time
+    ):
+      self.reset('timing_reset')
+      return FordPath()
+    status_fresh = (pscm_status is not None and pscm_status.valid and pscm_status.canMonoTime > 0
+                    and -.005 <= now-pscm_status.canMonoTime*1e-9 <= .15)
+    pscm_limited = bool(status_fresh and pscm_status.limit == 2)
+    driver_override = bool(driver_pressed or not _finite(driver_torque)
+                           or abs(driver_torque) > CarControllerParams.STEER_DRIVER_ALLOWANCE
+                           or (status_fresh and pscm_status.limit == 3))
+    feedback_enabled = not (driver_override or (status_fresh and (pscm_status.denied or pscm_status.lateralState != 2)))
+    command = self.core.update(model, desired_curvature, current_curvature=current_curvature, speed=speed, dt=dt,
+                               feedback_dt=feedback_dt, feedback_enabled=feedback_enabled, pscm_limited=pscm_limited)
+    if not command.valid:
+      self.reset('invalid_path')
+      return command
+    self.last_time, self.last_measurement_time, self.last_model_time = now, measurement_time, model_time
+    raw_heading = max(OFFSET_STATION_M, speed*HEADING_TIME_S)*desired_curvature
+    base_heading = float(np.clip(raw_heading, -.5, .5))
+    self.diagnostics = {'status': 'active', 'hypothesis': 'model-action-c1-feedback-v3',
+                        'calibration_approved': CALIBRATION_APPROVED, 'desired_curvature': desired_curvature,
+                        'model_age': now - model_time, 'measurement_age': now - measurement_time, 'reference_age': now - reference_time,
+                        'dt': dt, 'offset_request': self.core.c0, 'heading_request': self.core.c1,
+                        'curvature_error': desired_curvature-current_curvature, 'feedback_dt': feedback_dt,
+                        'heading_feedforward': base_heading,
+                        'offset_overflow': OFFSET_STATION_M*(raw_heading-base_heading),
+                        'heading_correction': self.core.correction, 'feedback_enabled': feedback_enabled,
+                        'carryover_release_count': self.core.carryover_release_count,
+                        'driver_override': driver_override, 'pscm_limited': pscm_limited, 'pscm_status_fresh': bool(status_fresh),
+                        'command': (command.path_offset, command.path_angle, 0., 0.)}
+    return command
+
+
+def select_model_action_controller(CP, enabled):
+  """Only opt-in Ford CAN FD vehicles override upstream curvature control."""
+  compatible = CP.brand == 'ford' and CP.flags & FordFlags.CANFD
+  if enabled and compatible:
+    return FordModelActionController()
+  return None

openpilot/selfdrive/controls/lib/ford_path.py

@@ -0,0 +1,368 @@
+from collections import deque
+from dataclasses import dataclass
+import math
+
+import numpy as np
+
+from opendbc.car.ford.values import CarControllerParams
+
+
+DBC_OFFSET = (-5.12, 5.11)
+DBC_ANGLE = (-0.5, 0.5235)
+DBC_CURVATURE = (-0.02, 0.02)
+DBC_CURVATURE_RATE = (-0.001024, 0.001023)
+
+DBC_OFFSET_RESOLUTION = 0.01
+DBC_ANGLE_RESOLUTION = 0.0005
+DBC_CURVATURE_RESOLUTION = 0.00002
+DBC_CURVATURE_RATE_RESOLUTION = 0.000001
+_PATH_MIN_LOOKAHEAD = 7.0
+_POSE_PREDICTION_TIME = 0.1
+_POSE_BLEND_CURVATURE = (0.006, 0.012)
+_PATH_OFFSET_RATE = 4.0
+_PATH_ANGLE_RATE = 1.0
+
+_PSCM_DT = 0.004
+_PSCM_C0_RATE = 1.5
+_PSCM_C1_RATE = 0.100006103515625
+_PSCM_C2_RATE = 0.0030059814453125
+_PSCM_SPEED_KPH = (0.0, 15.0, 40.0, 70.0, 100.0, 150.0, 200.0, 250.0)
+_PSCM_SPEED_GAIN = (32.0, 32.0, 32.0, 30.0, 30.0, 24.0, 12.0, 0.0)
+_PSCM_C0_EFFECTIVE_LIMIT = 1.0
+_PSCM_C1_EFFECTIVE_LIMIT = 0.349609375 / 10.0
+
+
+@dataclass(frozen=True)
+class FordPath:
+  valid: bool = False
+  path_offset: float = 0.0
+  path_angle: float = 0.0
+  curvature: float = 0.0
+  curvature_rate: float = 0.0
+
+
+@dataclass(frozen=True)
+class FordPscmState:
+  path_offset: float = 0.0
+  path_angle: float = 0.0
+  curvature: float = 0.0
+
+
+@dataclass(frozen=True)
+class FordModelPose:
+  path_offset: float
+  path_angle: float
+  offset_horizon: float
+  curvature_demand: float
+  forward_angle: float
+
+
+def _finite(value: float) -> float:
+  return float(value) if math.isfinite(value) else 0.0
+
+
+def _sample(distance: float, distances: list[float], values: list[float]) -> float:
+  return float(np.interp(distance, distances, values))
+
+
+def _blend_share(demand: float) -> float:
+  lower, upper = _POSE_BLEND_CURVATURE
+  return float(np.clip((demand - lower) / (upper - lower), 0.0, 1.0))
+
+
+def _model_path(model) -> tuple[list[float], list[float], list[float], list[float]] | None:
+  try:
+    x = [float(value) for value in model.position.x]
+    y = [float(value) for value in model.position.y]
+    heading = [float(value) for value in model.orientation.z]
+  except (AttributeError, TypeError, ValueError):
+    return None
+  if len(x) < 2 or len(x) != len(y) or len(x) != len(heading):
+    return None
+  if not all(math.isfinite(value) for values in (x, y, heading) for value in values):
+    return None
+
+  distance = [0.0]
+  for i in range(1, len(x)):
+    distance.append(distance[-1] + math.hypot(x[i] - x[i - 1], y[i] - y[i - 1]))
+  if distance[-1] <= 0.0:
+    return None
+
+  unwrapped_heading = [heading[0]]
+  for value in heading[1:]:
+    delta = (value - unwrapped_heading[-1] + math.pi) % (2.0 * math.pi) - math.pi
+    unwrapped_heading.append(unwrapped_heading[-1] + delta)
+  return distance, x, y, unwrapped_heading
+
+
+def _predicted_pose(distance: float, current_curvature: float,
+                    curvature_delta: float) -> tuple[float, float, float]:
+  curvature = current_curvature + 0.5 * curvature_delta
+  heading = curvature * distance
+  if abs(curvature) < 1e-9:
+    return distance, 0.0, 0.0
+  return math.sin(heading) / curvature, (1.0 - math.cos(heading)) / curvature, heading
+
+
+def _relative_pose(target_distance: float, path: tuple[list[float], list[float], list[float], list[float]],
+                   vehicle_pose: tuple[float, float, float]) -> tuple[float, float]:
+  distance, x, y, heading = path
+  vehicle_x, vehicle_y, vehicle_heading = vehicle_pose
+  dx = _sample(target_distance, distance, x) - vehicle_x
+  dy = _sample(target_distance, distance, y) - vehicle_y
+  cosine = math.cos(vehicle_heading)
+  sine = math.sin(vehicle_heading)
+  offset = -sine * dx + cosine * dy
+  angle = math.atan2(math.sin(_sample(target_distance, distance, heading) - vehicle_heading),
+                     math.cos(_sample(target_distance, distance, heading) - vehicle_heading))
+  return offset, angle
+
+
+def _path_pose(target_distance: float,
+               path: tuple[list[float], list[float], list[float], list[float]]) -> tuple[float, float, float]:
+  distance, x, y, heading = path
+  return (_sample(target_distance, distance, x), _sample(target_distance, distance, y),
+          _sample(target_distance, distance, heading))
+
+
+def _bounded_feedback(feedforward: float, feedback: float, resolution: float, zero_path_limit: float) -> float:
+  quantization_threshold = 0.5 * resolution
+  limit = max(abs(feedforward) - resolution, 0.0) if abs(feedforward) >= quantization_threshold else zero_path_limit
+  return float(np.clip(feedback, -limit, limit))
+
+
+def _model_pose(path: tuple[list[float], list[float], list[float], list[float]],
+                current_curvature: float, curvature_delta: float, v_ego: float) -> FordModelPose:
+  distance, _, _, _ = path
+  advance = min(v_ego * _POSE_PREDICTION_TIME, distance[-1])
+  offset_horizon = min(_PATH_MIN_LOOKAHEAD, distance[-1] - advance)
+  angle_horizon = min(max(v_ego, _PATH_MIN_LOOKAHEAD), distance[-1] - advance)
+
+  # Keep the model's remaining path as feedforward. Measured vehicle motion is
+  # a separate, short delay-aligned correction, so catching the requested
+  # curvature cannot erase a turn that is still present in the model path.
+  model_pose = _path_pose(advance, path)
+  model_offset, _ = _relative_pose(advance + offset_horizon, path, model_pose)
+  _, model_angle = _relative_pose(advance + angle_horizon, path, model_pose)
+  vehicle_pose = _predicted_pose(advance, current_curvature, curvature_delta)
+  feedback_offset, feedback_angle = _relative_pose(advance, path, vehicle_pose)
+  gentle_curvature = _POSE_BLEND_CURVATURE[0]
+  feedback_offset = _bounded_feedback(model_offset, feedback_offset, DBC_OFFSET_RESOLUTION,
+                                       0.5 * gentle_curvature * advance ** 2)
+  feedback_angle = _bounded_feedback(model_angle, feedback_angle, DBC_ANGLE_RESOLUTION,
+                                      gentle_curvature * advance)
+
+  offset_curvature = 2.0 * model_offset / max(offset_horizon, 1e-3) ** 2
+  angle_curvature = model_angle / max(angle_horizon, 1e-3)
+  return FordModelPose(model_offset + feedback_offset, model_angle + feedback_angle, offset_horizon,
+                       max(abs(offset_curvature), abs(angle_curvature)), model_angle)
+
+
+def _encode_pose(pose: FordModelPose, pose_share: float, curvature: float) -> FordPath:
+  path_offset = pose_share * pose.path_offset
+  path_angle = pose_share * pose.path_angle
+  if abs(path_offset) < 0.5 * DBC_OFFSET_RESOLUTION:
+    path_offset = 0.0
+  if abs(path_angle) < 0.5 * DBC_ANGLE_RESOLUTION:
+    path_angle = 0.0
+  limited_path_angle = float(np.clip(path_angle, *DBC_ANGLE))
+  path_offset += (path_angle - limited_path_angle) * pose.offset_horizon
+  return FordPath(
+    valid=True,
+    path_offset=float(np.clip(path_offset, *DBC_OFFSET)),
+    path_angle=limited_path_angle,
+    curvature=float(np.clip(curvature, *DBC_CURVATURE)),
+    curvature_rate=0.0,
+  )
+
+
+def _encode_path(path: tuple[list[float], list[float], list[float], list[float]], desired_curvature: float,
+                 current_curvature: float, curvature_delta: float, v_ego: float) -> FordPath:
+  pose = _model_pose(path, current_curvature, curvature_delta, v_ego)
+  pose_share = _blend_share(max(pose.curvature_demand, abs(desired_curvature)))
+
+  # Match upstream's C2-only normal driving, then continuously transfer the
+  # command to the model pose for larger maneuvers. An opposing/finished model
+  # path must unload sticky C2 and retain the fast pose needed to unwind it.
+  c2_opposes_path = desired_curvature != 0.0 and desired_curvature * pose.forward_angle <= 0.0
+  if c2_opposes_path:
+    pose_share = 1.0
+    curvature = 0.0
+  else:
+    curvature = desired_curvature * (1.0 - pose_share)
+
+  return _encode_pose(pose, pose_share, curvature)
+
+
+class FordPathController:
+  """Blend normal C2 following into the model's forward C0/C1 pose."""
+
+  def __init__(self, dt: float = 0.01):
+    self.dt = dt
+    self._last_path = FordPath(valid=True)
+    self._curvature_history = deque(maxlen=max(round(_POSE_PREDICTION_TIME / dt) + 1, 2))
+
+  def _limit(self, target: FordPath) -> FordPath:
+    offset_delta = target.path_offset - self._last_path.path_offset
+    angle_delta = target.path_angle - self._last_path.path_angle
+    scale = min(
+      1.0,
+      _PATH_OFFSET_RATE * self.dt / abs(offset_delta) if offset_delta else 1.0,
+      _PATH_ANGLE_RATE * self.dt / abs(angle_delta) if angle_delta else 1.0,
+    )
+    self._last_path = FordPath(
+      True,
+      self._last_path.path_offset + scale * offset_delta,
+      self._last_path.path_angle + scale * angle_delta,
+      self._last_path.curvature + scale * (target.curvature - self._last_path.curvature),
+      0.0,
+    )
+    return self._last_path
+
+  def update(self, model, desired_curvature: float, *, current_curvature: float = 0.0,
+             v_ego: float = 0.0, active: bool = True) -> FordPath:
+    if not active:
+      self._last_path = FordPath(valid=True)
+      self._curvature_history.clear()
+      return FordPath()
+    current_curvature = _finite(current_curvature)
+    self._curvature_history.append(current_curvature)
+    curvature_delta = (current_curvature - self._curvature_history[0]
+                       if len(self._curvature_history) == self._curvature_history.maxlen else 0.0)
+    path = _model_path(model) if model is not None else None
+    if path is None:
+      return self._limit(FordPath(valid=True))
+    return self._limit(_encode_path(path, _finite(desired_curvature), current_curvature, curvature_delta,
+                                    max(_finite(v_ego), 0.0)))
+
+
+def _pscm_slew(value: float, target: float, rate: float, ticks: int) -> float:
+  step = rate * _PSCM_DT * ticks
+  return float(np.clip(target, value - step, value + step))
+
+
+def _pscm_speed_gain(v_ego: float) -> float:
+  return float(np.interp(max(v_ego, 0.0) * 3.6, _PSCM_SPEED_KPH, _PSCM_SPEED_GAIN))
+
+
+def _wire_path(path: FordPath) -> FordPath:
+  return FordPath(
+    valid=path.valid,
+    path_offset=round(path.path_offset / DBC_OFFSET_RESOLUTION) * DBC_OFFSET_RESOLUTION,
+    path_angle=round(path.path_angle / DBC_ANGLE_RESOLUTION) * DBC_ANGLE_RESOLUTION,
+    curvature=round(path.curvature / DBC_CURVATURE_RESOLUTION) * DBC_CURVATURE_RESOLUTION,
+    curvature_rate=round(path.curvature_rate / DBC_CURVATURE_RATE_RESOLUTION) * DBC_CURVATURE_RATE_RESOLUTION,
+  )
+
+
+def _pscm_contributions(state: FordPscmState, v_ego: float) -> tuple[float, float, float]:
+  gain = _pscm_speed_gain(v_ego)
+  return (
+    float(np.clip(0.5 * gain * state.path_offset, -0.5 * gain, 0.5 * gain)),
+    float(np.clip(10.0 * gain * state.path_angle, -0.349609375 * gain, 0.349609375 * gain)),
+    float(np.clip(0.30078125 * gain * state.curvature * v_ego ** 2, -0.5 * gain, 0.5 * gain)),
+  )
+
+
+class FordPscmObserver:
+  """Mirror the firmware's held-command coefficient states at its 250 Hz step."""
+
+  def __init__(self):
+    self.state = FordPscmState()
+    self.command = FordPath(valid=True)
+    self._phase = 0.0
+
+  def reset(self) -> None:
+    self.state = FordPscmState()
+    self.command = FordPath(valid=True)
+    self._phase = 0.0
+
+  def advance(self, elapsed: float) -> None:
+    self._phase += max(elapsed, 0.0)
+    ticks = int((self._phase + 1e-12) / _PSCM_DT)
+    self._phase -= ticks * _PSCM_DT
+    if ticks == 0:
+      return
+    self.state = FordPscmState(
+      _pscm_slew(self.state.path_offset, self.command.path_offset, _PSCM_C0_RATE, ticks),
+      _pscm_slew(self.state.path_angle, self.command.path_angle, _PSCM_C1_RATE, ticks),
+      _pscm_slew(self.state.curvature, self.command.curvature + 10.0 * self.command.curvature_rate,
+                  _PSCM_C2_RATE, ticks),
+    )
+
+  def set_command(self, command: FordPath) -> None:
+    self.command = _wire_path(command)
+
+
+class FordPscmObserverPathController:
+  """Compensate model-path commands for the PSCM coefficient state it still carries."""
+
+  def __init__(self, dt: float = 0.01):
+    self.dt = dt
+    self._last_path = FordPath(valid=True)
+    self._curvature_history = deque(maxlen=max(round(_POSE_PREDICTION_TIME / dt) + 1, 2))
+    self.observer = FordPscmObserver()
+    self._sent_c2 = 0.0
+
+  def _reset(self) -> None:
+    self._last_path = FordPath(valid=True)
+    self._curvature_history.clear()
+    self.observer.reset()
+    self._sent_c2 = 0.0
+
+  def _command_for_state(self, target: FordPath, v_ego: float) -> FordPath:
+    # The target describes the desired fully-settled PSCM contribution. C0 keeps
+    # the remaining C1-saturated residual. C1 supplies the primary contribution
+    # that the known slow C2 state does not yet provide, without a guessed gain.
+    target_state = FordPscmState(target.path_offset, target.path_angle, target.curvature)
+    target_contribution = sum(_pscm_contributions(target_state, v_ego))
+    _, _, observed_c2 = _pscm_contributions(self.observer.state, v_ego)
+    gain = _pscm_speed_gain(v_ego)
+    required_fast = target_contribution - observed_c2
+    c1_contribution = float(np.clip(required_fast, -0.349609375 * gain, 0.349609375 * gain))
+    c0_contribution = required_fast - c1_contribution
+    path_offset = c0_contribution / (0.5 * gain) if gain > 0.0 else 0.0
+    path_angle = c1_contribution / (10.0 * gain) if gain > 0.0 else 0.0
+    return FordPath(
+      valid=True,
+      path_offset=float(np.clip(path_offset, -_PSCM_C0_EFFECTIVE_LIMIT, _PSCM_C0_EFFECTIVE_LIMIT)),
+      path_angle=float(np.clip(path_angle, -_PSCM_C1_EFFECTIVE_LIMIT, _PSCM_C1_EFFECTIVE_LIMIT)),
+      curvature=target.curvature,
+      curvature_rate=target.curvature_rate,
+    )
+
+  def _limit(self, target: FordPath, v_ego_raw: float) -> FordPath:
+    path_offset = float(np.clip(target.path_offset,
+                                self._last_path.path_offset - _PATH_OFFSET_RATE * self.dt,
+                                self._last_path.path_offset + _PATH_OFFSET_RATE * self.dt))
+    path_angle = float(np.clip(target.path_angle,
+                               self._last_path.path_angle - _PATH_ANGLE_RATE * self.dt,
+                               self._last_path.path_angle + _PATH_ANGLE_RATE * self.dt))
+    curvature = CarControllerParams.CURVATURE_LIMITS.apply_limits(
+      target.curvature, self._sent_c2, v_ego_raw, 0.0, True, CarControllerParams.LMC2_STEP,
+    )
+    self._sent_c2 = curvature
+    self._last_path = FordPath(True, path_offset, path_angle, curvature, target.curvature_rate)
+    self.observer.set_command(self._last_path)
+    return self._last_path
+
+  def update(self, model, desired_curvature: float, *, current_curvature: float = 0.0,
+             v_ego: float = 0.0, v_ego_raw: float = 0.0, active: bool = True) -> FordPath:
+    if not active:
+      self._reset()
+      return FordPath()
+
+    self.observer.advance(self.dt)
+    current_curvature = _finite(current_curvature)
+    self._curvature_history.append(current_curvature)
+    curvature_delta = (current_curvature - self._curvature_history[0]
+                       if len(self._curvature_history) == self._curvature_history.maxlen else 0.0)
+    path = _model_path(model) if model is not None else None
+    if path is None:
+      target = FordPath(valid=True)
+    else:
+      target = _encode_path(path, _finite(desired_curvature), current_curvature, curvature_delta,
+                            max(_finite(v_ego), 0.0))
+    v_ego_raw = max(_finite(v_ego_raw), 0.0)
+    command = self._command_for_state(target, v_ego_raw)
+    return self._limit(command, v_ego_raw)

openpilot/selfdrive/controls/tests/fixtures/ford_c2_free_path_routes.json

@@ -0,0 +1,229 @@
+{
+  "description": "Curvature-driven C0 and full-heading C1 command regression; does not predict counterfactual wheel response. Contains geometry and control signals only, no GPS.",
+  "fixture_sha256": "12782ac1b0d0637945f729a46ad03af16cd58188872b6a65f104e32c4db70e9b",
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+  },
+  "pairing": "controlsState cycle time; causal carState speed/yaw/pressed; exact consumed model timestamp and geometry; nearest same-cycle carControl and carControlSP within 5ms.",
+  "yaw_rate": "Negative carState.yawRate, matching the model/control curvature coordinate sign; no wheel-to-curvature conversion.",
+  "desired_curvature": "Exact controlsState.desiredCurvature from the matching controlsState cycle. This is the post-selection, post-limiting request consumed by controlsd; it is not a wheel-angle-to-curvature fit.",
+  "reference_time": "Exact consumed modelV2 publication time, in the same relative seconds as each episode. The extraction cache does not retain consumed lateralManeuverPlan timestamps or validity; model time is an explicit replay assumption and cannot verify alternate-reference freshness."
+}

openpilot/selfdrive/controls/tests/fixtures/ford_curvature_heading_route80.json

@@ -0,0 +1,67 @@
+{
+  "description": "Real route80 turn-command regressions. Signal-only fixture; no GPS. Counterfactual commands do not predict physical vehicle response.",
+  "route": "84865544361f55cb_00000080--1643deea7e",
+  "source_commit": "98662df401217a00ec9fc8e73b16857b6c220150",
+  "frozen_v3_controller_sha256": "576f4ec6f2dbc93f7e6c93a69839f69447eb5a0c2f834bd48b24f84a163dc2eb",
+  "fixture_sha256": "c1460e2cf1d3fd52b1a036d923fec7835a7d361126ee0c2decbc3f101ee6653c",
+  "episodes": [
+    {
+      "name": "under_333_339",
+      "range_seconds": [
+        331.5,
+        339.0
+      ],
+      "evidence_seconds": [
+        333.0,
+        339.0
+      ],
+      "samples": 745
+    },
+    {
+      "name": "over_417_420",
+      "range_seconds": [
+        415.5,
+        420.0
+      ],
+      "evidence_seconds": [
+        417.0,
+        420.0
+      ],
+      "samples": 447
+    },
+    {
+      "name": "under_430_435",
+      "range_seconds": [
+        428.5,
+        435.0
+      ],
+      "evidence_seconds": [
+        430.0,
+        435.0
+      ],
+      "samples": 646
+    }
+  ],
+  "sources": [
+    {
+      "name": "84865544361f55cb_00000080--1643deea7e--5--rlog.zst",
+      "bytes": 12531711,
+      "sha256": "059482830794cb0eabe6069b75a9610b900bf2a93d7a6624f53c575cef997157"
+    },
+    {
+      "name": "84865544361f55cb_00000080--1643deea7e--6--rlog.zst",
+      "bytes": 12560505,
+      "sha256": "147276789f5b14913adc4cd16db18f3d4bd27ce8497c9ff96fdf0315c219339f"
+    },
+    {
+      "name": "84865544361f55cb_00000080--1643deea7e--7--rlog.zst",
+      "bytes": 12660797,
+      "sha256": "b311b6ace75819db52b9618154d68c7d12e2751d5046b6d174adb89ef87a223c"
+    }
+  ],
+  "pairing": "Exact controlsState desiredCurvature and consumed model publication timestamp; causal carState speed, negative CAN yaw, and steeringPressed; nearest same-cycle carControl/carControlSP within 5 ms.",
+  "reference_time": "Consumed modelV2 publication time. Controller audit confirms route80 used modelV2 as reference throughout.",
+  "preroll": "Each episode starts from reset 1.5 s before evidence; v3_replay stores those exact cold-start commands and gates, while recorded stores original live path fields.",
+  "benchmark_clean": "Existing route80 benchmark mask: whole interval request minus 0.5 s through response (0.2 s) plus 0.25 s active, unpressed, valid, fresh, and speed >= 2 m/s.",
+  "expected_common_c1": "Independent shadow: clip(desiredCurvature * max(7 m, vEgo * 1 s), +/-0.5 rad), independently slewed at 0.5 rad/s and packed to Float32/sign-reversed CAN semantics. No subtraction of measured curvature."
+}

openpilot/selfdrive/controls/tests/fixtures/ford_heading_feedback_route80_status.json

@@ -0,0 +1,13 @@
+{
+  "description": "PSCM status and raw driver-torque overlay for the existing three route80 request windows. No GPS. No counterfactual vehicle response.",
+  "fixture_sha256": "a9defdc5abdf26724358d606beb16becbdf30faa972974d49b179a9e004d7629",
+  "base_fixture": "ford_curvature_heading_route80.npz",
+  "base_fixture_sha256": "c1460e2cf1d3fd52b1a036d923fec7835a7d361126ee0c2decbc3f101ee6653c",
+  "source_route": "84865544361f55cb_00000080--1643deea7e",
+  "source_commit": "98662df401217a00ec9fc8e73b16857b6c220150",
+  "samples": 1838,
+  "source_cache_sha256": "1cd3e0c00805869ace1c5954dc682644f36f5eddb71785b69e4cb9da40f7f04f",
+  "pairing": "Latest actual bus-0 EPS 972 frame at or before each controlsState cycle; raw steering torque from the exact causal carState used by the base fixture.",
+  "timestamp_policy": "Actual CAN event logMonoTime in route-relative seconds, not the benchmark response-shifted status. The old route predates the new carStateSP status telemetry; source CAN timestamps are an explicit replay approximation.",
+  "validity": "Replay validity uses the paired carState valid and canValid values; enum validity, availability and age are checked by the production feedback controller."
+}

openpilot/selfdrive/controls/tests/fixtures/ford_heading_recovery_requests.json

@@ -0,0 +1,40 @@
+{
+  "description": "Signal-only v6 turn-exit recovery regression; no location, device identity, or predicted new vehicle response.",
+  "recorded_controller_revision": "61dac4977bf9c36504398e8a4959dfed79cf6f05",
+  "baseline_revision": "61dac4977bf9c36504398e8a4959dfed79cf6f05",
+  "response_delay": 0.20000000298023224,
+  "samples": 9134,
+  "models": 1843,
+  "fixture_sha256": "41d5e3efcee03a9e02fcaf7bf456c050c6a671a5b7f7fc9706ddf4d27bad71b8",
+  "windows": [
+    {
+      "name": "overturn_then_underturn",
+      "range_s": [
+        19.99615067150053,
+        29.48070058550053
+      ],
+      "samples": 521
+    },
+    {
+      "name": "well_tracked_curve_a",
+      "range_s": [
+        56.19474309950053,
+        63.68808603150053
+      ],
+      "samples": 729
+    },
+    {
+      "name": "well_tracked_curve_b",
+      "range_s": [
+        101.19780691350051,
+        116.33885445450052
+      ],
+      "samples": 810
+    }
+  ],
+  "selection": "One previously identified overturn-then-underturn event and two previously reported well-tracked curves; selected before recovery implementation.",
+  "mask": "Whole t-0.5 through t+0.65 interval active, valid, fresh, unpressed, raw driver torque magnitude <=1 Nm; requested |curvature|*speed\u00b2 >=.5 m/s\u00b2.",
+  "timing": "Exact consumed model publication; causal CAN/PSCM at estimated control computation time. Subtract observed median computation-to-publication delay; unsampled tick timing remains approximate.",
+  "context": "At least 20 seconds prior context or the available start, extended before the latest observed reset. Overlapping episodes are merged.",
+  "coordinates": "Times are local elapsed seconds; models contain only relative position.x/y and orientation.z arrays."
+}

openpilot/selfdrive/controls/tests/fixtures/ford_large_turn_requests_route83.json

@@ -0,0 +1,247 @@
+{
+  "description": "Signal-only historical fallback evidence and frozen-v5 comparison; no GPS or inferred counterfactual vehicle response.",
+  "route": "route83",
+  "recorded_commit": "79a4caa1f6b71488949108aee9ae6ae6566347b1",
+  "fixture_sha256": "d00312c430ace47000c05b8284ee8d56df56ec24bb17a9ea8f4dce83133527c3",
+  "samples": 11744,
+  "model_count": 2367,
+  "source_cache_sha256": "53d786aff2e0b6338e1991320145305fda3101f7b76e50bd2929adbcaea95b28",
+  "response_delay": 0.20000000298023224,
+  "episodes": [
+    [
+      1861.2933736250002,
+      1874.756970279
+    ],
+    [
+      1878.07372132,
+      1892.07372132
+    ],
+    [
+      1950.874232409,
+      1964.874232409
+    ],
+    [
+      2440.9020600930003,
+      2456.964158177
+    ],
+    [
+      2580.722658577,
+      2611.364366768
+    ],
+    [
+      2734.478264791,
+      2764.574374172
+    ]
+  ],
+  "windows": [
+    {
+      "name": "successful_large_early",
+      "role": "authority_target",
+      "range_s": [
+        1866.722720383,
+        1874.756970279
+      ],
+      "samples": 426,
+      "substantial_demand_required": true,
+      "recorded_can_ratio_02s_median": 1.0233371460413845,
+      "published_median_abs_c0_c1": [
+        1.6002928018569946,
+        0.2796146124601364
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        1.6002928018569946,
+        0.2796146124601364
+      ],
+      "phase_samples": {
+        "phase_turn_in": 15,
+        "phase_held": 122,
+        "phase_release": 402,
+        "phase_reversal": 0
+      }
+    },
+    {
+      "name": "centering_reversal_positive_to_negative",
+      "role": "reversal",
+      "range_s": [
+        1888.07372132,
+        1892.07372132
+      ],
+      "samples": 396,
+      "substantial_demand_required": false,
+      "recorded_can_ratio_02s_median": null,
+      "published_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "phase_samples": {
+        "phase_turn_in": 283,
+        "phase_held": 48,
+        "phase_release": 104,
+        "phase_reversal": 21
+      }
+    },
+    {
+      "name": "centering_reversal_negative_to_positive",
+      "role": "reversal",
+      "range_s": [
+        1960.874232409,
+        1964.874232409
+      ],
+      "samples": 397,
+      "substantial_demand_required": false,
+      "recorded_can_ratio_02s_median": null,
+      "published_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "phase_samples": {
+        "phase_turn_in": 154,
+        "phase_held": 0,
+        "phase_release": 183,
+        "phase_reversal": 21
+      }
+    },
+    {
+      "name": "clean_release",
+      "role": "release",
+      "range_s": [
+        2453.714158177,
+        2456.964158177
+      ],
+      "samples": 323,
+      "substantial_demand_required": false,
+      "recorded_can_ratio_02s_median": null,
+      "published_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        0.0,
+        0.0
+      ],
+      "phase_samples": {
+        "phase_turn_in": 4,
+        "phase_held": 0,
+        "phase_release": 305,
+        "phase_reversal": 17
+      }
+    },
+    {
+      "name": "successful_smaller_positive",
+      "role": "sign_coverage_only",
+      "range_s": [
+        2590.722658577,
+        2600.918740146
+      ],
+      "samples": 175,
+      "substantial_demand_required": true,
+      "recorded_can_ratio_02s_median": 1.0960646334373787,
+      "published_median_abs_c0_c1": [
+        0.42173025012016296,
+        0.1222948431968689
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        0.42173025012016296,
+        0.1222948431968689
+      ],
+      "phase_samples": {
+        "phase_turn_in": 170,
+        "phase_held": 61,
+        "phase_release": 0,
+        "phase_reversal": 0
+      }
+    },
+    {
+      "name": "large_under_response",
+      "role": "under_response_challenge",
+      "range_s": [
+        2604.2254721,
+        2611.364366768
+      ],
+      "samples": 128,
+      "substantial_demand_required": true,
+      "recorded_can_ratio_02s_median": 0.7322859508492778,
+      "published_median_abs_c0_c1": [
+        2.4204851388931274,
+        0.42145511507987976
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        2.4204851388931274,
+        0.42145511507987976
+      ],
+      "phase_samples": {
+        "phase_turn_in": 68,
+        "phase_held": 96,
+        "phase_release": 56,
+        "phase_reversal": 0
+      }
+    },
+    {
+      "name": "successful_large_181deg",
+      "role": "authority_target",
+      "range_s": [
+        2744.478264791,
+        2750.573209708
+      ],
+      "samples": 207,
+      "substantial_demand_required": true,
+      "recorded_can_ratio_02s_median": 1.0087938914780248,
+      "published_median_abs_c0_c1": [
+        2.1044259071350098,
+        0.3815947473049164
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        2.1044259071350098,
+        0.3815947473049164
+      ],
+      "phase_samples": {
+        "phase_turn_in": 137,
+        "phase_held": 94,
+        "phase_release": 64,
+        "phase_reversal": 0
+      }
+    },
+    {
+      "name": "large_over_response_290deg",
+      "role": "over_response_challenge_not_target",
+      "range_s": [
+        2760.493612962,
+        2764.574374172
+      ],
+      "samples": 181,
+      "substantial_demand_required": true,
+      "recorded_can_ratio_02s_median": 1.2515789463064766,
+      "published_median_abs_c0_c1": [
+        4.737145900726318,
+        0.5235000252723694
+      ],
+      "send_clamped_median_abs_c0_c1": [
+        4.737145900726318,
+        0.5
+      ],
+      "phase_samples": {
+        "phase_turn_in": 139,
+        "phase_held": 90,
+        "phase_release": 41,
+        "phase_reversal": 0
+      }
+    }
+  ],
+  "selection": "Authority targets require automatic turn windows with >=1 second strict torque eligibility, eligible |wheel|>=150 degrees, and whole-window CAN response ratio median 0.90..1.10 at fixed 0.2 s. No positive-request large turn qualifies.",
+  "non_targets": "Positive smaller turn supplies sign coverage only. Under/over response and release/reversal windows are regression challenges, not authority targets.",
+  "context": "At least 10 s pre-roll or available route start, extended to include the preceding feedback reset/sign reversal. Overlapping intervals are merged. First episode begins at the partial route boundary with unobserved earlier history.",
+  "phase_policy": "Held means request curvature range over +/-0.25 s times speed squared <0.15 m/s2 at demand>=0.5. Turn-in/release compare current absolute curvature with the historical held request at measurement_time-delay, scaled by max(7,speed), using +/-0.0005 rad. These masks can overlap held; reversal means opposing delayed/current signs.",
+  "wire_policy": "Published coefficients preserve Float32 values. Send-clamped copy caps C0 to +/-5.11 and C1 to +/-0.5 before packing. Actual decoded wire is normalized to controller sign, nearest within 15 ms; wire_time/fresh/mode expose timing approximation.",
+  "model_schema": "models[model_index] contains position.x, position.y, orientation.z; Float32 conversion preserves the original model payload precision.",
+  "v5_reference": "Frozen full sequential replay from command_replay.npz, whose source hash and limitations are recorded in command_replay.json.",
+  "frozen_v5_revision": "09acf8ec2f327769f00ee53563ad2dd9225e37a7",
+  "preroll_validation": "Compact reset replay exactly matches full sequential frozen-v5 C0/C1, gates and bias on all 2233 evidence samples."
+}

openpilot/selfdrive/controls/tests/fixtures/ford_turn_exit_requests.json

@@ -0,0 +1,156 @@
+{
+  "description": "Anonymous recorded-input turn-exit regression fixture; command construction only, not simulated vehicle response.",
+  "baseline_revision": "dfcfddb91ce2409511f5b2dbce25d06d5056b3d6",
+  "baseline_hypothesis": "model-pose-c0-c1-feedback-v7",
+  "baseline_source_hashes": {
+    "controller_sha256": "4951a6352d89fcd66277bbfe682bd22e935a31b5a4db33e617ad21189b6705fd",
+    "allocator_sha256": "383538fc7cdae3bc28dffb71fe12ac5f3f9866ffbe6adfb7457f3593e9fc903a"
+  },
+  "fixture_sha256": "87a030c309061b7dc218715d05440c2077e465a8138079b46e8e8cee94201e54",
+  "source_fixture_sha256": "d476110b83dc628ffbd094220e464d6d3114b709bda2977813c3217964d41086",
+  "response_delay": 0.20000000298023224,
+  "publication_latency_estimate_s": 0.0015483515003040793,
+  "samples": 15273,
+  "model_count": 3078,
+  "evidence_samples": 4879,
+  "context_policy": "At least twenty seconds prior context, extended before the last observed reset. Overlapping intervals are merged.",
+  "provenance": "Selected from a recorded drive running the pinned baseline; request, model, driver and PSCM observations stay fixed during replay.",
+  "baseline_policy": "Stored commands, validity and bias exactly match the complete baseline replay on evidence samples. Context outside evidence initializes state and is not an exact-output target.",
+  "compact_full_baseline_evidence_parity": {
+    "commands": {
+      "exact": true,
+      "max_difference": 0.0
+    },
+    "valid": {
+      "exact": true,
+      "max_difference": 0.0
+    },
+    "heading_bias": {
+      "exact": true,
+      "max_difference": 0.0
+    }
+  },
+  "measurement_policy": "Controller computation time is estimated from publication time using the recorded median latency; exact vehicle motion under changed commands is unknown.",
+  "clean_policy": "Every sample from request time minus 0.5 s through plus 0.65 s is active, valid, fresh, unpressed and within 1 Nm raw driver torque. Demand is absolute desired curvature times current speed squared; substantial means at least 0.5 m/s2.",
+  "driver_policy": "All replay inputs retain driver interference; only comparison metrics use the clean mask. History-reset failures intentionally retain nearby driver context.",
+  "coordinates": "Elapsed seconds shifted to the first fixture control cycle; model x/y/heading are vehicle-relative, not global position.",
+  "retained_fields": [
+    "t",
+    "episode",
+    "model_index",
+    "models",
+    "desired_curvature",
+    "yaw_rate",
+    "speed",
+    "measurement_time",
+    "model_time",
+    "reference_time",
+    "active",
+    "valid",
+    "pressed",
+    "steering_torque",
+    "pscm_timestamp",
+    "pscm_valid",
+    "pscm_lateral_state",
+    "pscm_limit",
+    "pscm_capability",
+    "pscm_denied",
+    "clean_rawtorque",
+    "demand",
+    "window_masks",
+    "evidence",
+    "baseline_commands",
+    "baseline_valid",
+    "baseline_heading_base",
+    "baseline_heading_target",
+    "baseline_heading_bias",
+    "baseline_feedback_yaw_error",
+    "baseline_feedback_reference_curvature",
+    "baseline_status",
+    "baseline_offset_target"
+  ],
+  "omitted_data": "No route/device identifiers, VIN, GPS, private paths, raw wheel angle, wheel rate, EPS torque, or absolute clock origins.",
+  "baseline_status_meaning": "feedback_status from the pinned baseline",
+  "windows": [
+    {
+      "name": "good_curve_a",
+      "role": "comparison",
+      "range_s": [
+        20.0002130975003,
+        25.0002130975003
+      ],
+      "samples": 496,
+      "clean_substantial_samples": 259
+    },
+    {
+      "name": "first_reversal",
+      "role": "reversal",
+      "range_s": [
+        83.0002130975003,
+        92.7002130975003
+      ],
+      "samples": 964,
+      "clean_substantial_samples": 167
+    },
+    {
+      "name": "good_curve_b",
+      "role": "comparison",
+      "range_s": [
+        121.0002130975003,
+        128.0002130975003
+      ],
+      "samples": 695,
+      "clean_substantial_samples": 308
+    },
+    {
+      "name": "second_reversal",
+      "role": "reversal",
+      "range_s": [
+        133.5002130975003,
+        138.9002130975003
+      ],
+      "samples": 537,
+      "clean_substantial_samples": 191
+    },
+    {
+      "name": "large_turn_driver_context_a",
+      "role": "driver_context",
+      "range_s": [
+        150.0002130975003,
+        157.0002130975003
+      ],
+      "samples": 695,
+      "clean_substantial_samples": 0
+    },
+    {
+      "name": "over_growth",
+      "role": "over_response",
+      "range_s": [
+        182.0002130975003,
+        191.0002130975003
+      ],
+      "samples": 897,
+      "clean_substantial_samples": 66
+    },
+    {
+      "name": "large_turn_driver_context_b",
+      "role": "driver_context",
+      "range_s": [
+        199.0002130975003,
+        205.0002130975003
+      ],
+      "samples": 595,
+      "clean_substantial_samples": 281
+    },
+    {
+      "name": "zero_bias_release",
+      "role": "under_response",
+      "range_s": [
+        202.0002130975003,
+        205.0002130975003
+      ],
+      "samples": 297,
+      "clean_substantial_samples": 279
+    }
+  ]
+}

openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py

@@ -0,0 +1,61 @@
+import ast
+import io
+import json
+import logging
+from pathlib import Path
+from types import SimpleNamespace
+import unittest
+
+from openpilot.common.logging_extra import SwagFormatter, SwagLogger
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController
+from openpilot.selfdrive.controls.tests.test_ford_model_action import circle
+
+
+class TestFordControlsLogging(unittest.TestCase):
+  def emit_controls_event(self, event, controls):
+    # Execute the actual controlsd call with the real logger and formatter,
+    # without launching hardware-dependent Controls or opening logging IPC.
+    source_path = Path(__file__).resolve().parents[1] / 'controlsd.py'
+    source = ast.parse(source_path.read_text())
+    calls = [node for node in ast.walk(source) if isinstance(node, ast.Call)
+             and isinstance(node.func, ast.Attribute) and isinstance(node.func.value, ast.Name)
+             and node.func.value.id == 'cloudlog' and node.args
+             and isinstance(node.args[0], ast.Constant) and node.args[0].value == event]
+    self.assertEqual(len(calls), 1)
+    logger = SwagLogger()
+    logger.setLevel(logging.INFO)  # disabled INFO logging would hide this crash
+    stream = io.StringIO()
+    handler = logging.StreamHandler(stream)
+    handler.setFormatter(SwagFormatter(logger))
+    logger.addHandler(handler)
+    try:
+      expression = ast.Expression(body=calls[0])
+      eval(compile(expression, str(source_path), 'eval'), {'cloudlog': logger, 'self': controls, 'reference_service': 'modelV2'})
+      record = json.loads(stream.getvalue())
+    finally:
+      handler.close()
+    self.assertEqual(record['level'], 'INFO')
+    self.assertEqual(record['msg']['event'], event)
+    return record['msg']
+
+  def test_startup_logs_selected_controller_without_crashing(self):
+    for controller in (None, FordModelActionController()):
+      with self.subTest(controller=type(controller).__name__):
+        record = self.emit_controls_event('Ford path controller selected',
+                                          SimpleNamespace(ford_path_controller=controller, ford_model_action=controller is not None))
+        self.assertEqual(record['controller'], 'upstream' if controller is None else type(controller).__name__)
+
+  def test_candidate_diagnostics_identify_the_experiment_and_do_not_claim_calibration(self):
+    controller = FordModelActionController()
+    for active, valid in ((False, True), (True, True), (True, False)):
+      controller.update(circle(.01), .03, current_curvature=.015, yaw_rate=.3, speed=20., now=1.,
+                        measurement_time=1., model_time=1., reference_time=1., active=active, valid=valid)
+      controls = SimpleNamespace(ford_path_controller=controller, desired_curvature=.03, curvature=.015,
+                                 sm=SimpleNamespace(logMonoTime={'modelV2': 123456789, 'carState': 123450000}))
+      record = self.emit_controls_event('Ford C2-free path tracking', controls)
+      self.assertEqual(record['hypothesis'], 'model-action-c1-feedback-v3')
+      self.assertIs(record['calibration_approved'], False)
+      self.assertEqual(record['command'][2:], [0., 0.])
+      self.assertEqual(record['status'], controller.diagnostics['status'])
+      if active and valid:
+        self.assertAlmostEqual(record['offset_overflow'], .7)

openpilot/selfdrive/controls/tests/test_ford_model_action.py

@@ -0,0 +1,194 @@
+import math
+from types import SimpleNamespace
+
+import numpy as np
+import pytest
+
+from opendbc.can import CANPacker, CANParser
+from opendbc.car.ford.fordcan import CanBus, create_lat_ctl2_msg
+from openpilot.cereal import custom
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+from openpilot.selfdrive.controls.lib.ford_model_action import ModelActionController, encode_model_action
+
+
+def make_model(x, y, heading):
+  return SimpleNamespace(position=SimpleNamespace(x=x, y=y), orientation=SimpleNamespace(z=heading))
+
+
+def circle(curvature):
+  s = np.linspace(0., 60., 601)
+  return make_model(np.sin(curvature*s)/curvature, (1-np.cos(curvature*s))/curvature, curvature*s)
+
+
+def straight(offset=0.):
+  x = np.linspace(0., 60., 121)
+  return make_model(x, np.full_like(x, offset), np.zeros_like(x))
+
+
+def test_selected_action_controls_heading_even_when_model_previews_another_turn():
+  model = circle(.02)
+  assert encode_model_action(model, 0., 20.).path_angle == 0.
+  assert encode_model_action(model, -.004, 20.).path_angle == pytest.approx(-.08)
+  assert encode_model_action(model, 0., 20.).path_offset > 0.
+
+
+def test_centering_information_is_independent_of_action_and_not_scaled_with_speed():
+  for speed in (2., 7., 20., 35.):
+    target = encode_model_action(straight(.4), 0., speed)
+    assert target == FordPath(True, .4, 0., 0., 0.)
+  for sign in (-1, 1):
+    target = encode_model_action(circle(sign*.01), sign*.01, 20.)
+    assert target.path_offset == pytest.approx(sign*(1-math.cos(.07))/.01, abs=1e-6)
+    assert target.path_angle == pytest.approx(sign*.2)  # No 10 m cap at highway speed.
+
+
+def test_three_control_states_are_sufficient_for_every_next_output():
+  controller = ModelActionController()
+  assert not hasattr(controller, '__dict__')
+  for i in range(300):
+    copied = ModelActionController()
+    copied.c0, copied.c1, copied.correction = controller.c0, controller.c1, controller.correction
+    model = straight(.2*math.sin(i*.1))
+    kwargs = {'speed': 20., 'dt': .01}
+    desired = .005*math.cos(i*.03)
+    assert controller.update(model, desired, current_curvature=0., **kwargs) == copied.update(model, desired, current_curvature=0., **kwargs)
+
+
+def test_held_turn_releases_without_a_bias_tail_or_sign_reversal():
+  for sign in (-1., 1.):
+    controller = ModelActionController()
+    for _ in range(400):
+      out = controller.update(circle(sign*.01), sign*.01, current_curvature=sign*.01, speed=20., dt=.01)
+    assert out.path_angle == pytest.approx(sign*.2)
+    previous = np.array([out.path_offset, out.path_angle])
+    for desired in sign*np.linspace(.01, 0., 101):
+      out = controller.update(straight(), desired, current_curvature=desired, speed=20., dt=.01)
+      values = np.array([out.path_offset, out.path_angle])
+      assert (abs(values) <= abs(previous)+1e-8).all()
+      assert (sign*values >= -1e-8).all()
+      previous = values
+    assert out == FordPath(True, 0., 0., 0., 0.)
+
+
+def test_current_model_replacement_leaves_only_independent_actuator_slew():
+  controller = ModelActionController()
+  for _ in range(150):
+    controller.update(straight(1.), .04, current_curvature=.04, speed=20., dt=.01)
+  # C0 starts at 1 + 7*(.8-.5) = 3.1 m, including the clipped heading.
+  for _ in range(78):
+    out = controller.update(straight(), 0., current_curvature=0., speed=20., dt=.01)
+  assert out.path_offset == pytest.approx(0.)
+  assert out.path_angle > 0.  # C1 cannot hold C0 during its longer release.
+  for _ in range(22):
+    out = controller.update(straight(), 0., current_curvature=0., speed=20., dt=.01)
+  assert out == FordPath(True, 0., 0., 0., 0.)
+
+
+@pytest.mark.parametrize('overrides', [{'active': False}, {'valid': False}, {'dt': .2}, {'speed': math.nan}])
+def test_invalid_or_inactive_input_clears_state_before_reengagement(overrides):
+  controller = ModelActionController()
+  for _ in range(100):
+    controller.update(straight(.5), .01, current_curvature=.01, speed=20., dt=.01)
+  kwargs = {'speed': 20., 'dt': .01, 'active': True, 'valid': True}
+  kwargs.update(overrides)
+  assert controller.update(straight(), 0., current_curvature=0., **kwargs) == FordPath()
+  assert (controller.c0, controller.c1) == (0., 0.)
+  assert controller.update(straight(), 0., current_curvature=0., speed=20., dt=.01) == FordPath(True, 0., 0., 0., 0.)
+
+
+def test_malformed_geometry_and_nonfinite_action_never_create_an_active_command():
+  for model, desired in ((None, 0.), (straight(), math.nan), (straight(), math.inf)):
+    assert not encode_model_action(model, desired, 20.).valid
+
+
+def test_selected_core_reversal_through_float32_and_wire_keeps_sign_and_zero_c2():
+  controller = ModelActionController()
+  packer = CANPacker('ford_lincoln_base_pt')
+  parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], 0)
+  bus = CanBus(fingerprint={0: {}})
+  previous = np.zeros(2)
+  for i in range(600):
+    sign = 1. if i < 300 else -1.
+    out = controller.update(straight(sign*8.), sign*.1, current_curvature=sign*.1, speed=30., dt=.01)
+    fields = np.array([out.path_offset, out.path_angle])
+    assert (abs(fields) <= [5.1100001, .5000001]).all()
+    assert (abs(fields-previous) <= [.0500001, .0055001]).all()
+    previous = fields
+    message = custom.CarControlSP.new_message()
+    message.fordLateralPath.pathOffset = out.path_offset
+    message.fordLateralPath.pathAngle = out.path_angle
+    packet = create_lat_ctl2_msg(packer, bus, 2, -message.fordLateralPath.pathOffset,
+                                -message.fordLateralPath.pathAngle, out.curvature, out.curvature_rate, i % 16)
+    parser.update([i*10_000_000, [packet]])
+    decoded = parser.vl['LateralMotionControl2']
+    assert decoded['LatCtlPathOffst_L_Actl'] == pytest.approx(-out.path_offset)
+    assert decoded['LatCtlPath_An_Actl'] == pytest.approx(-out.path_angle)
+    assert decoded['LatCtlCurv_No_Actl'] == decoded['LatCtlCrv_NoRate2_Actl'] == 0.
+
+
+def test_short_path_holds_available_endpoint_without_extrapolation():
+  model = make_model([0., 1.], [0., .1], [0., 0.])
+  assert encode_model_action(model, .01, 20.) == FordPath(True, .1, .2, 0., 0.)
+
+
+def test_overflowing_arc_resets_instead_of_publishing_invalid_geometry():
+  model = make_model([0., 1e308, -1e308], [0., 0., 0.], [0., 0., 0.])
+  controller = ModelActionController()
+  controller.update(straight(.4), .01, current_curvature=.01, speed=20., dt=.01)
+  assert controller.update(model, .01, current_curvature=.01, speed=20., dt=.01) == FordPath()
+  assert (controller.c0, controller.c1) == (0., 0.)
+
+
+@pytest.mark.parametrize('value', [None, 'bad', 10**400])
+@pytest.mark.parametrize('field', ['dt', 'speed', 'desired_curvature'])
+def test_malformed_numeric_input_resets_without_throwing(field, value):
+  controller = ModelActionController()
+  kwargs = {'speed': 20., 'dt': .01, 'desired_curvature': .01}
+  controller.update(straight(.4), current_curvature=kwargs['desired_curvature'], **kwargs)
+  kwargs[field] = value
+  assert controller.update(straight(.4), current_curvature=kwargs['desired_curvature'], **kwargs) == FordPath()
+  assert (controller.c0, controller.c1) == (0., 0.)
+
+
+@pytest.mark.parametrize('model', [
+  make_model([], [], []), make_model([0.], [0.], [0.]),
+  make_model([0., 10.], [0.], [0., 0.]), make_model([0., 10.], [0., 0.], [0.]),
+  make_model([0., 0.], [0., 0.], [0., 0.]),
+  make_model([0., 10.], [0., math.nan], [0., 0.]), make_model([0., math.inf], [0., 0.], [0., 0.]),
+  make_model([0., 10.], [0., 0.], [0., math.inf]),
+  make_model([0., 10**400], [0., 0.], [0., 0.]),
+  make_model([0., 10.], [0., 0.], [1e308, -1e308]),
+])
+def test_malformed_model_arrays_cannot_reuse_a_previous_valid_command(model):
+  controller = ModelActionController()
+  controller.update(straight(.4), .01, current_curvature=.01, speed=20., dt=.01)
+  assert controller.update(model, .01, current_curvature=.01, speed=20., dt=.01) == FordPath()
+  assert (controller.c0, controller.c1) == (0., 0.)
+
+
+@pytest.mark.parametrize('field,value,valid', [
+  ('speed', .2999, False), ('speed', .3, True), ('speed', 55., True), ('speed', 55.0001, False),
+  ('desired_curvature', -1., True), ('desired_curvature', 1., True), ('desired_curvature', -1.0001, False),
+  ('dt', .001999, False), ('dt', .002, True), ('dt', .1, True), ('dt', .100001, False), ('dt', 0., False),
+])
+def test_domain_and_elapsed_time_boundaries(field, value, valid):
+  kwargs = {'speed': 20., 'desired_curvature': .01, 'dt': .01}
+  kwargs[field] = value
+  assert ModelActionController().update(straight(.4), current_curvature=kwargs['desired_curvature'], **kwargs).valid == valid
+
+
+def test_arc_station_not_forward_x_or_model_heading_determines_offset():
+  x = np.array([0., 6., 12.])
+  y = .4+x*.75
+  target = encode_model_action(make_model(x, y, [2., -2., 1.]), -.01, 20.)
+  # Arc length is 1.25*x on this line, so y(arc=7)=.4+.75*(7/1.25).
+  assert target.path_offset == pytest.approx(4.6)
+  assert target.path_angle == pytest.approx(-.2)
+
+
+def test_duplicate_stations_keep_valid_geometry_and_first_cycle_slew():
+  model = make_model([0., 0., 10.], [.4, .4, .4], [0., 0., 0.])
+  assert encode_model_action(model, .01, 20.) == FordPath(True, .4, .2, 0., 0.)
+  out = ModelActionController().update(model, .01, current_curvature=.01, speed=20., dt=.002)
+  assert out.path_offset == pytest.approx(.01)
+  assert out.path_angle == pytest.approx(.001)

openpilot/selfdrive/controls/tests/test_ford_model_action_adapter.py

@@ -0,0 +1,454 @@
+"""Exercise the candidate through existing selection, publication and CAN code.
+
+Tests enable the candidate through controlsd's real startup selection.
+No hardware, IPC or CAN transmission is involved.
+"""
+import ast
+from collections import defaultdict
+import json
+import math
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+from opendbc.can import CANParser
+from opendbc.car import Bus, structs
+from opendbc.car.ford.carcontroller import CarController
+from opendbc.car.ford.fordcan import calculate_lat_ctl2_checksum
+from opendbc.car.ford.values import CAR, CarControllerParams, FordFlags
+from openpilot.cereal import custom
+from openpilot.selfdrive.car.helpers import convert_carControlSP
+from openpilot.selfdrive.controls.lib.drive_helpers import clip_curvature
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+from openpilot.selfdrive.controls.tests.test_ford_model_action import circle, straight
+from openpilot.selfdrive.controls.tests.test_ford_model_action_selection import CANFD_CARS, car_params, startup
+
+
+def update(controller, now=1., **overrides):
+  kwargs = {'model': straight(.4), 'desired_curvature': .01, 'speed': 20., 'yaw_rate': 0., 'now': now,
+                'model_time': now, 'measurement_time': now, 'reference_time': now, 'active': True}
+  kwargs.update(overrides)
+  kwargs.setdefault('current_curvature', kwargs['desired_curvature'])  # Preserve feedforward-only compatibility probes.
+  return controller.update(**kwargs)
+
+
+@pytest.mark.parametrize('field', ['model_time', 'measurement_time', 'reference_time'])
+@pytest.mark.parametrize('age', [.151, -.006])
+def test_stale_or_future_service_clears_commands_and_reengages_from_zero(field, age):
+  controller = FordModelActionController()
+  update(controller)
+  assert update(controller, 1.01, **{field: 1.01-age}) == FordPath()
+  assert controller.diagnostics['status'] == 'stale_input'
+  assert update(controller, 1.02).path_offset == pytest.approx(.04)
+
+
+@pytest.mark.parametrize('change,reason', [
+  ({'now': 1.}, 'timing_reset'),
+  ({'now': .99}, 'timing_reset'),
+  ({'now': 1.001}, 'timing_reset'),
+  ({'now': 1.101}, 'timing_reset'),
+  ({'model_time': .999}, 'timing_reset'),
+  ({'measurement_time': .999}, 'timing_reset'),
+  ({'active': False}, 'inactive'),
+  ({'valid': False}, 'invalid_service'),
+  ({'model': None}, 'invalid_path'),
+  ({'yaw_rate': math.nan}, 'nonfinite'),
+  ({'yaw_rate': 3.01}, 'input_range'),
+  ({'speed': 55.01}, 'input_range'),
+  ({'desired_curvature': 1.01}, 'input_range'),
+])
+def test_invalid_cycle_never_keeps_a_previous_active_request(change, reason):
+  controller = FordModelActionController()
+  update(controller)
+  now = change.get('now', 1.01)
+  assert update(controller, **dict(change, now=now)) == FordPath()
+  assert controller.diagnostics['status'] == reason
+  assert (controller.core.c0, controller.core.c1) == (0., 0.)
+  assert update(controller, now+1.).path_angle == pytest.approx(.005)
+
+
+@pytest.mark.parametrize('field', ['now', 'measurement_time', 'model_time', 'reference_time', 'speed', 'yaw_rate', 'desired_curvature'])
+@pytest.mark.parametrize('value', [math.nan, math.inf, -math.inf, None])
+def test_nonfinite_input_never_raises_or_leaks_into_diagnostics(field, value):
+  controller = FordModelActionController()
+  update(controller)
+  assert update(controller, **{field: value}) == FordPath()
+  assert controller.diagnostics['status'] == 'nonfinite'
+  json.dumps(controller.diagnostics, allow_nan=False)
+
+
+def test_repeated_measurements_do_not_freeze_slew_or_cache_invalid_model_geometry():
+  controller = FordModelActionController()
+  for i in range(10):
+    result = update(controller, 1.+i*.01, measurement_time=1., model_time=1., reference_time=1.)
+  assert result.path_offset == pytest.approx(.4)
+  assert result.path_angle == pytest.approx(.05)
+  broken = straight(.4)
+  broken.position.y[5] = math.nan
+  assert update(controller, 1.1, model=broken, model_time=1., measurement_time=1.) == FordPath()
+  assert controller.diagnostics['status'] == 'invalid_path'
+
+
+def test_yaw_offset_does_not_change_the_base():
+  controllers = [FordModelActionController() for _ in range(3)]
+  variants = [{}, {'yaw_rate': .0072}, {'yaw_rate': -.0072}]
+  for i in range(100):
+    outputs = [update(c, 1.+i*.01, **kwargs) for c, kwargs in zip(controllers, variants, strict=True)]
+    assert all(out == outputs[0] for out in outputs)
+  assert outputs[0].path_angle == pytest.approx(.2)
+
+
+def test_reference_source_can_change_to_an_older_but_fresh_publication():
+  controller = FordModelActionController()
+  update(controller, reference_time=.99)
+  assert update(controller, 1.01, reference_time=.98).valid
+
+
+def test_release_keeps_current_geometry_and_may_grow_c0_while_c1_decreases():
+  for sign in (-1., 1.):
+    controller = FordModelActionController()
+    for i in range(100):
+      before = update(controller, 1.+i*.01, model=circle(sign*.01), desired_curvature=sign*.005)
+    for i in range(100):
+      after = update(controller, 2.+i*.01, model=circle(sign*.02), desired_curvature=sign*.004)
+    assert abs(after.path_offset) > abs(before.path_offset)
+    assert abs(after.path_angle) < abs(before.path_angle)
+    for i in range(100):
+      released = update(controller, 3.+i*.01, model=circle(sign*.02), desired_curvature=0.)
+    assert released.path_offset == after.path_offset
+    assert released.path_angle == pytest.approx(0.)
+
+
+def _method(filename, class_name, method):
+  tree = ast.parse(filename.read_text())
+  cls = next(node for node in tree.body if isinstance(node, ast.ClassDef) and node.name == class_name)
+  return next(node for node in cls.body if isinstance(node, ast.FunctionDef) and node.name == method)
+
+
+@pytest.fixture
+def pipeline():
+  root = Path(__file__).resolve().parents[3]
+  controls_file = root/'selfdrive/controls/controlsd.py'
+  body = _method(controls_file, 'Controls', 'state_control').body
+  # Execute the actual source choice, upstream limiter and Ford integration.
+  selection = next(n for n in body if isinstance(n, ast.If) and ast.unparse(n.test) == "self.sm.valid['lateralManeuverPlan']")
+  limiter = next(n for n in body if isinstance(n, ast.Assign) and isinstance(n.value, ast.Call) and
+                 isinstance(n.value.func, ast.Name) and n.value.func.id == 'clip_curvature')
+  branch = next(n for n in body if isinstance(n, ast.If) and ast.unparse(n.test) == "self.CP.brand == 'ford'")
+  call = compile(ast.Module(body=[selection, limiter, branch], type_ignores=[]), str(controls_file), 'exec')
+  publication_file = root/'sunnypilot/selfdrive/controls/controlsd_ext.py'
+  body = _method(publication_file, 'ControlsExt', 'state_control_ext').body
+  publish = [n for n in body if (isinstance(n, ast.Assign) and ast.unparse(n.targets[0]) == 'ford_path') or
+             (isinstance(n, ast.If) and ast.unparse(n.test) == 'ford_path is not None')]
+  assert len(publish) == 2
+  publication = compile(ast.Module(body=publish, type_ignores=[]), str(publication_file), 'exec')
+  return call, publication
+
+
+class Subscriptions:
+  frame = 1
+
+  def __init__(self, maneuver):
+    self.valid = {'lateralManeuverPlan': maneuver, 'modelV2': True, 'carStateSP': True}
+    self.logMonoTime = {'carState': 995_000_000, 'modelV2': 980_000_000, 'lateralManeuverPlan': 990_000_000}
+    self.failed = set()
+    self.messages = {'carStateSP': custom.CarStateSP.new_message(), 'lateralManeuverPlan': SimpleNamespace(desiredCurvature=-.1)}
+
+  def __getitem__(self, service):
+    return self.messages[service]
+
+  def all_checks(self, services):
+    return not self.failed.intersection(services) and all(self.valid.get(s, True) for s in services)
+
+
+@pytest.mark.parametrize('maneuver', [False, True])
+@pytest.mark.parametrize('fingerprint', CANFD_CARS)
+def test_actual_controlsd_selection_limiting_publication_and_downstream_can(pipeline, maneuver, fingerprint):
+  call, publication = pipeline
+  sm = Subscriptions(maneuver)
+  controls = startup(car_params(carFingerprint=fingerprint))
+  controller = controls.ford_path_controller
+  controls.sm, controls.desired_curvature, controls.curvature = sm, 0., 0.
+  model = straight(.4)
+  model.action = SimpleNamespace(desiredCurvature=.1)
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=20., yawRate=-.0072, canValid=True, steeringPressed=False, steeringTorque=0.)
+  environment = {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model, 'lp': SimpleNamespace(roll=0.),
+                     'clip_curvature': clip_curvature, 'time': SimpleNamespace(monotonic=lambda: 1.)}
+  exec(call, environment)
+  expected_curvature = (-1 if maneuver else 1)*.000125
+  assert controls.desired_curvature == pytest.approx(expected_curvature)
+  assert controls.ford_path.path_angle == pytest.approx(20.*expected_curvature)
+  assert controls.ford_path.path_offset == pytest.approx(.04)
+  assert cc.latActive and cc.actuators.curvature == 0.
+  assert controller.diagnostics['reference_age'] == pytest.approx(.01 if maneuver else .02)
+
+  cp = structs.CarParams(flags=int(FordFlags.CANFD), carFingerprint=fingerprint)
+  downstream = CarController({Bus.pt: 'ford_lincoln_base_pt'}, cp, structs.CarParamsSP())
+  vehicle = SimpleNamespace(out=structs.CarState(vEgo=20., vEgoRaw=20.), acc_tja_status_stock_values=defaultdict(int),
+                            lkas_status_stock_values=defaultdict(int), buttons_stock_values=defaultdict(int))
+  parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], downstream.CAN.main)
+  for i, fail in enumerate((False, True)):
+    if fail:
+      sm.failed.add('modelV2')
+      exec(call, environment)
+      assert not cc.latActive and controls.ford_path == FordPath()
+    msg = custom.CarControlSP.new_message()
+    exec(publication, {'self': controls, 'CC_SP': msg})
+    _, packets = downstream.update(cc.as_reader(), convert_carControlSP(msg.as_reader()), vehicle, (i+1)*10_000_000)
+    parser.update([(i+1)*10_000_000, packets])
+    wire = parser.vl['LateralMotionControl2']
+    assert wire['LatCtlPathOffst_L_Actl'] == pytest.approx(-controls.ford_path.path_offset)
+    assert wire['LatCtlPath_An_Actl'] == pytest.approx(-controls.ford_path.path_angle)
+    assert wire['LatCtlCurv_No_Actl'] == wire['LatCtlCrv_NoRate2_Actl'] == 0.
+    assert wire['LatCtl_D2_Rq'] == (0 if fail else 2)
+
+
+@pytest.mark.parametrize('maneuver', [False, True])
+@pytest.mark.parametrize('failed', ['carState', 'modelV2', 'vehicleParameters', 'lateralManeuverPlan'])
+def test_actual_controlsd_service_gates(pipeline, maneuver, failed):
+  sm = Subscriptions(maneuver)
+  sm.failed.add(failed)
+  controls = startup()
+  controls.sm, controls.desired_curvature, controls.curvature = sm, 0., 0.
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=20., yawRate=0., canValid=True, steeringPressed=False, steeringTorque=0.)
+  model = straight()
+  model.action = SimpleNamespace(desiredCurvature=.1)
+  exec(pipeline[0], {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model, 'lp': SimpleNamespace(roll=0.),
+                         'clip_curvature': clip_curvature, 'time': SimpleNamespace(monotonic=lambda: 1.)})
+  assert controls.ford_path.valid == cc.latActive == (failed == 'lateralManeuverPlan' and not maneuver)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_feedback_through_actual_controlsd_publication_and_100hz_sender(pipeline, sign):
+  call, publication = pipeline
+  controls, sm = startup(), Subscriptions(False)
+  controls.sm, controls.desired_curvature = sm, sign*.004
+  model = straight(.4)
+  model.action = SimpleNamespace(desiredCurvature=sign*.004)
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=20., yawRate=.2, canValid=True, steeringPressed=False, steeringTorque=0.)
+  cp = structs.CarParams(flags=int(FordFlags.CANFD), carFingerprint='FORD_F_150_LIGHTNING_MK1')
+  downstream = CarController({Bus.pt: 'ford_lincoln_base_pt'}, cp, structs.CarParamsSP())
+  vehicle = SimpleNamespace(out=structs.CarState(vEgo=20., vEgoRaw=20.), acc_tja_status_stock_values=defaultdict(int),
+                            lkas_status_stock_values=defaultdict(int), buttons_stock_values=defaultdict(int))
+  parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], downstream.CAN.main)
+  frame = 0
+  for measured, torque, count, expected in [(sign*.004, 0., 100, 0.), (sign*.003, 0., 100, sign*.02),
+                                           (sign*.004, 0., 100, sign*.02), (sign*.005, 0., 100, 0.),
+                                           (sign*.003, 0., 100, sign*.02), (0., 1.0625, 5, 0.)]:
+    for _ in range(count):
+      now = 1.+frame*.01
+      controls.curvature, cs.steeringTorque = measured, torque
+      sm.logMonoTime.update(carState=round(now*1e9), modelV2=round(now*1e9))
+      environment = {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model,
+                     'lp': SimpleNamespace(roll=0.), 'clip_curvature': clip_curvature,
+                     'time': SimpleNamespace(monotonic=lambda now=now: now)}
+      exec(call, environment)
+      msg = custom.CarControlSP.new_message()
+      exec(publication, {'self': controls, 'CC_SP': msg})
+      _, packets = downstream.update(cc.as_reader(), convert_carControlSP(msg.as_reader()), vehicle, round(now*1e9))
+      received = parser.update([round(now*1e9), packets])
+      assert parser.dbc.name_to_msg['LateralMotionControl2'].address in received
+      wire = parser.vl['LateralMotionControl2']
+      assert wire['LatCtlPath_An_Actl'] == pytest.approx(-controls.ford_path.path_angle)
+      assert wire['LatCtlPathOffst_L_Actl'] == pytest.approx(-controls.ford_path.path_offset)
+      assert wire['LatCtlCurv_No_Actl'] == wire['LatCtlCrv_NoRate2_Actl'] == 0.
+      assert wire['LatCtl_D2_Rq'] == 2
+      assert wire['LatCtlPath_No_Cnt'] == frame % 16
+      address = parser.dbc.name_to_msg['LateralMotionControl2'].address
+      packet = next(packet for packet in packets if packet[0] == address)
+      assert wire['LatCtlPath_No_Cs'] == calculate_lat_ctl2_checksum(2, frame % 16, packet[1])
+      frame += 1
+    assert controls.ford_path_controller.core.correction == pytest.approx(expected)
+    assert controls.ford_path.path_angle == pytest.approx(sign*.08+expected)
+    assert controls.ford_path.path_offset == pytest.approx(.4)
+
+
+@pytest.mark.parametrize('service_valid', [False, True])
+def test_actual_controlsd_passes_only_valid_pscm_service_to_feedback(pipeline, service_valid):
+  controls, sm = startup(), Subscriptions(False)
+  controls.sm, controls.desired_curvature = sm, .004
+  model = straight(.4)
+  model.action = SimpleNamespace(desiredCurvature=.004)
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=20., yawRate=0., canValid=True, steeringPressed=False, steeringTorque=0.)
+  for frame in range(101):
+    now = 1.+frame*.01
+    controls.curvature = .004 if frame < 100 else .003
+    sm.logMonoTime.update(carState=round(now*1e9), modelV2=round(now*1e9))
+    sm.valid['carStateSP'] = service_valid
+    status = sm['carStateSP'].fordPscmStatus
+    status.valid, status.canMonoTime, status.limit, status.lateralState = True, round(now*1e9), 2, 2
+    exec(pipeline[0], {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model,
+                      'lp': SimpleNamespace(roll=0.), 'clip_curvature': clip_curvature,
+                      'time': SimpleNamespace(monotonic=lambda now=now: now)})
+  controller = controls.ford_path_controller
+  assert controller.diagnostics['pscm_limited'] is service_valid
+  assert controller.core.correction == pytest.approx(0. if service_valid else .0002)
+  assert cc.latActive and controls.ford_path.valid
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('maneuver', [False, True])
+def test_carryover_release_through_selected_limited_request_and_actual_can(pipeline, sign, maneuver):
+  call, publication = pipeline
+  controls, sm = startup(), Subscriptions(maneuver)
+  controls.sm, controls.desired_curvature = sm, sign*.004
+  core = controls.ford_path_controller.core
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=20., yawRate=0., canValid=True, steeringPressed=False, steeringTorque=0.)
+  cp = structs.CarParams(flags=int(FordFlags.CANFD), carFingerprint='FORD_F_150_LIGHTNING_MK1')
+  downstream = CarController({Bus.pt: 'ford_lincoln_base_pt'}, cp, structs.CarParamsSP())
+  vehicle = SimpleNamespace(out=structs.CarState(vEgo=20., vEgoRaw=20.), acc_tja_status_stock_values=defaultdict(int),
+                            lkas_status_stock_values=defaultdict(int), buttons_stock_values=defaultdict(int))
+  parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], downstream.CAN.main)
+  for frame in range(280):
+    now = 1.+frame*.01
+    desired = sign*(.004 if frame < 200 else -.001)
+    model = straight(sign*(.2 if frame < 200 else -.2))
+    model.action = SimpleNamespace(desiredCurvature=-desired if maneuver else desired)
+    sm.messages['lateralManeuverPlan'].desiredCurvature = desired
+    controls.curvature = sign*(.004 if frame < 100 else .001 if frame < 200 else .003)
+    sm.logMonoTime.update(carState=round(now*1e9), modelV2=round(now*1e9), lateralManeuverPlan=round(now*1e9))
+    before = core.c0, core.c1
+    exec(call, {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model,
+                'lp': SimpleNamespace(roll=0.), 'clip_curvature': clip_curvature,
+                'time': SimpleNamespace(monotonic=lambda now=now: now)})
+    assert abs(core.c0-before[0]) <= .0400000001 and abs(core.c1-before[1]) <= .0050000001
+    msg = custom.CarControlSP.new_message()
+    exec(publication, {'self': controls, 'CC_SP': msg})
+    _, packets = downstream.update(cc.as_reader(), convert_carControlSP(msg.as_reader()), vehicle, round(now*1e9))
+    received = parser.update([round(now*1e9), packets])
+    address = parser.dbc.name_to_msg['LateralMotionControl2'].address
+    assert address in received
+    wire = parser.vl['LateralMotionControl2']
+    assert wire['LatCtlPath_An_Actl'] == pytest.approx(-controls.ford_path.path_angle)
+    assert wire['LatCtlPathOffst_L_Actl'] == pytest.approx(-controls.ford_path.path_offset)
+    assert wire['LatCtlCurv_No_Actl'] == wire['LatCtlCrv_NoRate2_Actl'] == 0.
+    assert wire['LatCtl_D2_Rq'] == 2 and wire['LatCtlPath_No_Cnt'] == frame % 16
+    packet = next(packet for packet in packets if packet[0] == address)
+    assert wire['LatCtlPath_No_Cs'] == calculate_lat_ctl2_checksum(2, frame % 16, packet[1])
+    if frame == 199:
+      assert core.correction == pytest.approx(sign*.06)
+      assert core.carryover_release_count == 0
+  assert core.carryover_release_count == 1
+  assert controls.ford_path_controller.diagnostics['carryover_release_count'] == 1
+  assert controls.ford_path_controller.diagnostics['hypothesis'] == 'model-action-c1-feedback-v3'
+  assert sign*controls.ford_path.path_angle < 0.
+  assert controls.ford_path.path_offset == pytest.approx(-sign*.2)
+  controls.ford_path_controller.reset()
+  assert core.carryover_release_count == 0
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('fingerprint', CANFD_CARS)
+def test_heading_overflow_and_release_through_actual_can(pipeline, sign, fingerprint):
+  call, publication = pipeline
+  controls, sm = startup(car_params(carFingerprint=fingerprint)), Subscriptions(False)
+  controls.sm, controls.desired_curvature = sm, sign*.1
+  core = controls.ford_path_controller.core
+  model = straight(sign*.2)
+  cc = structs.CarControl(latActive=True)
+  cs = SimpleNamespace(vEgo=5., yawRate=0., canValid=True, steeringPressed=False, steeringTorque=0.)
+  cp = structs.CarParams(flags=int(FordFlags.CANFD), carFingerprint=fingerprint)
+  downstream = CarController({Bus.pt: 'ford_lincoln_base_pt'}, cp, structs.CarParamsSP())
+  vehicle = SimpleNamespace(out=structs.CarState(vEgo=5., vEgoRaw=5.), acc_tja_status_stock_values=defaultdict(int),
+                            lkas_status_stock_values=defaultdict(int), buttons_stock_values=defaultdict(int))
+  parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], downstream.CAN.main)
+  for frame in range(400):
+    now = 1.+frame*.01
+    desired = sign*(.1 if frame < 150 else .04)
+    model.action = SimpleNamespace(desiredCurvature=desired)
+    # Match the selected request after its real upstream limiter, isolating base allocation.
+    controls.curvature = clip_curvature(cs.vEgo, controls.desired_curvature, desired, 0.)[0]
+    sm.logMonoTime.update(carState=round(now*1e9), modelV2=round(now*1e9))
+    before = core.c0, core.c1
+    exec(call, {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model,
+                'lp': SimpleNamespace(roll=0.), 'clip_curvature': clip_curvature,
+                'time': SimpleNamespace(monotonic=lambda now=now: now)})
+    assert abs(core.c0-before[0]) <= .0400000001 and abs(core.c1-before[1]) <= .0050000001
+    assert core.correction == 0.
+    msg = custom.CarControlSP.new_message()
+    exec(publication, {'self': controls, 'CC_SP': msg})
+    _, packets = downstream.update(cc.as_reader(), convert_carControlSP(msg.as_reader()), vehicle, round(now*1e9))
+    received = parser.update([round(now*1e9), packets])
+    address = parser.dbc.name_to_msg['LateralMotionControl2'].address
+    assert address in received
+    wire = parser.vl['LateralMotionControl2']
+    assert wire['LatCtlPath_An_Actl'] == pytest.approx(-controls.ford_path.path_angle)
+    assert wire['LatCtlPathOffst_L_Actl'] == pytest.approx(-controls.ford_path.path_offset)
+    assert wire['LatCtlCurv_No_Actl'] == wire['LatCtlCrv_NoRate2_Actl'] == 0.
+    assert wire['LatCtl_D2_Rq'] == 2 and wire['LatCtlPath_No_Cnt'] == frame % 16
+    packet = next(packet for packet in packets if packet[0] == address)
+    assert wire['LatCtlPath_No_Cs'] == calculate_lat_ctl2_checksum(2, frame % 16, packet[1])
+    if frame == 149:
+      assert controls.desired_curvature == pytest.approx(sign*.1)
+      assert controls.ford_path.path_offset == pytest.approx(sign*1.6)
+      assert controls.ford_path.path_angle == pytest.approx(sign*.5)
+      assert controls.ford_path_controller.diagnostics['offset_overflow'] == pytest.approx(sign*1.4)
+  assert controls.ford_path.path_offset == pytest.approx(sign*.2)
+  assert controls.ford_path.path_angle == pytest.approx(sign*.28)
+  assert controls.ford_path_controller.diagnostics['offset_overflow'] == 0.
+
+
+@pytest.mark.parametrize('fingerprint', [*CANFD_CARS, CAR.FORD_ESCAPE_MK4])
+@pytest.mark.parametrize('observer', [False, True])
+def test_toggle_off_preserves_upstream_actuators_and_can(pipeline, fingerprint, observer):
+  call, publication = pipeline
+  settings = {'FordModelActionController': False, 'FordPscmObserver': observer}
+  flags = CAR(fingerprint).config.flags
+  controls = startup(car_params(carFingerprint=fingerprint, flags=flags), SimpleNamespace(get_bool=settings.__getitem__))
+  assert controls.ford_path_controller is None
+  sm = Subscriptions(False)
+  controls.sm, controls.desired_curvature, controls.curvature = sm, .004, 0.
+  # Missing custom model geometry must not inhibit the upstream actuator output.
+  model = SimpleNamespace(action=SimpleNamespace(desiredCurvature=.004))
+  cs = SimpleNamespace(vEgo=5., yawRate=0., canValid=True, steeringPressed=False, steeringTorque=0.)
+  cp = structs.CarParams(flags=int(flags), carFingerprint=fingerprint)
+  downstream = CarController({Bus.pt: 'ford_lincoln_base_pt'}, cp, structs.CarParamsSP())
+  vehicle = SimpleNamespace(out=structs.CarState(vEgo=5., vEgoRaw=5.), acc_tja_status_stock_values=defaultdict(int),
+                            lkas_status_stock_values=defaultdict(int), buttons_stock_values=defaultdict(int))
+  canfd = bool(flags & FordFlags.CANFD)
+  name = 'LateralMotionControl2' if canfd else 'LateralMotionControl'
+  parser = CANParser('ford_lincoln_base_pt', [(name, 20)], downstream.CAN.main)
+  address = parser.dbc.name_to_msg[name].address
+  sent = 0
+  for frame in range(300):
+    active = not 100 <= frame < 200
+    cc = structs.CarControl(latActive=active)
+    cc.actuators.curvature = -.003 if active else 0.  # Distinct from desired curvature; produced by LaC upstream.
+    before = cc.actuators.curvature
+    now = 1.+frame*.01
+    sm.logMonoTime.update(carState=round(now*1e9), modelV2=round(now*1e9))
+    exec(call, {'self': controls, 'CS': cs, 'CC': cc, 'actuators': cc.actuators, 'model_v2': model,
+                'lp': SimpleNamespace(roll=0.), 'clip_curvature': clip_curvature})
+    assert cc.actuators.curvature == before and cc.latActive == active
+    msg = custom.CarControlSP.new_message()
+    exec(publication, {'self': controls, 'CC_SP': msg})
+    assert not msg.fordLateralPath.enabled and not msg.fordLateralPath.valid
+    converted = convert_carControlSP(msg.as_reader())
+    assert not converted.fordLateralPath.enabled
+    _, packets = downstream.update(cc.as_reader(), converted, vehicle, round(now*1e9))
+    received = parser.update([round(now*1e9), packets])
+    assert (address in received) == (frame % CarControllerParams.STEER_STEP == 0)
+    if address in received:
+      sent += 1
+      wire = parser.vl[name]
+      assert wire['LatCtlPathOffst_L_Actl'] == wire['LatCtlPath_An_Actl'] == 0.
+      assert wire['LatCtlCrv_NoRate2_Actl' if canfd else 'LatCtlCurv_NoRate_Actl'] == 0.
+      assert wire['LatCtl_D2_Rq' if canfd else 'LatCtl_D_Rq'] == int(active)
+      assert wire['LatCtlRampType_D_Rq'] == 0
+      if canfd:
+        count = frame // CarControllerParams.STEER_STEP % 16
+        assert wire['LatCtlPath_No_Cnt'] == count
+        packet = next(packet for packet in packets if packet[0] == address)
+        assert wire['LatCtlPath_No_Cs'] == calculate_lat_ctl2_checksum(int(active), count, packet[1])
+      if frame in (95, 295):
+        assert wire['LatCtlCurv_No_Actl'] == pytest.approx(.003)
+      elif not active:
+        assert wire['LatCtlCurv_No_Actl'] == 0.
+  assert sent == 60

openpilot/selfdrive/controls/tests/test_ford_model_action_feedback.py

@@ -0,0 +1,290 @@
+"""C1 feedback behavior; these tests do not simulate a Ford steering plant."""
+import math
+from types import SimpleNamespace
+
+import pytest
+
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController, ModelActionController
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+from openpilot.selfdrive.controls.tests.test_ford_model_action import straight
+
+
+def tick(controller, desired, measured, **overrides):
+  kwargs = {'current_curvature': measured, 'speed': 20., 'dt': .01}
+  kwargs.update(overrides)
+  return controller.update(straight(.4), desired, **kwargs)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_old_turn_correction_does_not_keep_c1_in_old_direction_after_reversal(sign):
+  controller = ModelActionController()
+  # Build an actual correction through feedback, rather than injecting a state.
+  for _ in range(100):
+    controller.update(straight(), sign*.004, current_curvature=sign*.004, speed=20., dt=.01)
+  for _ in range(100):
+    controller.update(straight(), sign*.004, current_curvature=sign*.001, speed=20., dt=.01)
+  assert controller.correction == pytest.approx(sign*.06)
+  # The request has reversed, but measured steering still points into the old
+  # turn. C0 also confirms the new direction. The existing slew permits
+  # crossing zero within these 0.4 seconds.
+  for _ in range(40):
+    before = controller.c1
+    out = controller.update(straight(-sign*.2), -sign*.001, current_curvature=sign*.003, speed=20., dt=.01)
+    assert abs(controller.c1-before) <= .0050000001
+  assert sign*out.path_angle < 0., 'Stored old-turn correction still overrides the new C1 direction'
+  assert out.path_offset == pytest.approx(-sign*.2)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('limited', [False, True])
+def test_carryover_release_uses_fresh_feedback_and_preserves_final_slew(sign, limited):
+  controller = ModelActionController()
+  controller.c0, controller.c1, controller.correction = -sign*.2, sign*.03, sign*.05
+  kwargs = {'speed': 20., 'dt': .01, 'current_curvature': sign*.003, 'pscm_limited': limited}
+  controller.update(straight(-sign*.2), -sign*.001, feedback_dt=0., **kwargs)
+  assert controller.correction == pytest.approx(sign*.05)
+  before = controller.c1
+  out = controller.update(straight(-sign*.2), -sign*.001, **kwargs)
+  assert controller.correction == 0.
+  assert controller.carryover_release_count == 1
+  assert out.path_angle == pytest.approx(before-sign*.005)
+  for _ in range(30):
+    controller.update(straight(-sign*.2), -sign*.001, **kwargs)
+  assert controller.carryover_release_count == 1
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('case', ['matched', 'same_turn', 'already_turning_new_way', 'c0_opposes', 'c0_neutral',
+                                  'c0_sub_resolution', 'target_c0_opposes', 'c1_sub_resolution',
+                                  'neutral_request', 'neutral_measurement', 'correction_helps', 'correction_not_dominant'])
+def test_carryover_release_preserves_steady_correction_and_ambiguous_requests(sign, case):
+  controller = ModelActionController()
+  offset, desired, measured, correction = -.2, -.001, .003, .05
+  if case == 'matched':
+    measured = desired
+  elif case == 'same_turn':
+    measured = -.0005
+  elif case == 'already_turning_new_way':
+    measured = -.003
+  elif case == 'c0_opposes':
+    offset = .2
+  elif case == 'c0_neutral':
+    offset = 0.
+  elif case == 'c0_sub_resolution':
+    offset = -.001
+  elif case == 'c1_sub_resolution':
+    desired = -.000001
+  elif case == 'neutral_request':
+    desired = 0.
+  elif case == 'neutral_measurement':
+    measured = 0.
+  elif case == 'correction_helps':
+    correction = -.05
+  elif case == 'correction_not_dominant':
+    correction = .01
+  controller.c0, controller.c1, controller.correction = sign*offset, sign*(20.*desired+correction), sign*correction
+  if case == 'target_c0_opposes':
+    offset = .2  # The old slewed C0 alone is not enough to confirm the request.
+  controller.update(straight(sign*offset), sign*desired, current_curvature=sign*measured, speed=20., dt=.01)
+  assert controller.carryover_release_count == 0
+  assert abs(controller.correction-sign*correction) <= abs(desired-measured)*20.*.01+1e-10
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_carryover_release_waits_for_c0_to_finish_opposing_the_new_request(sign):
+  controller = ModelActionController()
+  controller.c0, controller.c1, controller.correction = sign*.2, sign*.03, sign*.05
+  for _ in range(4):
+    controller.update(straight(-sign*.2), -sign*.001, current_curvature=sign*.003, speed=20., dt=.01)
+    assert controller.carryover_release_count == 0
+  for _ in range(3):
+    controller.update(straight(-sign*.2), -sign*.001, current_curvature=sign*.003, speed=20., dt=.01)
+  assert controller.carryover_release_count == 1
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_steady_opposing_correction_is_preserved_through_small_error_crossings(sign):
+  controller = ModelActionController()
+  controller.c0, controller.c1, controller.correction = -sign*.2, sign*.03, sign*.05
+  for i in range(200):
+    measured = sign*(-.001+(-1 if i % 2 else 1)*.000001)
+    controller.update(straight(-sign*.2), -sign*.001, current_curvature=measured, speed=20., dt=.01)
+  assert controller.carryover_release_count == 0
+  assert controller.correction == pytest.approx(sign*.05)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('offset', [.009999, .01, .010001])
+@pytest.mark.parametrize('heading', [.0004999, .0005, .0005001])
+def test_carryover_direction_confirmation_uses_existing_dbc_steps(sign, offset, heading):
+  controller = ModelActionController()
+  controller.c0, controller.c1, controller.correction = -sign*offset, sign*.03, sign*.05
+  controller.update(straight(-sign*offset), -sign*heading/20., current_curvature=sign*.003, speed=20., dt=.01)
+  assert controller.carryover_release_count == int(offset >= .01 and heading >= .0005)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_feedback_builds_holds_and_unwinds_without_changing_c0(sign):
+  controller, matched = ModelActionController(), ModelActionController()
+  for _ in range(100):
+    tick(controller, sign*.004, sign*.004)
+  for _ in range(100):
+    out = tick(controller, sign*.004, sign*.003)
+    baseline = tick(matched, sign*.004, sign*.004)
+  assert controller.correction == pytest.approx(sign*.02)
+  assert out.path_angle == pytest.approx(sign*.1)
+  assert out.path_offset == baseline.path_offset == pytest.approx(.4)
+  for _ in range(100):
+    out = tick(controller, sign*.004, sign*.004)
+  assert controller.correction == pytest.approx(sign*.02)
+  assert out.path_angle == pytest.approx(sign*.1)
+  for _ in range(200):
+    out = tick(controller, sign*.004, sign*.005)
+  assert controller.correction == pytest.approx(-sign*.02)
+  assert out.path_angle == pytest.approx(sign*.06)
+  assert out.curvature == out.curvature_rate == 0.
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_amplitude_and_slew_limits_do_not_store_unavailable_feedback(sign):
+  controller = ModelActionController()
+  # The unchanged model request is already ahead of the output slew.
+  for _ in range(10):
+    tick(controller, sign*.01, 0.)
+    assert controller.correction == 0.
+  for _ in range(1000):
+    before = controller.c1
+    tick(controller, sign*.01, -sign*.9)
+    assert abs(controller.c1-before) <= .0050000001
+    assert abs(controller.correction) <= .3000000001
+  assert controller.c1 == pytest.approx(sign*.5)
+  assert controller.correction == pytest.approx(sign*.3)
+  for _ in range(200):
+    tick(controller, sign*.01, 0.)
+  assert controller.correction == pytest.approx(sign*.3)
+  tick(controller, sign*.01, sign*.02)
+  assert sign*controller.correction < .3  # Unwind is allowed at the cap.
+  assert sign*controller.c1 < .5
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_pscm_limit_only_blocks_feedback_further_into_measured_turn(sign):
+  controller = ModelActionController()
+  for _ in range(100):
+    tick(controller, sign*.004, sign*.004)
+  for _ in range(100):
+    tick(controller, sign*.004, sign*.003, pscm_limited=True)
+  assert controller.correction == 0.
+  out = tick(controller, sign*.004, sign*.005, pscm_limited=True)
+  assert sign*controller.correction < 0.
+  # A limit cannot stall the new model request itself or its unwind slew.
+  for _ in range(100):
+    out = tick(controller, 0., 0., pscm_limited=True)
+  assert abs(out.path_angle) < .001
+  assert out.path_offset == pytest.approx(.4)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_pscm_limit_cannot_trap_old_correction_below_the_model_request(sign):
+  controller = ModelActionController()
+  controller.correction = -sign*.02
+  controller.c1 = sign*.06
+  for _ in range(200):
+    out = tick(controller, sign*.004, sign*.003, pscm_limited=True)
+  assert controller.correction == pytest.approx(0.)
+  assert out.path_angle == pytest.approx(sign*.08)
+
+
+def test_driver_intervention_clears_feedback_through_existing_output_slew():
+  controller = ModelActionController()
+  for _ in range(100):
+    tick(controller, .004, .004)
+  for _ in range(100):
+    tick(controller, .004, .003)
+  assert controller.correction > 0.
+  previous = controller.c1
+  tick(controller, .004, -.01, feedback_enabled=False)
+  assert controller.correction == 0.
+  assert abs(controller.c1-previous) <= .0050000001
+  for _ in range(100):
+    out = tick(controller, .004, -.01, feedback_enabled=False)
+  assert controller.correction == 0.
+  assert out.path_angle == pytest.approx(.08)
+
+
+@pytest.mark.parametrize('field,value', [('current_curvature', math.nan), ('current_curvature', None),
+                                       ('current_curvature', 1.01), ('feedback_dt', math.nan),
+                                       ('feedback_dt', -.001), ('feedback_dt', .151), ('active', False)])
+def test_bad_feedback_inputs_and_disengagement_clear_every_control_state(field, value):
+  controller = ModelActionController()
+  controller.correction = .03
+  out = tick(controller, .004, .003, **{field: value})
+  assert out == FordPath()
+  assert (controller.c0, controller.c1, controller.correction) == (0., 0., 0.)
+
+
+def adapter_tick(controller, now, **overrides):
+  kwargs = {'current_curvature': .003, 'speed': 20., 'yaw_rate': 0., 'now': now,
+            'measurement_time': now, 'model_time': now, 'reference_time': now, 'active': True}
+  kwargs.update(overrides)
+  return controller.update(straight(.4), .004, **kwargs)
+
+
+def status(now, **overrides):
+  fields = {'valid': True, 'canMonoTime': round(now*1e9), 'limit': 0, 'lateralState': 2, 'denied': False}
+  fields.update(overrides)
+  return SimpleNamespace(**fields)
+
+
+def test_repeated_steering_samples_only_advance_output_slew():
+  controller = FordModelActionController()
+  for i in range(100):
+    adapter_tick(controller, 1.+i*.01, current_curvature=.004)
+  before = controller.core.correction
+  for i in range(1, 6):
+    adapter_tick(controller, 1.99+i*.01, measurement_time=1.99)
+    assert controller.core.correction == before
+  adapter_tick(controller, 2.05)
+  assert controller.core.correction == pytest.approx(.02*.06)
+  assert controller.diagnostics['feedback_dt'] == pytest.approx(.06)
+
+
+@pytest.mark.parametrize('overrides', [{'driver_pressed': True}, {'driver_torque': 1.01},
+                                     {'driver_torque': -1.01}, {'driver_torque': math.nan},
+                                     {'pscm_status': status(2.01, limit=3)},
+                                     {'pscm_status': status(2.01, denied=True)},
+                                     {'pscm_status': status(2.01, lateralState=1)}])
+def test_adapter_clears_feedback_when_driver_or_pscm_overrides(overrides):
+  controller = FordModelActionController()
+  for i in range(101):
+    adapter_tick(controller, 1.+i*.01)
+  assert controller.core.correction > 0.
+  assert adapter_tick(controller, 2.01, **overrides).valid
+  assert controller.core.correction == 0.
+  assert not controller.diagnostics['feedback_enabled']
+
+
+@pytest.mark.parametrize('overrides,limited', [({}, True), ({'valid': False}, False),
+                                            ({'canMonoTime': 0}, False), ({'canMonoTime': 1_800_000_000}, False),
+                                            ({'canMonoTime': 2_020_000_000}, False), ({'limit': 1}, False)])
+def test_only_fresh_reached_pscm_limit_blocks_outward_integration(overrides, limited):
+  controller = FordModelActionController()
+  for i in range(100):
+    adapter_tick(controller, 1.+i*.01, current_curvature=.004)
+  adapter_tick(controller, 2., pscm_status=status(2., **{'limit': 2, **overrides}))
+  assert controller.diagnostics['pscm_limited'] is limited
+  assert (controller.core.correction == 0.) is limited
+
+
+def test_measurement_cadence_preserves_elapsed_distance_integration():
+  results = []
+  for period in (1, 2, 5):
+    controller = FordModelActionController()
+    for i in range(101):
+      now = 1.+i*.01
+      adapter_tick(controller, now, current_curvature=.004)
+    for i in range(1, 101):
+      now = 2.+i*.01
+      adapter_tick(controller, now, measurement_time=2.+(i//period)*period*.01)
+    results.append(controller.core.correction)
+  assert results == pytest.approx([.02, .02, .02])

openpilot/selfdrive/controls/tests/test_ford_model_action_overflow.py

@@ -0,0 +1,90 @@
+"""C1 overflow allocation and release; no assumptions about PSCM response."""
+import pytest
+
+from openpilot.selfdrive.controls.lib.ford_model_action import ModelActionController
+from openpilot.selfdrive.controls.tests.test_ford_model_action import make_model, straight
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('speed', [3., 7., 20., 55.])
+@pytest.mark.parametrize('heading,offset', [(.4, .2), (.5, .2), (.6, .9), (.8, 2.3)])
+def test_clipped_base_heading_preserves_the_seven_metre_reference(sign, speed, heading, offset):
+  controller = ModelActionController()
+  desired = sign*heading/max(7., speed)
+  for _ in range(150):
+    out = controller.update(straight(sign*.2), desired, current_curvature=desired, speed=speed, dt=.01)
+  assert controller.correction == 0.
+  assert out.path_offset == pytest.approx(sign*offset)
+  assert out.path_angle == pytest.approx(sign*min(heading, .5))
+  assert out.path_offset+7.*out.path_angle == pytest.approx(sign*(.2+7.*heading))
+  assert out.curvature == out.curvature_rate == 0.
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_combined_offset_is_clipped_after_allocating_heading(sign):
+  controller = ModelActionController()
+  for _ in range(200):
+    out = controller.update(straight(sign*4.), sign*.1, current_curvature=sign*.1, speed=7., dt=.01)
+  assert out.path_offset == pytest.approx(sign*5.11)
+  assert out.path_angle == pytest.approx(sign*.5)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_overflow_uses_existing_reference_with_short_model_path(sign):
+  controller = ModelActionController()
+  model = make_model([0., 1.], [0., sign*.2], [0., 0.])
+  for _ in range(150):
+    out = controller.update(model, sign*.03, current_curvature=sign*.03, speed=20., dt=.01)
+  assert out.path_offset == pytest.approx(sign*.9)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_extra_offset_releases_at_existing_slew_without_stored_overflow(sign):
+  controller = ModelActionController()
+  for _ in range(200):
+    controller.update(straight(sign*.2), sign*.04, current_curvature=sign*.04, speed=20., dt=.01)
+  assert controller.c0 == pytest.approx(sign*2.3)
+  for i in range(60):
+    before = controller.c0
+    out = controller.update(straight(sign*.2), sign*.02, current_curvature=sign*.02, speed=20., dt=.01)
+    assert sign*controller.c0 >= .2-1e-10
+    assert sign*controller.c0 <= sign*before+1e-10
+    assert abs(controller.c0-before) <= .04+1e-10
+    if i == 0:
+      assert controller.c0 == pytest.approx(sign*2.26)
+  assert out.path_offset == pytest.approx(sign*.2)
+  assert out.path_angle == pytest.approx(sign*.4)
+  assert controller.correction == 0.
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_c1_feedback_saturation_does_not_spill_correction_into_c0(sign):
+  controller = ModelActionController()
+  for _ in range(200):
+    out = controller.update(straight(sign*.2), sign*.02, current_curvature=0., speed=20., dt=.01)
+  assert out.path_angle == pytest.approx(sign*.5)
+  assert controller.correction == pytest.approx(sign*.1)
+  assert out.path_offset == pytest.approx(sign*.2)
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+@pytest.mark.parametrize('enabled,limited', [(False, False), (True, True)])
+def test_overflow_is_base_geometry_with_existing_feedback_gates(sign, enabled, limited):
+  controller = ModelActionController()
+  for _ in range(150):
+    out = controller.update(straight(sign*.2), sign*.03, current_curvature=sign*.02, speed=20., dt=.01,
+                            feedback_enabled=enabled, pscm_limited=limited)
+  assert out.path_offset == pytest.approx(sign*.9)
+  assert out.path_angle == pytest.approx(sign*.5)
+  assert controller.correction == 0.
+
+
+@pytest.mark.parametrize('sign', [-1., 1.])
+def test_overflow_cannot_replace_model_centering_confirmation_for_carryover_release(sign):
+  controller = ModelActionController()
+  controller.c0, controller.c1, controller.correction = sign*.6, -sign*.1, -sign*.6
+  for _ in range(20):
+    controller.update(straight(-sign*.1), sign*.03, current_curvature=-sign*.002, speed=20., dt=.01)
+  assert sign*controller.c0 > 0.  # Overflow agrees with heading; model centering still opposes it.
+  assert controller.carryover_release_count == 0
+  assert sign*controller.correction < -.4

openpilot/selfdrive/controls/tests/test_ford_model_action_selection.py

@@ -0,0 +1,110 @@
+"""Exercise real startup selection and Sunnylink writes without starting hardware."""
+import ast
+import base64
+import itertools
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+from opendbc.car.ford.values import CAR, FordFlags
+from openpilot.common.params import Params, ParamKeyFlag, ParamKeyType
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController, select_model_action_controller
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+
+
+CANFD_CARS = [car for car in CAR if car.config.flags & FordFlags.CANFD]
+
+
+def car_params(**overrides):
+  return SimpleNamespace(**({'brand': 'ford', 'flags': FordFlags.CANFD, 'carFingerprint': 'FORD_F_150_LIGHTNING_MK1',
+                             'carFw': []} | overrides))
+
+
+def startup(cp=None, params=None):
+  filename = Path(__file__).resolve().parents[1]/'controlsd.py'
+  tree = ast.parse(filename.read_text())
+  cls = next(n for n in tree.body if isinstance(n, ast.ClassDef) and n.name == 'Controls')
+  body = next(n for n in cls.body if isinstance(n, ast.FunctionDef) and n.name == '__init__').body
+  start = next(i for i, n in enumerate(body) if isinstance(n, ast.Assign) and ast.unparse(n.targets[0]) == 'self.ford_path_controller')
+  end = next(i for i, n in enumerate(body) if isinstance(n, ast.Assign) and ast.unparse(n.targets[0]) == 'self.ford_path')
+  if params is None:
+    params = SimpleNamespace(get_bool=lambda key: key == 'FordModelActionController')
+  controls = SimpleNamespace(CP=cp or car_params(), params=params)
+  environment = {'self': controls, 'FordFlags': FordFlags, 'FordPath': FordPath,
+                 'FordModelActionController': FordModelActionController,
+                 'select_model_action_controller': select_model_action_controller,
+                 'cloudlog': SimpleNamespace(event=lambda *args, **kwargs: None)}
+  exec(compile(ast.Module(body=body[start:end+1], type_ignores=[]), str(filename), 'exec'), environment)
+  return controls
+
+
+@pytest.mark.parametrize('candidate,observer', list(itertools.product((False, True), repeat=2)))
+@pytest.mark.parametrize('fingerprint', [*CANFD_CARS, 'FORD_FUTURE_CANFD'])
+def test_actual_startup_priority(candidate, observer, fingerprint):
+  settings = {'FordModelActionController': candidate, 'FordPscmObserver': observer}
+  selected = startup(car_params(carFingerprint=fingerprint), params=SimpleNamespace(get_bool=settings.__getitem__))
+  if candidate:
+    assert type(selected.ford_path_controller) is FordModelActionController
+  else:
+    assert selected.ford_path_controller is None
+  assert selected.ford_model_action == candidate
+  assert selected.ford_path == FordPath()
+
+
+@pytest.mark.parametrize('overrides', [{'brand': 'tesla'}, {'flags': 0}, {'flags': 8}])
+@pytest.mark.parametrize('observer', [False, True])
+def test_other_vehicles_always_use_upstream(overrides, observer):
+  settings = {'FordModelActionController': False, 'FordPscmObserver': observer}
+  params = SimpleNamespace(get_bool=settings.__getitem__)
+  before = startup(car_params(**overrides), params)
+  settings['FordModelActionController'] = True
+  after = startup(car_params(**overrides), params)
+  assert after.ford_path_controller is before.ford_path_controller is None
+  assert not after.ford_model_action
+
+
+@pytest.mark.parametrize('firmware', [[], [SimpleNamespace(ecu='eps', fwVersion=b'other')]])
+def test_candidate_does_not_depend_on_eps_firmware_query(firmware):
+  assert isinstance(startup(car_params(carFw=firmware)).ford_path_controller, FordModelActionController)
+
+
+def test_candidate_accepts_canfd_with_additional_flags():
+  assert isinstance(startup(car_params(flags=FordFlags.CANFD | 8)).ford_path_controller, FordModelActionController)
+
+
+@pytest.mark.parametrize('observer', [False, True])
+@pytest.mark.parametrize('fingerprint', CANFD_CARS)
+def test_sunnylink_write_takes_effect_on_restart_and_restores_upstream(tmp_path, monkeypatch, observer, fingerprint):
+  from openpilot.sunnypilot.sunnylink import utils
+
+  params = Params(str(tmp_path))
+  monkeypatch.setattr(utils, 'Params', lambda: params)
+  assert params.get_default_value('FordModelActionController') is False
+  assert params.get_type('FordModelActionController') == ParamKeyType.BOOL
+  assert b'FordModelActionController' in params.all_keys(ParamKeyFlag.PERSISTENT)
+  assert b'FordModelActionController' in params.all_keys(ParamKeyFlag.BACKUP)
+  params.put_bool('FordPscmObserver', observer, block=True)
+  cp = car_params(carFingerprint=fingerprint)
+  old = startup(cp, params=params)
+  assert old.ford_path_controller is None
+  utils.save_param_from_base64_encoded_string('FordModelActionController', base64.b64encode(b'true').decode())
+  enabled = startup(cp, params=params)
+  assert isinstance(enabled.ford_path_controller, FordModelActionController)
+  assert not isinstance(old.ford_path_controller, FordModelActionController)
+  utils.save_param_from_base64_encoded_string('FordModelActionController', base64.b64encode(b'false').decode())
+  assert isinstance(enabled.ford_path_controller, FordModelActionController)
+  assert startup(cp, params=params).ford_path_controller is None
+  assert params.get_bool('FordPscmObserver') == observer
+
+
+def test_stored_retired_toggle_cannot_enable_the_candidate(tmp_path):
+  params = Params(str(tmp_path))
+  Path(params.get_param_path('FordVirtualAngleController')).write_text('1')
+  assert b'FordVirtualAngleController' not in params.all_keys()
+  assert params.get_bool('FordModelActionController') is False
+  assert startup(params=params).ford_path_controller is None
+  params.put_bool('FordModelActionController', True, block=True)
+  params.clear_all(ParamKeyFlag.CLEAR_ON_MANAGER_START)
+  assert not Path(params.get_param_path('FordVirtualAngleController')).exists()
+  assert params.get_bool('FordModelActionController') is True

openpilot/selfdrive/controls/tests/test_ford_path.py

@@ -0,0 +1,422 @@
+import math
+from types import SimpleNamespace
+
+import numpy as np
+
+from openpilot.cereal import custom
+from openpilot.selfdrive.car.helpers import convert_carControlSP
+from openpilot.selfdrive.controls.lib.ford_path import (DBC_ANGLE, DBC_CURVATURE, DBC_OFFSET, FordPath, FordPathController,
+                                                        FordPscmObserver, FordPscmObserverPathController, FordPscmState,
+                                                        _bounded_feedback, _encode_path, _model_path, _predicted_pose,
+                                                        _pscm_contributions, _relative_pose)
+
+
+def _path(curvature: float, speed: float = 8.0):
+  t = np.linspace(0.0, 3.0, 61)
+  distance = speed * t
+  heading = curvature * distance
+  x = np.zeros_like(distance)
+  y = np.zeros_like(distance)
+  for i in range(1, len(distance)):
+    ds = distance[i] - distance[i - 1]
+    average_heading = 0.5 * (heading[i] + heading[i - 1])
+    x[i] = x[i - 1] + ds * math.cos(average_heading)
+    y[i] = y[i - 1] + ds * math.sin(average_heading)
+  return SimpleNamespace(
+    position=SimpleNamespace(t=t.tolist(), x=x.tolist(), y=y.tolist()),
+    orientation=SimpleNamespace(z=heading.tolist()),
+  )
+
+
+def _changing_path(start_curvature: float, end_curvature: float, speed: float = 8.0):
+  t = np.linspace(0.0, 3.0, 61)
+  distance = speed * t
+  curvature = np.interp(distance, [distance[0], min(distance[-1], 7.0)], [start_curvature, end_curvature])
+  heading = np.zeros_like(distance)
+  x = np.zeros_like(distance)
+  y = np.zeros_like(distance)
+  for i in range(1, len(distance)):
+    ds = distance[i] - distance[i - 1]
+    heading[i] = heading[i - 1] + 0.5 * (curvature[i] + curvature[i - 1]) * ds
+    average_heading = 0.5 * (heading[i] + heading[i - 1])
+    x[i] = x[i - 1] + ds * math.cos(average_heading)
+    y[i] = y[i - 1] + ds * math.sin(average_heading)
+  return SimpleNamespace(
+    position=SimpleNamespace(t=t.tolist(), x=x.tolist(), y=y.tolist()),
+    orientation=SimpleNamespace(z=heading.tolist()),
+  )
+
+
+def _command(model, desired_curvature: float, *, current_curvature: float = 0.0, v_ego: float = 8.0):
+  return FordPathController(dt=1.0).update(model, desired_curvature, current_curvature=current_curvature, v_ego=v_ego)
+
+
+def _equivalent_curvature(command) -> float:
+  return 2.0 * command.path_offset / 7.0 ** 2 + 2.0 * command.path_angle / 7.0 + command.curvature
+
+
+def test_gentle_path_uses_only_c2():
+  command = _command(_path(0.004, speed=20.0), 0.004, current_curvature=0.004, v_ego=20.0)
+  assert command.valid
+  assert command.path_offset == 0.0
+  assert command.path_angle == 0.0
+  assert np.isclose(command.curvature, 0.004, atol=1e-6)
+  assert command.curvature_rate == 0.0
+
+
+def test_gentle_path_uses_only_c2_when_model_and_action_disagree():
+  command = _command(_path(0.005), 0.002, current_curvature=0.005)
+  assert command.path_offset == 0.0
+  assert command.path_angle == 0.0
+  assert np.isclose(command.curvature, 0.002, atol=1e-6)
+
+
+def test_spatially_growing_path_adds_fast_pose_before_action_becomes_large():
+  controller = FordPathController(dt=1.0)
+  command = controller.update(_changing_path(0.0, 0.04), 0.012, current_curvature=0.0, v_ego=8.0)
+  assert command.path_offset > 0.0
+  assert command.path_angle > 0.0
+  assert command.curvature < 0.012
+  assert command.curvature_rate == 0.0
+
+
+def test_growing_model_pose_adds_authority_but_c3_is_never_transmitted():
+  constant = _command(_path(0.012), 0.012)
+  growing = _command(_changing_path(0.0, 0.04), 0.012)
+  assert _equivalent_curvature(growing) > _equivalent_curvature(constant)
+  assert constant.curvature_rate == 0.0
+  assert growing.curvature_rate == 0.0
+
+
+def test_local_tracking_error_corrects_without_replacing_forward_pose():
+  model = _changing_path(0.0, 0.04)
+  local_curvature = 0.5 * 0.04 * 2.0 / 7.0
+  aligned = _command(model, 0.012, current_curvature=local_curvature)
+  under = _command(model, 0.012, current_curvature=0.0)
+  assert aligned.path_offset > 0.0
+  assert aligned.path_angle > 0.0
+  assert under.path_offset > aligned.path_offset
+  assert under.path_angle > aligned.path_angle
+
+
+def test_large_maneuver_uses_fast_pose_and_zeros_c2():
+  command = _command(_path(0.04), 0.04)
+  assert command.path_offset > 0.5
+  assert command.path_angle > 0.2
+  assert command.curvature == 0.0
+  assert command.curvature_rate == 0.0
+
+
+def test_model_pose_can_trigger_maneuver_when_action_is_late():
+  command = _command(_path(0.04), 0.002)
+  assert command.path_offset > 0.5
+  assert command.path_angle > 0.2
+  assert command.curvature == 0.0
+
+
+def test_gentle_model_pose_does_not_replace_a_collapsed_action():
+  command = _command(_path(0.005), 0.0, current_curvature=0.005)
+  assert command.path_offset == 0.0
+  assert command.path_angle == 0.0
+  assert command.curvature == 0.0
+
+
+def test_changing_gentle_curve_keeps_upstream_strength_c2():
+  command = _command(_changing_path(0.0, 0.008), 0.004, current_curvature=0.0)
+  assert np.isclose(command.curvature, 0.004)
+  assert command.path_offset == 0.0
+  assert command.path_angle == 0.0
+
+
+def test_action_only_maneuver_cannot_invent_large_model_pose():
+  command = _command(_path(0.002), 0.04)
+  assert 0.0 < command.path_offset < 0.1
+  assert 0.0 < command.path_angle < 0.03
+  assert command.curvature == 0.0
+
+
+def test_nearby_demands_blend_continuously_without_a_mode_threshold():
+  low = _command(_path(0.0119), 0.0119)
+  high = _command(_path(0.0121), 0.0121)
+  assert abs(high.path_offset - low.path_offset) < 0.05
+  assert abs(high.path_angle - low.path_angle) < 0.03
+  assert abs(high.curvature - low.curvature) < 0.001
+
+
+def test_leaving_c2_normal_band_does_not_drop_total_authority():
+  normal = _command(_path(0.006), 0.006)
+  transition = _command(_path(0.0061), 0.0061)
+  assert transition.curvature <= normal.curvature
+  assert _equivalent_curvature(transition) >= _equivalent_curvature(normal)
+
+
+def test_low_speed_still_uses_available_model_pose():
+  command = _command(_path(0.04, speed=2.0), 0.04, v_ego=2.0)
+  assert command.path_offset > 0.0
+  assert command.path_angle > 0.0
+
+
+def test_higher_speed_advances_predicted_pose_and_extends_heading_horizon():
+  model = _changing_path(0.0, 0.015, speed=20.0)
+  slow = _command(model, 0.012, v_ego=7.0)
+  fast = _command(model, 0.012, v_ego=20.0)
+  assert fast.path_offset > slow.path_offset
+  assert fast.path_angle > slow.path_angle
+
+
+def test_short_model_uses_available_endpoint():
+  model = _path(0.04, speed=1.0)
+  command = _command(model, 0.04, v_ego=1.0)
+  assert command.valid
+  assert command.path_offset > 0.0
+  assert command.path_angle > 0.0
+
+
+def test_turn_entry_coordinates_c2_release_with_fast_pose_attack():
+  controller = FordPathController(dt=0.01)
+  for _ in range(20):
+    assert controller.update(_path(0.004), 0.004, v_ego=8.0).curvature > 0.0
+  outputs = [controller.update(_path(0.04), 0.04, current_curvature=0.01, v_ego=8.0) for _ in range(100)]
+  assert 0.0 < outputs[0].curvature < 0.004
+  assert outputs[0].path_offset > 0.0
+  assert outputs[0].path_angle > 0.0
+  assert outputs[-1].curvature == 0.0
+
+
+def test_turn_exit_allows_c2_to_take_over_while_fast_pose_drains():
+  controller = FordPathController(dt=0.01)
+  for _ in range(20):
+    controller.update(_path(0.04), 0.04, current_curvature=0.02, v_ego=8.0)
+  outputs = [controller.update(_path(0.004), 0.004, current_curvature=0.004, v_ego=8.0) for _ in range(100)]
+  assert 0.0 < outputs[0].curvature < 0.004
+  assert outputs[0].path_offset != 0.0 or outputs[0].path_angle != 0.0
+  assert outputs[-1].path_offset == 0.0
+  assert outputs[-1].path_angle == 0.0
+
+
+def test_100hz_handoff_preserves_total_authority_without_entry_drop_or_exit_overshoot():
+  controller = FordPathController(dt=0.01)
+  normal = controller.update(_path(0.006), 0.006, current_curvature=0.006, v_ego=8.0)
+  entries = [controller.update(_path(0.04), 0.04, current_curvature=0.01, v_ego=8.0) for _ in range(100)]
+  entry_authority = np.asarray([_equivalent_curvature(command) for command in entries])
+  assert np.all(np.diff(entry_authority) >= -1e-9)
+  assert entry_authority[0] >= _equivalent_curvature(normal)
+
+  exits = [controller.update(_path(0.004), 0.004, current_curvature=0.004, v_ego=8.0) for _ in range(100)]
+  exit_authority = np.asarray([_equivalent_curvature(command) for command in exits])
+  assert np.all(np.diff(exit_authority) <= 1e-9)
+  assert np.all(exit_authority >= 0.004 - 1e-9)
+
+
+def test_measured_tracking_error_closes_bidirectionally_without_abandoning_the_turn():
+  model = _path(0.04)
+  under = _command(model, 0.04, current_curvature=0.005)
+  on_target = _command(model, 0.04, current_curvature=0.04)
+  over = _command(model, 0.04, current_curvature=0.05)
+  assert under.path_offset > on_target.path_offset
+  assert under.path_angle > on_target.path_angle
+  assert 0.0 < over.path_offset < on_target.path_offset
+  assert 0.0 < over.path_angle < on_target.path_angle
+
+
+def test_gentle_curve_does_not_add_fast_tracking_trim():
+  model = _path(0.004)
+  under = _command(model, 0.004, current_curvature=0.002)
+  on_target = _command(model, 0.004, current_curvature=0.004)
+  over = _command(model, 0.004, current_curvature=0.006)
+  assert under.path_offset == on_target.path_offset == over.path_offset == 0.0
+  assert under.path_angle == on_target.path_angle == over.path_angle == 0.0
+  assert np.allclose([under.curvature, on_target.curvature, over.curvature], 0.004, atol=2e-6)
+
+
+def test_overshoot_trim_cannot_erase_a_modeled_turn():
+  model = _path(0.04)
+  on_target = _command(model, 0.04, current_curvature=0.04)
+  over = _command(model, 0.04, current_curvature=0.06)
+  assert over.path_offset > 0.95 * on_target.path_offset
+  assert over.path_angle > 0.9 * on_target.path_angle
+
+
+def test_corrupt_measured_curvature_cannot_reverse_a_modeled_turn():
+  command = _command(_path(0.04), 0.04, current_curvature=0.5)
+  assert command.path_offset > 0.0
+  assert command.path_angle > 0.0
+  assert command.curvature == 0.0
+
+
+def test_feedback_preserves_half_lsb_feedforward_direction():
+  for feedforward, resolution in ((0.006, 0.01), (0.0004, 0.0005)):
+    result = feedforward + _bounded_feedback(feedforward, -1.0, resolution, 1.0)
+    assert result >= 0.5 * resolution
+
+
+def test_recent_curvature_trend_advances_vehicle_pose_without_a_response_gain():
+  model = _model_path(_path(0.04))
+  assert model is not None
+  constant = _encode_path(model, 0.04, current_curvature=0.02, curvature_delta=0.0, v_ego=8.0)
+  rising = _encode_path(model, 0.04, current_curvature=0.02, curvature_delta=0.01, v_ego=8.0)
+  assert 0.0 < rising.path_offset < constant.path_offset
+  assert 0.0 < rising.path_angle < constant.path_angle
+
+
+def test_model_path_exit_zeros_lingering_c2_and_countersteers():
+  command = _command(_path(0.0), 0.004, current_curvature=0.006)
+  assert command.path_offset <= 0.0
+  assert command.path_angle < 0.0
+  assert command.curvature == 0.0
+
+
+def test_model_path_reversal_zeros_opposing_lingering_c2():
+  command = _command(_path(-0.004), 0.004, current_curvature=0.002)
+  assert command.path_offset < 0.0
+  assert command.path_angle < 0.0
+  assert command.curvature == 0.0
+
+
+def test_s_turn_reverses_model_pose_without_slow_c2():
+  controller = FordPathController(dt=0.05)
+  for _ in range(10):
+    controller.update(_path(0.04), 0.04, v_ego=8.0)
+  outputs = [controller.update(_path(-0.04), -0.04, v_ego=8.0) for _ in range(10)]
+  assert all(command.curvature == 0.0 for command in outputs)
+  assert np.all(np.diff([command.path_offset for command in outputs]) < 0.0)
+  assert np.all(np.diff([command.path_angle for command in outputs]) < 0.0)
+  assert outputs[-1].path_offset < 0.0
+  assert outputs[-1].path_angle < 0.0
+
+
+def test_output_limits_and_rates_are_bounded():
+  controller = FordPathController()
+  outputs = [controller.update(_path(0.2), 0.2, v_ego=8.0) for _ in range(100)]
+  assert all(DBC_OFFSET[0] <= command.path_offset <= DBC_OFFSET[1] for command in outputs)
+  assert all(DBC_ANGLE[0] <= command.path_angle <= DBC_ANGLE[1] for command in outputs)
+  assert all(DBC_CURVATURE[0] <= command.curvature <= DBC_CURVATURE[1] for command in outputs)
+  assert np.max(np.abs(np.diff([command.path_offset for command in outputs]))) <= 0.04 + 1e-9
+  assert np.max(np.abs(np.diff([command.path_angle for command in outputs]))) <= 0.01 + 1e-9
+
+
+def test_clipped_path_angle_uses_available_offset_to_preserve_endpoint():
+  horizon = 7.0
+  for curvature, angle_limit in ((-0.1, DBC_ANGLE[0]), (0.1, DBC_ANGLE[1])):
+    model = _path(curvature)
+    command = _command(model, curvature, current_curvature=curvature, v_ego=horizon)
+    path = _model_path(model)
+    assert path is not None
+    advance = 0.1 * horizon
+    model_offset, model_angle = _relative_pose(advance + horizon, path,
+                                                _predicted_pose(advance, curvature, 0.0))
+
+    assert command.path_angle == angle_limit
+    assert np.isclose(command.path_offset + horizon * command.path_angle,
+                      model_offset + horizon * model_angle)
+
+
+def test_invalid_model_ramps_pose_to_zero_and_inactive_resets():
+  controller = FordPathController(dt=0.01)
+  for _ in range(20):
+    active = controller.update(_path(0.04), 0.04, v_ego=8.0)
+  invalid = controller.update(None, 0.0, v_ego=8.0)
+  assert invalid.valid
+  assert abs(invalid.path_offset) < abs(active.path_offset)
+  assert abs(invalid.path_angle) < abs(active.path_angle)
+  assert not controller.update(_path(0.0), 0.0, v_ego=8.0, active=False).valid
+
+
+def test_sunnypilot_path_message_round_trip():
+  message = custom.CarControlSP.new_message()
+  message.fordLateralPath.pathOffset = 0.3
+  message.fordLateralPath.pathAngle = -0.2
+  message.fordLateralPath.curvature = 0.008
+  message.fordLateralPath.curvatureRate = -0.0004
+  message.fordLateralPath.valid = True
+  path = convert_carControlSP(message.as_reader()).fordLateralPath
+  assert np.isclose(path.pathOffset, 0.3)
+  assert np.isclose(path.pathAngle, -0.2)
+  assert np.isclose(path.curvature, 0.008)
+  assert np.isclose(path.curvatureRate, -0.0004)
+  assert path.valid
+
+
+def test_pscm_observer_mirrors_exact_250hz_slew_and_c3_target():
+  observer = FordPscmObserver()
+  observer.set_command(FordPath(True, 1.0, 0.5, 0.0, 0.001))
+  observer.advance(1.0)
+  assert np.isclose(observer.state.path_offset, 1.0)
+  assert np.isclose(observer.state.path_angle, 0.100006103515625)
+  assert np.isclose(observer.state.curvature, 0.0030059814453125)
+
+
+def test_pscm_observer_tracks_wire_quantized_commands():
+  observer = FordPscmObserver()
+  observer.set_command(FordPath(True, 0.006, 0.0004, 0.000011, 0.0))
+  assert observer.command.path_offset == 0.01
+  assert observer.command.path_angle == 0.0005
+  assert observer.command.curvature == 0.00002
+
+
+def test_pscm_c2_contribution_is_speed_scheduled():
+  state = FordPscmObserver().state
+  state = type(state)(curvature=0.004)
+  low = _pscm_contributions(state, 5.0)[2]
+  high = _pscm_contributions(state, 20.0)[2]
+  assert high > low * 10.0
+
+
+def test_pscm_observer_fills_missing_gentle_c2_with_fast_fields():
+  controller = FordPscmObserverPathController(dt=0.01)
+  command = controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
+                              v_ego=20.0, v_ego_raw=20.0)
+  assert command.path_offset > 0.0
+  assert command.path_angle > 0.0
+  assert command.curvature > 0.0
+
+
+def test_pscm_observer_uses_c0_only_after_c1_reaches_its_effective_limit():
+  controller = FordPscmObserverPathController(dt=0.01)
+  small = controller._command_for_state(FordPath(True, 0.2, 0.0, 0.0, 0.0), 8.0)
+  large = controller._command_for_state(FordPath(True, 1.0, 0.5, 0.0, 0.0), 8.0)
+  assert small.path_offset == 0.0
+  assert small.path_angle > 0.0
+  assert large.path_offset > 0.0
+  assert large.path_angle == 0.349609375 / 10.0
+
+
+def test_pscm_observer_preserves_c2_residual_across_c0_c1_headroom():
+  controller = FordPscmObserverPathController(dt=0.01)
+  target = FordPath(True, 0.0, 0.0, 0.004, 0.0)
+  command = controller._command_for_state(target, 20.0)
+  target_contribution = sum(_pscm_contributions(FordPscmState(curvature=target.curvature), 20.0))
+  command_contributions = _pscm_contributions(FordPscmState(command.path_offset, command.path_angle), 20.0)
+  assert np.isclose(sum(command_contributions), target_contribution)
+
+  controller.observer.state = FordPscmState(curvature=0.004)
+  unwind = controller._command_for_state(FordPath(valid=True), 20.0)
+  unwind_contributions = _pscm_contributions(FordPscmState(unwind.path_offset, unwind.path_angle), 20.0)
+  lingering_c2 = _pscm_contributions(controller.observer.state, 20.0)[2]
+  assert np.isclose(sum(unwind_contributions) + lingering_c2, 0.0)
+
+
+def test_pscm_observer_unloads_fast_residual_as_c2_loads():
+  controller = FordPscmObserverPathController(dt=0.01)
+  outputs = [controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
+                               v_ego=20.0, v_ego_raw=20.0) for _ in range(200)]
+  assert outputs[0].path_angle > outputs[-1].path_angle >= 0.0
+  assert controller.observer.state.curvature > 0.003
+
+
+def test_pscm_observer_counters_lingering_c2_during_model_exit():
+  controller = FordPscmObserverPathController(dt=0.01)
+  for _ in range(200):
+    controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
+                      v_ego=20.0, v_ego_raw=20.0)
+  command = controller.update(_path(0.0, speed=20.0), 0.0, current_curvature=0.004,
+                              v_ego=20.0, v_ego_raw=20.0)
+  assert command.path_angle < 0.0
+  assert command.curvature < controller.observer.state.curvature
+
+
+def test_pscm_observer_avoids_ineffective_c0_c1_windup():
+  controller = FordPscmObserverPathController(dt=1.0)
+  command = controller.update(_path(0.2), 0.2, v_ego=8.0, v_ego_raw=8.0)
+  assert abs(command.path_offset) <= 1.0
+  assert abs(command.path_angle) <= 0.349609375 / 10.0

openpilot/selfdrive/selfdrived/selfdrived.py

@@ -32,7 +32,14 @@ from openpilot.sunnypilot.selfdrive.car.car_specific import CarSpecificEventsSP
 from openpilot.sunnypilot.selfdrive.car.cruise_helpers import CruiseHelper
 from openpilot.sunnypilot.selfdrive.car.intelligent_cruise_button_management.controller import IntelligentCruiseButtonManagement
 from openpilot.sunnypilot.selfdrive.selfdrived.button_state_tracker import ButtonStateTracker
+from openpilot.sunnypilot.selfdrive.selfdrived.assisted_driving_milestones import (
+  AssistCategory,
+  AssistedDrivingMilestones,
+  MilestoneEvent,
+  MilestoneStore,
+)
 from openpilot.sunnypilot.selfdrive.selfdrived.events import EventsSP
+from openpilot.sunnypilot.system.statsd import statlog
 
 REPLAY = "REPLAY" in os.environ
 SIMULATION = "SIMULATION" in os.environ
@@ -88,7 +95,8 @@ class SelfdriveD(CruiseHelper):
     self.big_model_ready_t = 0.
 
     # Setup sockets
-    self.pm = messaging.PubMaster(['selfdriveState', 'onroadEvents'] + ['selfdriveStateSP', 'onroadEventsSP'])
+    self.pm = messaging.PubMaster(['selfdriveState', 'onroadEvents'] +
+                                  ['selfdriveStateSP', 'onroadEventsSP', 'assistedDrivingMilestoneState'])
 
     self.gps_location_service = get_gps_location_service(self.params)
     self.gps_packets = [self.gps_location_service]
@@ -127,6 +135,7 @@ class SelfdriveD(CruiseHelper):
       self.params.remove("ExperimentalMode")
 
     self.CS_prev = car.CarState.new_message()
+    self.car_state_log_mono_time = 0
     self.AM = AlertManager()
     self.events = Events()
 
@@ -137,6 +146,11 @@ class SelfdriveD(CruiseHelper):
     self.cruise_mismatch_counter = 0
     self.last_steering_pressed_frame = 0
     self.distance_traveled = 0
+    self.assisted_driving_milestones = AssistedDrivingMilestones(MilestoneStore(self.params))
+    self.assisted_driving_milestones_enabled = bool(self.params.get("AssistedDrivingMilestonesEnabled", return_default=True))
+    self.assisted_driving_milestone_drive_id = ""
+    self._milestone_event: MilestoneEvent | None = None
+    self._milestone_event_expires_ns = 0
     self.last_functional_fan_frame = 0
     self.events_prev = []
     self.logged_comm_issue = None
@@ -528,6 +542,8 @@ class SelfdriveD(CruiseHelper):
   def data_sample(self):
     _car_state = messaging.recv_one(self.car_state_sock)
     CS = _car_state.carState if _car_state else self.CS_prev
+    if _car_state is not None:
+      self.car_state_log_mono_time = _car_state.logMonoTime
 
     self.sm.update(0)
 
@@ -646,6 +662,31 @@ class SelfdriveD(CruiseHelper):
       self.pm.send('onroadEventsSP', ce_send_sp)
     self.events_sp_prev = self.events_sp.names.copy()
 
+  def publish_assisted_driving_milestones(self, now_ns: int, event: MilestoneEvent | None) -> None:
+    if event is not None:
+      self._milestone_event = event
+      self._milestone_event_expires_ns = now_ns + 1_000_000_000
+    elif now_ns >= self._milestone_event_expires_ns:
+      self._milestone_event = None
+
+    if event is None and self.sm.frame % 10 != 0:
+      return
+
+    snapshot = self.assisted_driving_milestones.snapshot()
+    msg = messaging.new_message("assistedDrivingMilestoneState")
+    msg.valid = True
+    state = msg.assistedDrivingMilestoneState
+    state.enabled = self.assisted_driving_milestones_enabled
+    state.madsDistanceMeters = snapshot.distances_meters[AssistCategory.MADS]
+    state.fullAssistDistanceMeters = snapshot.distances_meters[AssistCategory.FULL_ASSIST]
+    if self._milestone_event is not None:
+      state.event.id = self._milestone_event.event_id
+      state.event.category = self._milestone_event.category.value
+      state.event.distanceMeters = self._milestone_event.distance_meters
+      state.event.previousDistanceMeters = self._milestone_event.previous_distance_meters
+      state.event.unit = self._milestone_event.unit.value
+    self.pm.send("assistedDrivingMilestoneState", msg)
+
   def step(self):
     CS = self.data_sample()
     self.update_events(CS)
@@ -655,6 +696,28 @@ class SelfdriveD(CruiseHelper):
       self.mads.update(CS)
     self.update_alerts(CS)
 
+    now_ns = time.monotonic_ns()
+    if not self.assisted_driving_milestone_drive_id:
+      self.assisted_driving_milestone_drive_id = self.params.get("CurrentRoute") or ""
+      self.assisted_driving_milestones.set_drive_id(self.assisted_driving_milestone_drive_id)
+    car_control = self.sm['carControl']
+    milestone_event = self.assisted_driving_milestones.update(
+      self.car_state_log_mono_time,
+      CS.vEgo,
+      lat_active=car_control.latActive,
+      long_active=car_control.longActive,
+      is_metric=self.is_metric,
+      enabled=self.assisted_driving_milestones_enabled,
+    )
+    if milestone_event is not None:
+      cloudlog.event("assisted_driving_milestone_reached",
+                     event_id=milestone_event.event_id,
+                     category=milestone_event.category.value,
+                     distance_meters=milestone_event.distance_meters)
+      statlog.gauge(f"assisted_driving_milestone.{milestone_event.category.value}.meters",
+                    milestone_event.distance_meters)
+    self.publish_assisted_driving_milestones(now_ns, milestone_event)
+
     self.button_state_tracker.update(CS)
     self.publish_selfdriveState(CS)
 
@@ -667,6 +730,7 @@ class SelfdriveD(CruiseHelper):
       self.disengage_on_accelerator = self.params.get_bool("DisengageOnAccelerator")
       self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
       self.personality = self.params.get("LongitudinalPersonality", return_default=True)
+      self.assisted_driving_milestones_enabled = bool(self.params.get("AssistedDrivingMilestonesEnabled", return_default=True))
 
       self.mads.read_params()
       time.sleep(0.1)
@@ -680,6 +744,7 @@ class SelfdriveD(CruiseHelper):
         self.step()
         self.rk.monitor_time()
     finally:
+      self.assisted_driving_milestones.close()
       e.set()
       t.join()
 

openpilot/selfdrive/ui/mici/layouts/main.py

@@ -1,5 +1,8 @@
+import os
+
 import pyray as rl
 import openpilot.cereal.messaging as messaging
+from openpilot.common.hardware import PC
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
 from openpilot.selfdrive.ui.mici.layouts.settings.settings import SettingsLayout
 from openpilot.selfdrive.ui.mici.layouts.offroad_alerts import MiciOffroadAlerts
@@ -61,7 +64,8 @@ class MiciMainLayout(Scroller):
 
     # Start onboarding if terms or training not completed, make sure to push after self
     self._onboarding_window = OnboardingWindow(lambda: gui_app.pop_widgets_to(self))
-    if not self._onboarding_window.completed:
+    skip_onboarding_for_milestone_preview = PC and os.getenv("SP_MILESTONE_PREVIEW") == "1"
+    if not self._onboarding_window.completed and not skip_onboarding_for_milestone_preview:
       gui_app.push_widget(self._onboarding_window)
 
     # initialize correct onroad layout
@@ -119,6 +123,8 @@ class MiciMainLayout(Scroller):
         self._onroad_time_delay = rl.get_time()
       else:
         self._scroll_to(self._home_layout)
+        if hasattr(self._home_layout, "request_drive_summary"):
+          self._home_layout.request_drive_summary()
 
     # FIXME: these two pops can interrupt user interacting in the settings
     if self._onroad_time_delay is not None and rl.get_time() - self._onroad_time_delay >= ONROAD_DELAY:

openpilot/selfdrive/ui/mici/layouts/settings/toggles.py

@@ -47,6 +47,7 @@ class TogglesLayoutMici(NavScroller):
     is_metric_toggle = BigParamControl("use metric units", "IsMetric")
     ldw_toggle = BigParamControl("lane departure warnings", "IsLdwEnabled")
     always_on_dm_toggle = BigParamControl("always-on driver monitor", "AlwaysOnDM")
+    milestone_celebrations_toggle = BigParamControl("assisted driving milestones", "AssistedDrivingMilestonesEnabled")
     record_front = BigParamControl("record & upload cabin camera", "RecordFront", toggle_callback=restart_needed_callback)
     record_mic = BigParamControl("record & upload mic audio", "RecordAudio", toggle_callback=restart_needed_callback)
     enable_openpilot = BigParamControl("enable sunnypilot", "OpenpilotEnabledToggle", toggle_callback=restart_needed_callback)
@@ -57,6 +58,7 @@ class TogglesLayoutMici(NavScroller):
       is_metric_toggle,
       ldw_toggle,
       always_on_dm_toggle,
+      milestone_celebrations_toggle,
       record_front,
       record_mic,
       enable_openpilot,
@@ -68,6 +70,7 @@ class TogglesLayoutMici(NavScroller):
       ("IsMetric", is_metric_toggle),
       ("IsLdwEnabled", ldw_toggle),
       ("AlwaysOnDM", always_on_dm_toggle),
+      ("AssistedDrivingMilestonesEnabled", milestone_celebrations_toggle),
       ("RecordFront", record_front),
       ("RecordAudio", record_mic),
       ("OpenpilotEnabledToggle", enable_openpilot),

openpilot/selfdrive/ui/mici/onroad/alert_renderer.py

@@ -20,6 +20,7 @@ AlertSize = log.SelfdriveState.AlertSize
 AlertStatus = log.SelfdriveState.AlertStatus
 
 ALERT_MARGIN = 18
+ALERT_BACKGROUND_OPACITY = 0.90
 
 ALERT_FONT_SMALL = 66 - 50
 ALERT_FONT_BIG = 88 - 40
@@ -279,7 +280,7 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
   def _draw_background(self, alert: Alert) -> None:
     # draw top gradient for alert text at top
     color = ALERT_COLORS.get(alert.status, ALERT_COLORS[AlertStatus.normal])
-    color = rl.Color(color.r, color.g, color.b, int(255 * 0.90 * self._alpha_filter.x))
+    color = rl.Color(color.r, color.g, color.b, int(255 * ALERT_BACKGROUND_OPACITY * self._alpha_filter.x))
     translucent_color = rl.Color(color.r, color.g, color.b, int(0 * self._alpha_filter.x))
 
     small_alert_height = round(self._rect.height * 0.583) # 140px at mici height

openpilot/selfdrive/ui/mici/onroad/augmented_road_view.py

@@ -19,10 +19,15 @@ from openpilot.common.transformations.camera import DEVICE_CAMERAS, DeviceCamera
 from openpilot.common.transformations.orientation import rot_from_euler
 from enum import IntEnum
 
+MILESTONE_CELEBRATION_ENABLED = gui_app.sunnypilot_ui()
+
 if gui_app.sunnypilot_ui():
   from openpilot.selfdrive.ui.sunnypilot.mici.onroad.hud_renderer import HudRendererSP as HudRenderer
   from openpilot.selfdrive.ui.sunnypilot.ui_state import OnroadTimerStatus
 
+  if MILESTONE_CELEBRATION_ENABLED:
+    from openpilot.selfdrive.ui.sunnypilot.onroad.milestone_celebration import MilestoneCelebration
+
 OpState = log.SelfdriveState.OpenpilotState
 CALIBRATED = log.ExtrinsicsCalibration.Status.calibrated
 NARROW_ROAD_CAM = VisionStreamType.VISION_STREAM_NARROW_ROAD
@@ -156,6 +161,7 @@ class AugmentedRoadView(CameraView):
     self._alert_renderer = AlertRenderer()
     self._driver_state_renderer = DriverStateRenderer()
     self._confidence_ball = ConfidenceBall()
+    self._milestone_celebration = self._child(MilestoneCelebration()) if MILESTONE_CELEBRATION_ENABLED else None
     self._offroad_label = UnifiedLabel("start the car to\nuse sunnypilot", 54, FontWeight.DISPLAY,
                                        text_color=rl.Color(255, 255, 255, int(255 * 0.9)),
                                        alignment=TextAlignment.CENTER,
@@ -223,6 +229,12 @@ class AugmentedRoadView(CameraView):
 
     alert_to_render, not_animating_out = self._alert_renderer.will_render()
 
+    if self._milestone_celebration is not None:
+      if alert_to_render is not None:
+        self._milestone_celebration.cancel_for_alert()
+      else:
+        self._milestone_celebration.render(self._content_rect)
+
     # Hide DMoji when disengaged unless AlwaysOnDM is enabled
     should_draw_dmoji = (not self._hud_renderer.drawing_top_icons() and
                          (ui_state.status != UIStatus.DISENGAGED or ui_state.always_on_dm))
@@ -247,7 +259,6 @@ class AugmentedRoadView(CameraView):
     self._confidence_ball.render(self.rect)
 
     self._bookmark_icon.render(self.rect)
-
   def _switch_stream_if_needed(self, sm):
     if sm['selfdriveState'].experimentalMode and WIDE_CAM in self.available_streams:
       v_ego = sm['carState'].vEgo
@@ -355,10 +366,12 @@ class AugmentedRoadView(CameraView):
     return self._cached_matrix
 
   def show_event(self):
+    super().show_event()
     if gui_app.sunnypilot_ui():
       ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.RESUME)
 
   def hide_event(self):
+    super().hide_event()
     if gui_app.sunnypilot_ui():
       ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.PAUSE)
 

openpilot/selfdrive/ui/soundd.py

@@ -24,14 +24,8 @@ ALERT_RAMP_TIME = 4 # seconds to ramp to max volume for warningImmediate
 SELFDRIVE_STATE_TIMEOUT = 5 # 5 seconds
 FILTER_DT = 1. / (micd.SAMPLE_RATE / micd.FFT_SAMPLES)
 
-AMBIENT_DB = 26 # DB where MIN_VOLUME is applied
 DB_SCALE = 30 # AMBIENT_DB + DB_SCALE is where MAX_VOLUME is applied
 
-VOLUME_BASE = 20
-if HARDWARE.get_device_type() == "tizi":
-  AMBIENT_DB = 30
-  VOLUME_BASE = 10
-
 AudibleAlert = log.SelfdriveState.AudibleAlert
 AudibleAlertSP = custom.SelfdriveStateSP.AudibleAlert
 
@@ -53,6 +47,7 @@ sound_list: dict[int, tuple[str, int | None, float]] = {
   AudibleAlert.promptDistracted: ("dm_warning.wav", None, MAX_VOLUME),
 
   AudibleAlert.preAlert: ("pre_alert.wav", 1, MAX_VOLUME),
+  AudibleAlert.complete: ("milestone.wav", 1, MAX_VOLUME),
 
   AudibleAlert.warningSoft: ("critical.wav", None, MAX_VOLUME),
   AudibleAlert.warningImmediate: ("dm_critical.wav", None, MAX_VOLUME),
@@ -60,6 +55,14 @@ sound_list: dict[int, tuple[str, int | None, float]] = {
   **sound_list_sp,
 }
 
+
+def calculate_volume_for_device(weighted_db: float, device_type: str) -> float:
+  ambient_db = 30 if device_type in ("mici", "tizi") else 26
+  volume_base = 10 if device_type in ("mici", "tizi") else 20
+  volume_boost = 1.5 if device_type == "mici" else 1.0
+  volume = ((weighted_db - ambient_db) / DB_SCALE) * (MAX_VOLUME - MIN_VOLUME) + MIN_VOLUME
+  return min(MAX_VOLUME, volume_boost * math.pow(volume_base, (np.clip(volume, MIN_VOLUME, MAX_VOLUME) - 1)))
+
 def check_selfdrive_timeout_alert(sm):
   ss_missing = time.monotonic() - sm.recv_time['selfdriveState']
 
@@ -74,6 +77,7 @@ class Soundd(QuietMode):
   def __init__(self):
     super().__init__()
 
+    self.device_type = HARDWARE.get_device_type()
     self.load_sounds()
 
     self.current_alert = AudibleAlert.none
@@ -85,6 +89,7 @@ class Soundd(QuietMode):
 
     self.selfdrive_timeout_alert = False
     self.pending_stop = False
+    self.last_milestone_event_id = 0
 
     self.spl_filter_weighted = FirstOrderFilter(0, 2.5, FILTER_DT, initialized=False)
 
@@ -164,9 +169,19 @@ class Soundd(QuietMode):
       self.update_alert(AudibleAlert.none)
       self.selfdrive_timeout_alert = False
 
+  def update_milestone_alert(self, sm):
+    if not sm.updated['assistedDrivingMilestoneState']:
+      return
+    milestone_state = sm['assistedDrivingMilestoneState']
+    event_id = milestone_state.event.id
+    if not milestone_state.enabled or event_id == 0 or event_id == self.last_milestone_event_id:
+      return
+    self.last_milestone_event_id = event_id
+    if self.current_alert == AudibleAlert.none and not self.enabled:
+      self.update_alert(AudibleAlert.complete)
+
   def calculate_volume(self, weighted_db):
-    volume = ((weighted_db - AMBIENT_DB) / DB_SCALE) * (MAX_VOLUME - MIN_VOLUME) + MIN_VOLUME
+    return calculate_volume_for_device(weighted_db, self.device_type)
-    return math.pow(VOLUME_BASE, (np.clip(volume, MIN_VOLUME, MAX_VOLUME) - 1))
 
   @retry(attempts=10, delay=3)
   def get_stream(self, sd):
@@ -180,7 +195,7 @@ class Soundd(QuietMode):
     import sounddevice as sd
     micd.patch_sounddevice(sd)
 
-    sm = messaging.SubMaster(['selfdriveState', 'selfdriveStateSP', 'soundPressure'])
+    sm = messaging.SubMaster(['selfdriveState', 'selfdriveStateSP', 'soundPressure', 'assistedDrivingMilestoneState'])
 
     with self.get_stream(sd) as stream:
       rk = Ratekeeper(20)
@@ -198,6 +213,7 @@ class Soundd(QuietMode):
             self.current_volume = self.calculate_volume(float(self.spl_filter_weighted.x))
 
         self.get_audible_alert(sm)
+        self.update_milestone_alert(sm)
 
         # Ramp up immediate warning sound over 4s
         if self.current_alert == AudibleAlert.warningImmediate:

openpilot/selfdrive/ui/sunnypilot/mici/layouts/home.py

@@ -5,19 +5,79 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 import math
+import time
 
 import pyray as rl
 
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
 from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
-from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.lib.application import FontWeight, TextAlignment
-from openpilot.system.ui.widgets.label import UnifiedLabel
+from openpilot.system.ui.lib.multilang import tr
+from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
+
+METERS_PER_MILE = 1609.344
+METERS_PER_KILOMETER = 1000.0
+SUMMARY_DURATION_SECONDS = 10.0
+SUMMARY_WAIT_SECONDS = 3.0
+
+
+def _nonnegative_float(value) -> float:
+  try:
+    return max(0.0, float(value))
+  except (TypeError, ValueError):
+    return 0.0
 
 
 class MiciHomeLayoutSP(MiciHomeLayout):
   def __init__(self):
     super().__init__()
     self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
+    initial_summary = ui_state.params.get("LastDriveAssistedDrivingSummary", return_default=True) or {}
+    self._last_summary_id = initial_summary.get("id", 0)
+    self._summary_wait_until = 0.0
+    self._summary_visible_until = 0.0
+    self._drive_summary = {}
+
+  def request_drive_summary(self) -> None:
+    self._summary_wait_until = time.monotonic() + SUMMARY_WAIT_SECONDS
+
+  def _render(self, _: rl.Rectangle) -> None:
+    super()._render(_)
+    now = time.monotonic()
+    if now < self._summary_wait_until:
+      summary = ui_state.params.get("LastDriveAssistedDrivingSummary", return_default=True) or {}
+      summary_id = summary.get("id", 0)
+      if summary_id and summary_id != self._last_summary_id:
+        self._last_summary_id = summary_id
+        distances = summary.get("distancesMeters", {})
+        enabled = ui_state.params.get_bool("AssistedDrivingMilestonesEnabled")
+        if enabled and any(_nonnegative_float(distances.get(category, 0.0)) > 0.0 for category in ("mads", "fullAssist")):
+          self._drive_summary = summary
+          self._summary_visible_until = now + SUMMARY_DURATION_SECONDS
+        self._summary_wait_until = 0.0
+
+    if now < self._summary_visible_until:
+      self._draw_drive_summary(_)
+
+  def _draw_drive_summary(self, rect: rl.Rectangle) -> None:
+    distances = self._drive_summary.get("distancesMeters", {})
+    metric = self._drive_summary.get("unit") == "metric"
+    meters_per_unit = METERS_PER_KILOMETER if metric else METERS_PER_MILE
+    unit = "KM" if metric else "MI"
+    mads = _nonnegative_float(distances.get("mads", 0.0)) / meters_per_unit
+    full_assist = _nonnegative_float(distances.get("fullAssist", 0.0)) / meters_per_unit
+
+    rl.draw_rectangle_rec(rect, rl.Color(0, 0, 0, 235))
+    gui_label(rl.Rectangle(rect.x, rect.y + 14, rect.width, 52), tr("DRIVE COMPLETE"), 42,
+              font_weight=FontWeight.SEMI_BOLD, alignment=TextAlignment.CENTER)
+    gui_label(rl.Rectangle(rect.x + 20, rect.y + 78, rect.width / 2 - 30, 42), tr("MADS"), 28,
+              color=rl.Color(255, 255, 255, 184), alignment=TextAlignment.CENTER)
+    gui_label(rl.Rectangle(rect.x + rect.width / 2 + 10, rect.y + 78, rect.width / 2 - 30, 42), tr("FULL ASSIST"), 28,
+              color=rl.Color(255, 255, 255, 184), alignment=TextAlignment.CENTER)
+    gui_label(rl.Rectangle(rect.x + 20, rect.y + 116, rect.width / 2 - 30, 72), f"{mads:.1f} {unit}", 48,
+              font_weight=FontWeight.DISPLAY, alignment=TextAlignment.CENTER)
+    gui_label(rl.Rectangle(rect.x + rect.width / 2 + 10, rect.y + 116, rect.width / 2 - 30, 72), f"{full_assist:.1f} {unit}", 48,
+              font_weight=FontWeight.DISPLAY, alignment=TextAlignment.CENTER)
 
   def _set_chestnut_visibility(self):
     usb_connected = ui_state.usb_connected

openpilot/selfdrive/ui/sunnypilot/onroad/milestone_celebration.py

@@ -0,0 +1,228 @@
+"""Render assisted-driving milestone celebrations over the on-road view."""
+
+import math
+import random
+import time
+from collections import deque
+from dataclasses import dataclass
+
+import pyray as rl
+
+from openpilot.cereal import custom
+from openpilot.selfdrive.ui.mici.onroad.alert_renderer import ALERT_BACKGROUND_OPACITY
+from openpilot.selfdrive.ui.mici.onroad.hud_renderer import FONT_SIZES
+from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.system.ui.lib.application import FontWeight, gui_app
+from openpilot.system.ui.lib.multilang import tr
+from openpilot.system.ui.lib.text_measure import measure_text_cached
+from openpilot.system.ui.widgets import Widget
+
+
+CELEBRATION_DURATION = 4.5
+PARTICLE_COUNT = 150
+METERS_PER_MILE = 1609.344
+METERS_PER_KILOMETER = 1000.0
+
+CONFETTI_COLORS = (
+  rl.Color(255, 55, 95, 255),
+  rl.Color(255, 183, 3, 255),
+  rl.Color(48, 209, 88, 255),
+  rl.Color(36, 179, 255, 255),
+  rl.Color(112, 72, 232, 255),
+  rl.Color(255, 45, 196, 255),
+)
+
+
+@dataclass(frozen=True)
+class ConfettiParticle:
+  x: float
+  y: float
+  width: float
+  height: float
+  speed: float
+  drift: float
+  angle: float
+  spin: float
+  phase: float
+  color: rl.Color
+
+
+@dataclass(frozen=True)
+class CelebrationMilestone:
+  event_id: int
+  full_assist: bool
+  distance_meters: float
+  previous_distance_meters: float
+  metric: bool
+
+
+class MilestoneCelebration(Widget):
+  """Pure renderer for typed assisted-driving milestone events."""
+
+  def __init__(self):
+    super().__init__()
+    self._drive_started_time = -1.0
+    self._celebration_started_time: float | None = None
+    self._current_milestone: CelebrationMilestone | None = None
+    self._pending_milestones: deque[CelebrationMilestone] = deque()
+    self._last_event_id = 0
+    self._particles = self._make_particles()
+
+  @staticmethod
+  def _make_particles() -> list[ConfettiParticle]:
+    rng = random.Random(20260828)
+    return [
+      ConfettiParticle(
+        x=rng.random(),
+        y=rng.uniform(-0.25, 0.95),
+        width=rng.uniform(10, 24),
+        height=rng.uniform(24, 58),
+        speed=rng.uniform(0.12, 0.34),
+        drift=rng.uniform(-0.035, 0.035),
+        angle=rng.uniform(0, 360),
+        spin=rng.uniform(-150, 150),
+        phase=rng.uniform(0, math.tau),
+        color=CONFETTI_COLORS[rng.randrange(len(CONFETTI_COLORS))],
+      )
+      for _ in range(PARTICLE_COUNT)
+    ]
+
+  def _render(self, rect: rl.Rectangle, /) -> None:
+    now = time.monotonic()
+    if ui_state.started_time != self._drive_started_time:
+      self._drive_started_time = ui_state.started_time
+      self._celebration_started_time = None
+      self._current_milestone = None
+      self._pending_milestones.clear()
+
+    self._consume_event(suppress=False)
+
+    if self._current_milestone is None and self._pending_milestones:
+      self._current_milestone = self._pending_milestones.popleft()
+      self._celebration_started_time = now
+
+    if self._celebration_started_time is None or self._current_milestone is None:
+      return
+
+    elapsed = now - self._celebration_started_time
+    if elapsed >= CELEBRATION_DURATION:
+      self._celebration_started_time = None
+      self._current_milestone = None
+      return
+
+    alpha = min(1.0, elapsed / 0.2, (CELEBRATION_DURATION - elapsed) / 0.8)
+    self._draw_background_scrim(rect, alpha)
+    self._draw_confetti(rect, elapsed, alpha)
+    self._draw_milestone(rect, elapsed, alpha, self._current_milestone)
+
+  def cancel_for_alert(self) -> None:
+    self._consume_event(suppress=True)
+    self._celebration_started_time = None
+    self._current_milestone = None
+    self._pending_milestones.clear()
+
+  def _consume_event(self, suppress: bool) -> None:
+    if not ui_state.sm.updated["assistedDrivingMilestoneState"]:
+      return
+    state = ui_state.sm["assistedDrivingMilestoneState"]
+    event = state.event
+    if not state.enabled:
+      self._celebration_started_time = None
+      self._current_milestone = None
+      self._pending_milestones.clear()
+      return
+    if event.id == 0 or event.id == self._last_event_id:
+      return
+    self._last_event_id = event.id
+    if suppress:
+      return
+    self._pending_milestones.append(CelebrationMilestone(
+      event_id=event.id,
+      full_assist=event.category == custom.AssistedDrivingMilestoneState.Category.fullAssist,
+      distance_meters=event.distanceMeters,
+      previous_distance_meters=event.previousDistanceMeters,
+      metric=event.unit == custom.AssistedDrivingMilestoneState.Unit.metric,
+    ))
+
+  def _draw_confetti(self, rect: rl.Rectangle, elapsed: float, alpha: float) -> None:
+    travel_height = rect.height * 1.45
+    compact = rect.height <= 300
+    particle_scale = rect.height / 1080.0
+    particles = self._particles[:100] if compact else self._particles
+    for particle in particles:
+      x = rect.x + rect.width * (particle.x + particle.drift * elapsed + 0.012 * math.sin(elapsed * 3 + particle.phase))
+      y = rect.y - rect.height * 0.2 + (particle.y * travel_height + particle.speed * rect.height * elapsed) % travel_height
+      flip = 0.2 + 0.8 * abs(math.sin(elapsed * 5 + particle.phase))
+      particle_rect = rl.Rectangle(x, y, particle.width * particle_scale * flip, particle.height * particle_scale)
+      origin = rl.Vector2(particle_rect.width / 2, particle_rect.height / 2)
+      color = rl.Color(particle.color.r, particle.color.g, particle.color.b, int(255 * alpha))
+      rl.draw_rectangle_pro(particle_rect, origin, particle.angle + particle.spin * elapsed, color)
+
+  @staticmethod
+  def _draw_milestone(rect: rl.Rectangle, elapsed: float, alpha: float, milestone: CelebrationMilestone) -> None:
+    # Match the comma four set-speed hierarchy: DISPLAY number with a MAX-sized label.
+    scale = rect.height / 240.0
+    pulse = 1.0 + 0.025 * math.sin(min(elapsed, 0.6) / 0.6 * math.pi)
+    number_size = int(FONT_SIZES.set_speed * scale * pulse)
+    milestone_size = int(FONT_SIZES.max_speed * scale * pulse)
+    category_size = int(22 * scale * pulse)
+    unit_size = category_size
+
+    display_font = gui_app.font(FontWeight.DISPLAY)
+    semibold_font = gui_app.font(FontWeight.SEMI_BOLD)
+    tween_progress = min(elapsed / 0.85, 1.0)
+    tween_progress = 1.0 - (1.0 - tween_progress) ** 3
+    meters_per_unit = METERS_PER_KILOMETER if milestone.metric else METERS_PER_MILE
+    previous_distance = milestone.previous_distance_meters / meters_per_unit
+    milestone_distance = milestone.distance_meters / meters_per_unit
+    displayed_distance = previous_distance + (milestone_distance - previous_distance) * tween_progress
+    if tween_progress >= 1.0:
+      number = f"{round(milestone_distance):,}"
+    else:
+      number = f"{displayed_distance:,.1f}"
+    unit = tr("KM") if milestone.metric else tr("MI")
+    category = tr("FULL ASSIST") if milestone.full_assist else tr("MADS")
+    milestone_label = tr("MILESTONE")
+
+    unit_bounds = measure_text_cached(semibold_font, unit, unit_size)
+    number_bounds = measure_text_cached(display_font, number, number_size)
+    max_number_width = rect.width * 0.72 - unit_bounds.x - 8 * scale
+    if number_bounds.x > max_number_width:
+      number_size = max(1, int(number_size * max_number_width / number_bounds.x))
+      number_bounds = measure_text_cached(display_font, number, number_size)
+    category_bounds = measure_text_cached(semibold_font, category, category_size)
+    milestone_bounds = measure_text_cached(semibold_font, milestone_label, milestone_size)
+
+    center_x = rect.x + rect.width / 2
+    center_y = rect.y + rect.height / 2
+    text_color = rl.Color(255, 255, 255, int(255 * 0.9 * alpha))
+    secondary_color = rl.Color(255, 255, 255, int(255 * 0.72 * alpha))
+    number_line_width = number_bounds.x + 8 * scale + unit_bounds.x
+    number_x = center_x - number_line_width / 2
+    number_y = center_y - 76 * scale
+    unit_y = center_y + 14 * scale
+    category_y = center_y - 91 * scale
+    milestone_y = center_y + 50 * scale
+
+    rl.draw_text_ex(semibold_font, category, rl.Vector2(center_x - category_bounds.x / 2, category_y),
+                    category_size, 0, secondary_color)
+    rl.draw_text_ex(display_font, number, rl.Vector2(number_x, number_y), number_size, 0, text_color)
+    rl.draw_text_ex(semibold_font, unit, rl.Vector2(number_x + number_bounds.x + 8 * scale, unit_y),
+                    unit_size, 0, secondary_color)
+    rl.draw_text_ex(semibold_font, milestone_label, rl.Vector2(center_x - milestone_bounds.x / 2, milestone_y),
+                    milestone_size, 0, text_color)
+
+  @staticmethod
+  def _draw_background_scrim(rect: rl.Rectangle, alpha: float) -> None:
+    # Match the alert background: a mostly opaque black core fading to transparent.
+    fade_height = round(rect.height * 0.25)
+    solid_height = round(rect.height * 0.50)
+    solid_color = rl.Color(0, 0, 0, int(255 * ALERT_BACKGROUND_OPACITY * alpha))
+    transparent = rl.Color(0, 0, 0, 0)
+    x = int(rect.x)
+    y = int(rect.y)
+    width = int(rect.width)
+
+    rl.draw_rectangle_gradient_v(x, y, width, fade_height, transparent, solid_color)
+    rl.draw_rectangle(x, y + fade_height, width, solid_height, solid_color)
+    rl.draw_rectangle_gradient_v(x, y + fade_height + solid_height, width, fade_height, solid_color, transparent)

openpilot/selfdrive/ui/sunnypilot/ui_state.py

@@ -35,7 +35,8 @@ class UIStateSP:
     self.is_sp_release: bool = self.params.get_bool("IsReleaseSpBranch")
     self.sm_services_ext = [
       "modelManagerSP", "selfdriveStateSP", "longitudinalPlanSP", "backupManagerSP",
-      "gpsLocation", "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay"
+      "gpsLocation", "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay",
+      "assistedDrivingMilestoneState",
     ]
 
     self.sunnylink_state = SunnylinkState()

openpilot/selfdrive/ui/tests/generate_milestone_sound.py

@@ -0,0 +1,45 @@
+#!/usr/bin/env python3
+"""Generate the assisted-driving milestone celebration chime."""
+
+import math
+import wave
+from array import array
+from pathlib import Path
+
+
+SAMPLE_RATE = 48_000
+DURATION_SECONDS = 0.82
+NOTES = (
+  (0.00, 523.25),
+  (0.11, 659.25),
+  (0.22, 783.99),
+)
+
+
+def note_sample(age: float, frequency: float) -> float:
+  if not 0 <= age <= 0.58:
+    return 0.0
+  attack = min(age / 0.008, 1.0)
+  release = min((0.58 - age) / 0.15, 1.0)
+  envelope = attack * release * math.exp(-3.8 * age)
+  tone = math.sin(math.tau * frequency * age) + 0.16 * math.sin(math.tau * frequency * 2 * age)
+  return envelope * tone
+
+
+def main() -> None:
+  output = Path(__file__).parents[4] / "openpilot/selfdrive/assets/sounds/milestone.wav"
+  samples = array('h')
+  for frame in range(round(SAMPLE_RATE * DURATION_SECONDS)):
+    t = frame / SAMPLE_RATE
+    value = 0.38 * sum(note_sample(t - start, frequency) for start, frequency in NOTES)
+    samples.append(round(max(-1.0, min(1.0, value)) * 32767))
+
+  with wave.open(str(output), "wb") as wav:
+    wav.setnchannels(1)
+    wav.setsampwidth(2)
+    wav.setframerate(SAMPLE_RATE)
+    wav.writeframes(samples.tobytes())
+
+
+if __name__ == "__main__":
+  main()

openpilot/selfdrive/ui/tests/milestone_preview.py

@@ -0,0 +1,38 @@
+#!/usr/bin/env python3
+"""Publish deterministic milestone events for the local comma-four UI preview."""
+
+import itertools
+import time
+
+from openpilot.cereal import messaging
+
+
+def main() -> None:
+  pm = messaging.PubMaster(["assistedDrivingMilestoneState"])
+  milestones = itertools.cycle(((1, 0, "mads"), (2, 1, "fullAssist"), (5, 2, "mads"), (10, 5, "fullAssist")))
+  event_id = 0
+  milestone, previous_milestone, category = 0, 0, "mads"
+  next_event_time = time.monotonic() + 1.0
+
+  while True:
+    now = time.monotonic()
+    if now >= next_event_time:
+      event_id += 1
+      milestone, previous_milestone, category = next(milestones)
+      next_event_time = now + 6.0
+
+    msg = messaging.new_message("assistedDrivingMilestoneState")
+    state = msg.assistedDrivingMilestoneState
+    state.enabled = True
+    if event_id:
+      state.event.id = event_id
+      state.event.category = category
+      state.event.distanceMeters = milestone * 1609.344
+      state.event.previousDistanceMeters = previous_milestone * 1609.344
+      state.event.unit = "imperial"
+    pm.send("assistedDrivingMilestoneState", msg)
+    time.sleep(0.1)
+
+
+if __name__ == "__main__":
+  main()

openpilot/selfdrive/ui/tests/run_milestone_celebration.sh

@@ -0,0 +1,27 @@
+#!/usr/bin/env bash
+set -e
+
+repo_root="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../../.." && pwd)"
+replay_pid=""
+preview_pid=""
+
+cleanup() {
+  for pid in "$preview_pid" "$replay_pid"; do
+    if [[ -n "$pid" ]]; then
+      kill "$pid" 2>/dev/null || true
+      wait "$pid" 2>/dev/null || true
+    fi
+  done
+}
+trap cleanup EXIT INT TERM
+
+export PATH="$repo_root/.venv/bin:$PATH"
+export SP_MILESTONE_PREVIEW=1
+playback="${SP_MILESTONE_PLAYBACK:-1}"
+
+"$repo_root/openpilot/tools/replay/replay" --demo --playback "$playback" &
+replay_pid=$!
+"$repo_root/.venv/bin/python" "$repo_root/openpilot/selfdrive/ui/tests/milestone_preview.py" &
+preview_pid=$!
+
+"$repo_root/.venv/bin/python" "$repo_root/openpilot/selfdrive/ui/mici/onroad/augmented_road_view.py"

openpilot/selfdrive/ui/tests/test_soundd.py

@@ -4,12 +4,63 @@ import time
 from openpilot.common.test import OpenpilotTestCase
 from openpilot.cereal import log, messaging
 from openpilot.cereal.messaging import SubMaster, PubMaster
-from openpilot.selfdrive.ui.soundd import SELFDRIVE_STATE_TIMEOUT, check_selfdrive_timeout_alert
+from openpilot.selfdrive.ui.soundd import SELFDRIVE_STATE_TIMEOUT, Soundd, calculate_volume_for_device, check_selfdrive_timeout_alert
 
 AudibleAlert = log.SelfdriveState.AudibleAlert
 
 
 class TestSoundd(OpenpilotTestCase):
+  @staticmethod
+  def milestone_submaster(event_id=42):
+    class SubMasterStub:
+      def __init__(self):
+        self.updated = {'assistedDrivingMilestoneState': True}
+        msg = messaging.new_message('assistedDrivingMilestoneState')
+        msg.assistedDrivingMilestoneState.enabled = True
+        msg.assistedDrivingMilestoneState.event.id = event_id
+        self.data = {'assistedDrivingMilestoneState': msg.assistedDrivingMilestoneState}
+
+      def __getitem__(self, service):
+        return self.data[service]
+
+    return SubMasterStub()
+
+  def test_comma_four_volume_is_50_percent_louder_than_comma_three_x(self):
+    for weighted_db in (20.0, 30.0, 40.0, 50.0):
+      with self.subTest(weighted_db=weighted_db):
+        comma_three_x_volume = calculate_volume_for_device(weighted_db, "tizi")
+        comma_four_volume = calculate_volume_for_device(weighted_db, "mici")
+        assert comma_four_volume == min(1.0, comma_three_x_volume * 1.5)
+
+  def test_milestone_chime_uses_typed_milestone_event_once(self):
+    soundd = Soundd()
+    sm = self.milestone_submaster()
+    soundd.update_milestone_alert(sm)
+
+    assert soundd.current_alert == AudibleAlert.complete
+    soundd.current_alert = AudibleAlert.none
+    soundd.update_milestone_alert(sm)
+    assert soundd.current_alert == AudibleAlert.none
+
+  def test_safety_alert_consumes_milestone_without_replaying_it(self):
+    soundd = Soundd()
+    sm = self.milestone_submaster()
+    soundd.current_alert = AudibleAlert.warningImmediate
+
+    soundd.update_milestone_alert(sm)
+    soundd.current_alert = AudibleAlert.none
+    soundd.update_milestone_alert(sm)
+
+    assert soundd.current_alert == AudibleAlert.none
+
+  def test_quiet_mode_consumes_milestone_without_playing_it(self):
+    soundd = Soundd()
+    soundd.enabled = True
+
+    soundd.update_milestone_alert(self.milestone_submaster())
+
+    assert soundd.current_alert == AudibleAlert.none
+
   def test_check_selfdrive_timeout_alert(self, mocker):
     sm = SubMaster(['selfdriveState', 'selfdriveStateSP'])
     pm = PubMaster(['selfdriveState', 'selfdriveStateSP'])

openpilot/sunnypilot/selfdrive/controls/controlsd_ext.py

@@ -104,6 +104,15 @@ class ControlsExt(ModelStateBase):
     CC_SP.intelligentCruiseButtonManagement.sendButton = icbm_src.sendButton
     CC_SP.intelligentCruiseButtonManagement.vTarget = icbm_src.vTarget
 
+    ford_path = getattr(self, 'ford_path', None)
+    if ford_path is not None:
+      CC_SP.fordLateralPath.enabled = getattr(self, 'ford_model_action', False)
+      CC_SP.fordLateralPath.valid = ford_path.valid
+      CC_SP.fordLateralPath.pathOffset = ford_path.path_offset
+      CC_SP.fordLateralPath.pathAngle = ford_path.path_angle
+      CC_SP.fordLateralPath.curvature = ford_path.curvature
+      CC_SP.fordLateralPath.curvatureRate = ford_path.curvature_rate
+
     return CC_SP
 
   @staticmethod

openpilot/sunnypilot/selfdrive/selfdrived/assisted_driving_milestones.py

@@ -0,0 +1,260 @@
+"""Authoritative assisted-driving distance and milestone tracking."""
+
+import math
+from collections.abc import Mapping
+from dataclasses import dataclass
+from enum import StrEnum
+
+from openpilot.common.params import Params
+
+
+METERS_PER_MILE = 1609.344
+METERS_PER_KILOMETER = 1000.0
+MAX_SAMPLE_INTERVAL_SECONDS = 0.5
+PERSIST_INTERVAL_NS = 10_000_000_000
+STATE_VERSION = 1
+STATE_PARAM = "AssistedDrivingMilestoneState"
+LAST_DRIVE_SUMMARY_PARAM = "LastDriveAssistedDrivingSummary"
+
+
+class AssistCategory(StrEnum):
+  MADS = "mads"
+  FULL_ASSIST = "fullAssist"
+
+
+class MilestoneUnit(StrEnum):
+  IMPERIAL = "imperial"
+  METRIC = "metric"
+
+
+@dataclass(frozen=True)
+class MilestoneEvent:
+  event_id: int
+  category: AssistCategory
+  distance_meters: float
+  previous_distance_meters: float
+  unit: MilestoneUnit
+
+
+@dataclass(frozen=True)
+class MilestoneSnapshot:
+  distances_meters: dict[AssistCategory, float]
+  drive_start_distances_meters: dict[AssistCategory, float]
+  next_event_id: int
+  next_summary_id: int
+  unit: MilestoneUnit
+  active_drive_id: str
+
+
+def assist_category(lat_active: bool, long_active: bool) -> AssistCategory | None:
+  if not lat_active:
+    return None
+  return AssistCategory.FULL_ASSIST if long_active else AssistCategory.MADS
+
+
+def _meters_per_unit(unit: MilestoneUnit) -> float:
+  return METERS_PER_KILOMETER if unit == MilestoneUnit.METRIC else METERS_PER_MILE
+
+
+def _next_ladder_value(value: float) -> float:
+  value = max(0.0, value)
+  magnitude = 10.0 ** math.floor(math.log10(max(1.0, value)))
+  for multiplier in (1.0, 2.0, 5.0):
+    candidate = multiplier * magnitude
+    if candidate > value + 1e-9:
+      return candidate
+  return 10.0 * magnitude
+
+
+def _previous_ladder_value(value: float) -> float:
+  if value <= 1.0:
+    return 0.0
+  magnitude = 10.0 ** math.floor(math.log10(value))
+  normalized = value / magnitude
+  if normalized <= 1.0 + 1e-9:
+    return 5.0 * magnitude / 10.0
+  if normalized <= 2.0 + 1e-9:
+    return magnitude
+  return 2.0 * magnitude
+
+
+def next_milestone_meters(distance_meters: float, unit: MilestoneUnit) -> float:
+  meters_per_unit = _meters_per_unit(unit)
+  return _next_ladder_value(distance_meters / meters_per_unit) * meters_per_unit
+
+
+class MilestoneStore:
+  def __init__(self, params: Params | None = None):
+    self._params = params or Params()
+
+  def load(self) -> MilestoneSnapshot:
+    raw = self._params.get(STATE_PARAM, return_default=True)
+    raw = raw if isinstance(raw, dict) else {}
+    raw_distances = raw.get("distancesMeters", {})
+    raw_distances = raw_distances if isinstance(raw_distances, dict) else {}
+    try:
+      unit = MilestoneUnit(raw.get("unit", MilestoneUnit.IMPERIAL))
+    except ValueError:
+      unit = MilestoneUnit.IMPERIAL
+
+    def distance(category: AssistCategory) -> float:
+      try:
+        return max(0.0, float(raw_distances.get(category.value, 0.0)))
+      except (TypeError, ValueError):
+        return 0.0
+
+    distances = {category: distance(category) for category in AssistCategory}
+    raw_drive_start = raw.get("driveStartDistancesMeters", {})
+    raw_drive_start = raw_drive_start if isinstance(raw_drive_start, dict) else {}
+
+    def drive_start_distance(category: AssistCategory) -> float:
+      try:
+        return max(0.0, min(float(raw_drive_start.get(category.value, distances[category])), distances[category]))
+      except (TypeError, ValueError):
+        return distances[category]
+
+    try:
+      next_event_id = max(1, int(raw.get("nextEventId", 1)))
+    except (TypeError, ValueError):
+      next_event_id = 1
+    try:
+      next_summary_id = max(1, int(raw.get("nextSummaryId", 1)))
+    except (TypeError, ValueError):
+      next_summary_id = 1
+
+    return MilestoneSnapshot(
+      distances_meters=distances,
+      drive_start_distances_meters={category: drive_start_distance(category) for category in AssistCategory},
+      next_event_id=next_event_id,
+      next_summary_id=next_summary_id,
+      unit=unit,
+      active_drive_id=str(raw.get("activeDriveId", "")),
+    )
+
+  def save(self, snapshot: MilestoneSnapshot, block: bool = False) -> None:
+    if block:
+      self._params.flush()
+    self._params.put(STATE_PARAM, {
+      "version": STATE_VERSION,
+      "distancesMeters": {category.value: max(0.0, snapshot.distances_meters.get(category, 0.0)) for category in AssistCategory},
+      "driveStartDistancesMeters": {
+        category.value: max(0.0, snapshot.drive_start_distances_meters.get(category, 0.0)) for category in AssistCategory
+      },
+      "nextEventId": max(1, snapshot.next_event_id),
+      "nextSummaryId": max(1, snapshot.next_summary_id),
+      "unit": snapshot.unit.value,
+      "activeDriveId": snapshot.active_drive_id,
+    }, block=block)
+
+  def save_drive_summary(self, summary_id: int, distances_meters: Mapping[AssistCategory, float], unit: MilestoneUnit) -> None:
+    self._params.put(LAST_DRIVE_SUMMARY_PARAM, {
+      "version": STATE_VERSION,
+      "id": summary_id,
+      "distancesMeters": {category.value: max(0.0, distances_meters.get(category, 0.0)) for category in AssistCategory},
+      "unit": unit.value,
+    }, block=True)
+
+
+class AssistedDrivingMilestones:
+  """Tracks, persists, and emits milestones through one small interface."""
+
+  def __init__(self, store: MilestoneStore | None = None):
+    self._store = store or MilestoneStore()
+    snapshot = self._store.load()
+    self._distances_meters = snapshot.distances_meters
+    self._drive_start_distances_meters = snapshot.drive_start_distances_meters
+    self._next_event_id = snapshot.next_event_id
+    self._next_summary_id = snapshot.next_summary_id
+    self._unit = snapshot.unit
+    self._active_drive_id = snapshot.active_drive_id
+    self._next_milestone_meters = {
+      category: next_milestone_meters(distance, self._unit)
+      for category, distance in self._distances_meters.items()
+    }
+    self._last_timestamp_ns: int | None = None
+    self._last_persist_timestamp_ns: int | None = None
+    self._last_speed_mps = 0.0
+    self._last_category: AssistCategory | None = None
+    self._enabled = False
+    self._closed = False
+
+  def snapshot(self) -> MilestoneSnapshot:
+    return MilestoneSnapshot(
+      self._distances_meters.copy(),
+      self._drive_start_distances_meters.copy(),
+      self._next_event_id,
+      self._next_summary_id,
+      self._unit,
+      self._active_drive_id,
+    )
+
+  def set_drive_id(self, drive_id: str) -> None:
+    if not drive_id or drive_id == self._active_drive_id:
+      return
+    self._active_drive_id = drive_id
+    self._drive_start_distances_meters = self._distances_meters.copy()
+    self._persist()
+
+  def update(self, timestamp_ns: int, speed_mps: float, *, lat_active: bool, long_active: bool,
+             is_metric: bool, enabled: bool) -> MilestoneEvent | None:
+    self._enabled = enabled
+    unit = MilestoneUnit.METRIC if is_metric else MilestoneUnit.IMPERIAL
+    if unit != self._unit:
+      self._unit = unit
+      self._next_milestone_meters = {
+        category: next_milestone_meters(distance, unit)
+        for category, distance in self._distances_meters.items()
+      }
+
+    speed_mps = max(0.0, speed_mps)
+    category = assist_category(lat_active, long_active) if enabled else None
+    event = None
+
+    if self._last_timestamp_ns is not None and timestamp_ns != self._last_timestamp_ns:
+      dt = (timestamp_ns - self._last_timestamp_ns) / 1e9
+      if 0 < dt <= MAX_SAMPLE_INTERVAL_SECONDS and self._last_category is not None:
+        active_category = self._last_category
+        self._distances_meters[active_category] += (self._last_speed_mps + speed_mps) / 2.0 * dt
+        threshold_meters = self._next_milestone_meters[active_category]
+        if self._distances_meters[active_category] >= threshold_meters:
+          meters_per_unit = _meters_per_unit(self._unit)
+          threshold_units = threshold_meters / meters_per_unit
+          event = MilestoneEvent(
+            event_id=self._next_event_id,
+            category=active_category,
+            distance_meters=threshold_meters,
+            previous_distance_meters=_previous_ladder_value(threshold_units) * meters_per_unit,
+            unit=self._unit,
+          )
+          self._next_event_id += 1
+          self._next_milestone_meters[active_category] = next_milestone_meters(threshold_meters, self._unit)
+          self._persist(timestamp_ns=timestamp_ns)
+
+    self._last_timestamp_ns = timestamp_ns
+    self._last_speed_mps = speed_mps
+    self._last_category = category
+
+    if self._last_persist_timestamp_ns is None:
+      self._last_persist_timestamp_ns = timestamp_ns
+    elif timestamp_ns - self._last_persist_timestamp_ns >= PERSIST_INTERVAL_NS:
+      self._persist(timestamp_ns=timestamp_ns)
+
+    return event
+
+  def close(self) -> None:
+    if self._closed:
+      return
+    self._closed = True
+    drive_distances = {
+      category: self._distances_meters[category] - self._drive_start_distances_meters[category]
+      for category in AssistCategory
+    }
+    summary_id = self._next_summary_id
+    self._next_summary_id += 1
+    self._persist(block=True)
+    if self._enabled:
+      self._store.save_drive_summary(summary_id, drive_distances, self._unit)
+
+  def _persist(self, block: bool = False, timestamp_ns: int | None = None) -> None:
+    self._store.save(self.snapshot(), block=block)
+    self._last_persist_timestamp_ns = self._last_timestamp_ns if timestamp_ns is None else timestamp_ns

openpilot/sunnypilot/selfdrive/selfdrived/tests/test_assisted_driving_milestones.py

@@ -0,0 +1,123 @@
+import unittest
+
+from openpilot.sunnypilot.selfdrive.selfdrived.assisted_driving_milestones import (
+  METERS_PER_MILE,
+  AssistCategory,
+  AssistedDrivingMilestones,
+  MilestoneStore,
+  MilestoneUnit,
+)
+
+
+class ParamsStub:
+  def __init__(self, state=None):
+    self.values = {"AssistedDrivingMilestoneState": state or {}}
+    self.writes = []
+
+  def get(self, key, return_default=False):
+    return self.values.get(key, {} if return_default else None)
+
+  def put(self, key, value, block=False):
+    self.values[key] = value
+    self.writes.append((key, value, block))
+
+  def flush(self):
+    pass
+
+
+class TestAssistedDrivingMilestones(unittest.TestCase):
+  def test_emits_and_asynchronously_persists_first_imperial_milestone(self):
+    params = ParamsStub({
+      "version": 1,
+      "distancesMeters": {"mads": METERS_PER_MILE - 5.0, "fullAssist": 0.0},
+      "nextEventId": 7,
+      "unit": "imperial",
+    })
+    milestones = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+
+    self.assertIsNone(milestones.update(0, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True))
+    event = milestones.update(500_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+
+    self.assertIsNotNone(event)
+    assert event is not None
+    self.assertEqual(event.event_id, 7)
+    self.assertEqual(event.category, AssistCategory.MADS)
+    self.assertEqual(event.unit, MilestoneUnit.IMPERIAL)
+    self.assertAlmostEqual(event.distance_meters, METERS_PER_MILE)
+    self.assertFalse(params.writes[-1][2])
+
+  def test_switching_units_schedules_only_a_future_milestone(self):
+    params = ParamsStub({
+      "version": 1,
+      "distancesMeters": {"mads": 9_500.0, "fullAssist": 0.0},
+      "nextEventId": 2,
+      "unit": "imperial",
+    })
+    milestones = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+
+    self.assertIsNone(milestones.update(0, 1_000.0, lat_active=True, long_active=False, is_metric=True, enabled=True))
+    event = milestones.update(500_000_000, 1_000.0, lat_active=True, long_active=False, is_metric=True, enabled=True)
+
+    self.assertIsNotNone(event)
+    assert event is not None
+    self.assertEqual(event.unit, MilestoneUnit.METRIC)
+    self.assertAlmostEqual(event.distance_meters, 10_000.0)
+
+  def test_ignores_disabled_reverse_and_timestamp_gaps(self):
+    params = ParamsStub()
+    milestones = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+
+    milestones.update(0, 20.0, lat_active=True, long_active=False, is_metric=False, enabled=False)
+    milestones.update(500_000_000, 20.0, lat_active=True, long_active=False, is_metric=False, enabled=False)
+    milestones.update(1_000_000_000, -20.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    milestones.update(2_000_000_000, 20.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+
+    self.assertEqual(milestones.snapshot().distances_meters[AssistCategory.MADS], 0.0)
+
+  def test_close_persists_totals_and_last_drive_summary(self):
+    params = ParamsStub()
+    milestones = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+    milestones.update(0, 10.0, lat_active=True, long_active=True, is_metric=False, enabled=True)
+    milestones.update(500_000_000, 10.0, lat_active=True, long_active=True, is_metric=False, enabled=True)
+
+    milestones.close()
+
+    summary = params.values["LastDriveAssistedDrivingSummary"]
+    self.assertAlmostEqual(summary["distancesMeters"]["fullAssist"], 5.0)
+    self.assertTrue(params.writes[-1][2])
+
+    write_count = len(params.writes)
+    milestones.close()
+    self.assertEqual(len(params.writes), write_count)
+
+  def test_process_restart_preserves_the_current_drive_start(self):
+    params = ParamsStub()
+    first_process = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+    first_process.set_drive_id("route-1")
+    first_process.update(0, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    first_process.update(500_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    first_process.close()
+
+    second_process = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+    second_process.set_drive_id("route-1")
+    second_process.update(1_000_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    second_process.update(1_500_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    second_process.close()
+
+    summary = params.values["LastDriveAssistedDrivingSummary"]
+    self.assertAlmostEqual(summary["distancesMeters"]["mads"], 10.0)
+
+  def test_disabled_feature_does_not_publish_drive_summary(self):
+    params = ParamsStub()
+    milestones = AssistedDrivingMilestones(MilestoneStore(params))  # type: ignore[arg-type]
+    milestones.update(0, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    milestones.update(500_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=True)
+    milestones.update(1_000_000_000, 10.0, lat_active=True, long_active=False, is_metric=False, enabled=False)
+
+    milestones.close()
+
+    self.assertNotIn("LastDriveAssistedDrivingSummary", params.values)
+
+
+if __name__ == "__main__":
+  unittest.main()

openpilot/sunnypilot/sunnylink/settings_ui.json

@@ -1383,6 +1383,12 @@
               "title": "Steering Arc",
               "description": "Display steering arc on the driving screen when lateral control is enabled."
             },
+            {
+              "key": "AssistedDrivingMilestonesEnabled",
+              "widget": "toggle",
+              "title": "Assisted Driving Milestones",
+              "description": "Celebrate cumulative MADS and full-assist distance milestones while driving."
+            },
             {
               "key": "ShowTurnSignals",
               "widget": "toggle",
@@ -2168,6 +2174,25 @@
     }
   ],
   "vehicle_settings": {
+    "ford": {
+      "title": "Ford Settings",
+      "description": "",
+      "items": [
+        {
+          "key": "FordModelActionController",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Selected-Action Path Tracking (Experimental)",
+          "description": "Follow the selected steering plan using model-path centering and measured steering feedback on any Ford CAN FD vehicle.",
+          "details": "Uses the nearby model path for centering and adjusts the heading request using the difference between requested and measured steering. Uses remaining path-offset range when the base heading request reaches its limit. The correction holds when steering matches and clears on driver override. Default off; physical tracking and turn-exit behavior are not road-validated. Enable only for controlled testing. Turning it off restores upstream Ford curvature control, regardless of any previously stored experimental settings. Only Ford CAN FD vehicles can use this experiment. Changes apply after a real offroad-to-onroad cycle, not immediately or on disengagement alone.",
+          "enablement": [
+            {
+              "type": "offroad_only"
+            }
+          ]
+        }
+      ]
+    },
     "hyundai": {
       "title": "Hyundai / Kia / Genesis Settings",
       "description": "",

openpilot/sunnypilot/sunnylink/settings_ui_src/pages/vehicle.yaml

@@ -6,6 +6,18 @@ icon: vehicle
 order: 99
 kind: vehicle
 sections:
+- id: ford
+  title: Ford Settings
+  description: ''
+  items:
+  - key: FordModelActionController
+    widget: toggle
+    needs_onroad_cycle: true
+    title: Selected-Action Path Tracking (Experimental)
+    description: Follow the selected steering plan using model-path centering and measured steering feedback on any Ford CAN FD vehicle.
+    details: Uses the nearby model path for centering and adjusts the heading request using the difference between requested and measured steering. Uses remaining path-offset range when the base heading request reaches its limit. The correction holds when steering matches and clears on driver override. Default off; physical tracking and turn-exit behavior are not road-validated. Enable only for controlled testing. Turning it off restores upstream Ford curvature control, regardless of any previously stored experimental settings. Only Ford CAN FD vehicles can use this experiment. Changes apply after a real offroad-to-onroad cycle, not immediately or on disengagement alone.
+    enablement:
+    - $ref: '#/macros/offroad'
 - id: hyundai
   title: Hyundai / Kia / Genesis Settings
   description: ''

openpilot/sunnypilot/sunnylink/settings_ui_src/pages/visuals.yaml

@@ -20,6 +20,10 @@ sections:
     widget: toggle
     title: Steering Arc
     description: Display steering arc on the driving screen when lateral control is enabled.
+  - key: AssistedDrivingMilestonesEnabled
+    widget: toggle
+    title: Assisted Driving Milestones
+    description: Celebrate cumulative MADS and full-assist distance milestones while driving.
   - key: ShowTurnSignals
     widget: toggle
     title: Display Turn Signals

openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py

@@ -5,6 +5,7 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 import json
+import tempfile
 
 from openpilot.common.params import Params
 from openpilot.sunnypilot.sunnylink.tools.generate_settings_schema import (
@@ -278,6 +279,26 @@ class TestKnownPanels(OpenpilotTestCase):
 
 
 class TestKnownVehicleSettings(OpenpilotTestCase):
+  def test_ford_model_action_is_separate_default_off_cycle_only_toggle(self, schema):
+    items = _brand_items(schema["vehicle_settings"].get("ford"))
+    candidate = next(item for item in items if item["key"] == "FordModelActionController")
+    assert candidate["title"] == "Selected-Action Path Tracking (Experimental)"
+    assert candidate["widget"] == "toggle"
+    assert candidate["needs_onroad_cycle"] is True
+    assert candidate["enablement"] == [{"type": "offroad_only"}]
+    assert "Turning it off restores upstream Ford curvature control" in candidate["details"]
+    assert "regardless of any previously stored experimental settings" in candidate["details"]
+    assert "not road-validated" in candidate["details"]
+    with tempfile.TemporaryDirectory() as path:
+      assert Params(path).get_default_value("FordModelActionController") is False
+
+  def test_retired_ford_toggles_are_not_exposed(self, schema):
+    items = _brand_items(schema["vehicle_settings"].get("ford"))
+    keys = {item["key"] for item in items}
+    assert "FordVirtualAngleController" not in keys
+    assert "FordSharedPathController" not in keys
+    assert "FordPscmObserver" not in keys
+
   def test_hyundai_has_longitudinal_tuning(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("hyundai"))}
     assert "HyundaiLongitudinalTuning" in keys

openpilot/sunnypilot/system/params_migration.py

@@ -103,6 +103,32 @@ def _migrate_model_bundle_slots(_params):
     cloudlog.exception(f"Error migrating model bundle slots: {e}")
 
 
+def _migrate_assisted_driving_milestones(_params):
+  try:
+    state = _params.get("AssistedDrivingMilestoneState", return_default=True)
+    if isinstance(state, dict) and state.get("version") == 1:
+      return
+
+    _params.put("AssistedDrivingMilestoneState", {
+      "version": 1,
+      "distancesMeters": {
+        "mads": max(0.0, _params.get("MadsDrivenDistanceMeters", return_default=True) or 0.0),
+        "fullAssist": max(0.0, _params.get("FullAssistDrivenDistanceMeters", return_default=True) or 0.0),
+      },
+      "driveStartDistancesMeters": {
+        "mads": max(0.0, _params.get("MadsDrivenDistanceMeters", return_default=True) or 0.0),
+        "fullAssist": max(0.0, _params.get("FullAssistDrivenDistanceMeters", return_default=True) or 0.0),
+      },
+      "nextEventId": 1,
+      "nextSummaryId": 1,
+      "unit": "metric" if _params.get_bool("IsMetric") else "imperial",
+      "activeDriveId": "",
+    }, block=True)
+    cloudlog.info("params_migration: migrated assisted-driving milestone state")
+  except Exception as e:
+    cloudlog.exception(f"Error migrating assisted-driving milestone state: {e}")
+
+
 def run_migration(_params):
   # migrate OnroadScreenOffBrightness
   if _params.get("OnroadScreenOffBrightnessMigrated") != ONROAD_BRIGHTNESS_MIGRATION_VERSION:
@@ -142,3 +168,5 @@ def run_migration(_params):
 
   # seed the chestnut model slot from the pre-split single slot
   _migrate_model_bundle_slots(_params)
+
+  _migrate_assisted_driving_milestones(_params)

openpilot/sunnypilot/system/tests/test_params_migration.py

@@ -7,7 +7,44 @@ See the LICENSE.md file in the root directory for more details.
 
 from openpilot.common.params import Params
 from openpilot.common.test import OpenpilotTestCase
-from openpilot.sunnypilot.system.params_migration import _migrate_model_bundle_slots
+from openpilot.sunnypilot.system.params_migration import _migrate_model_bundle_slots, run_migration
+
+
+class TestAssistedDrivingMilestoneMigration(OpenpilotTestCase):
+  def test_preserves_prototype_distances_once(self):
+    class ParamsStub:
+      def __init__(self):
+        self.values = {
+          "MadsDrivenDistanceMeters": 123.0,
+          "FullAssistDrivenDistanceMeters": 456.0,
+          "OnroadScreenOffBrightness": 0,
+          "OnroadScreenOffTimer": 15,
+          "AssistedDrivingMilestoneState": {},
+          "IsMetric": False,
+        }
+
+      def get(self, key, return_default=False):
+        return self.values.get(key)
+
+      def put(self, key, value, block=False):
+        self.values[key] = value
+
+      def get_bool(self, key):
+        return bool(self.values.get(key, False))
+
+    params = ParamsStub()
+
+    run_migration(params)
+
+    state = params.get("AssistedDrivingMilestoneState")
+    assert state["distancesMeters"] == {"mads": 123.0, "fullAssist": 456.0}
+
+    params.put("MadsDrivenDistanceMeters", 12.0, block=True)
+    params.put("FullAssistDrivenDistanceMeters", 34.0, block=True)
+    run_migration(params)
+
+    state = params.get("AssistedDrivingMilestoneState")
+    assert state["distancesMeters"] == {"mads": 123.0, "fullAssist": 456.0}
 
 
 class TestModelBundleSlotMigration(OpenpilotTestCase):

tools/ford_native_path.py

@@ -0,0 +1,498 @@
+#!/usr/bin/env python3
+"""Offline evaluation of Ford's native four-field path polynomial.
+
+The experiment deliberately does not alter the live controller. It rebases the
+model path into the vehicle pose expected at actuation time, fits one cubic over
+the remaining short path, and converts the cubic into the LMC2 C0/C1/C2/C3
+signals. A first-order C2 response envelope is included to expose commands that
+would look good only if the PSCM curvature channel were instantaneous.
+"""
+
+import argparse
+from collections import defaultdict
+from dataclasses import dataclass
+import glob
+import math
+from pathlib import Path
+
+import numpy as np
+
+from openpilot.tools.lib.logreader import LogReader
+
+
+DBC_OFFSET = (-5.12, 5.11)
+DBC_ANGLE = (-0.5, 0.5235)
+DBC_CURVATURE = (-0.02, 0.02)
+DBC_CURVATURE_RATE = (-0.001024, 0.001023)
+MAX_LATERAL_ACCEL = 3.0 + 9.81 * 0.06
+MAX_LATERAL_JERK = 3.0 + 9.81 * 0.06
+@dataclass(frozen=True)
+class ModelPath:
+  x: np.ndarray
+  y: np.ndarray
+  heading: np.ndarray
+  distance: np.ndarray
+
+
+@dataclass(frozen=True)
+class Sample:
+  route: str
+  time: float
+  speed: float
+  curvature: float
+  steering_pressed: bool
+  path: ModelPath
+  sent_c0: float
+  sent_c1: float
+  sent_c2: float
+  sent_c3: float
+@dataclass(frozen=True)
+class NativePath:
+  c0: float
+  c1: float
+  c2: float
+  c3: float
+  fit_rmse: float
+  path_rms: float
+
+
+def _model_path(model) -> ModelPath | None:
+  try:
+    x = np.asarray(model.position.x, dtype=float)
+    y = np.asarray(model.position.y, dtype=float)
+    heading = np.unwrap(np.asarray(model.orientation.z, dtype=float))
+  except (AttributeError, TypeError, ValueError):
+    return None
+  if len(x) < 4 or len(x) != len(y) or len(x) != len(heading):
+    return None
+  if not np.isfinite(np.concatenate((x, y, heading))).all():
+    return None
+  distance = np.concatenate(([0.0], np.cumsum(np.hypot(np.diff(x), np.diff(y)))))
+  unique_distance, unique = np.unique(distance, return_index=True)
+  if len(unique_distance) < 4 or unique_distance[-1] <= 0.0:
+    return None
+  return ModelPath(x[unique], y[unique], heading[unique], unique_distance)
+
+
+def _arc_pose(distance: float, curvature: float) -> tuple[float, float, float]:
+  heading = curvature * distance
+  if abs(curvature) < 1e-9:
+    return distance, 0.0, 0.0
+  return math.sin(heading) / curvature, (1.0 - math.cos(heading)) / curvature, heading
+
+
+def _relative_points(path: ModelPath, vehicle_pose: tuple[float, float, float], start: float,
+                     horizon: float, count: int = 25) -> tuple[np.ndarray, np.ndarray]:
+  sample_distance = np.linspace(start, min(start + horizon, path.distance[-1]), count)
+  desired_x = np.interp(sample_distance, path.distance, path.x)
+  desired_y = np.interp(sample_distance, path.distance, path.y)
+  vehicle_x, vehicle_y, vehicle_heading = vehicle_pose
+  dx = desired_x - vehicle_x
+  dy = desired_y - vehicle_y
+  cosine = math.cos(vehicle_heading)
+  sine = math.sin(vehicle_heading)
+  return cosine * dx + sine * dy, -sine * dx + cosine * dy
+
+
+def _fit_points(path: ModelPath, speed: float, current_curvature: float, delay: float,
+                horizon: float) -> tuple[np.ndarray, np.ndarray] | None:
+  advance = min(max(speed, 0.0) * delay, path.distance[-1])
+  available = min(horizon, path.distance[-1] - advance)
+  if available <= 0.25:
+    return None
+  x, y = _relative_points(path, _arc_pose(advance, current_curvature), advance, available)
+  forward = (x >= -0.25) & (x <= horizon)
+  x = x[forward]
+  y = y[forward]
+  if len(x) < 4 or np.ptp(x) <= 0.25:
+    return None
+  return x, y
+
+
+def _wire_coefficients(c0: float, c1: float, c2: float, c3: float) -> tuple[float, float, float, float]:
+  slope = math.tan(c1)
+  slope_norm = 1.0 + slope ** 2
+  a2 = 0.5 * c2 * slope_norm ** 1.5
+  a3 = (c3 + 12.0 * slope * a2 ** 2 / slope_norm ** 3) * slope_norm ** 2 / 6.0
+  return c0, slope, a2, a3
+
+
+def _wire_rmse(command: tuple[float, float, float, float], x: np.ndarray, y: np.ndarray) -> float:
+  a0, a1, a2, a3 = _wire_coefficients(*command)
+  reconstructed = a0 + a1 * x + a2 * x ** 2 + a3 * x ** 3
+  return float(np.sqrt(np.mean((reconstructed - y) ** 2)))
+
+
+def fit_native_path(path: ModelPath, speed: float, current_curvature: float, *, delay: float,
+                    horizon: float) -> NativePath:
+  """Fit the delay-aligned path and return physical LMC2 fields.
+
+  C2 and C3 are curvature and curvature rate at the vehicle-frame origin, not
+  the raw quadratic and cubic polynomial coefficients.
+  """
+  points = _fit_points(path, speed, current_curvature, delay, horizon)
+  if points is None:
+    return NativePath(0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
+  x, y = points
+
+  # Scaling x before the least-squares solve keeps tight-turn fits well
+  # conditioned while preserving an ordinary cubic in vehicle coordinates.
+  scale = max(float(np.max(np.abs(x))), 1.0)
+  normalized_x = x / scale
+  design = np.column_stack((np.ones(len(x)), normalized_x, normalized_x ** 2, normalized_x ** 3))
+  scaled, *_ = np.linalg.lstsq(design, y, rcond=None)
+  a0, a1, a2, a3 = (float(scaled[index] / scale ** index) for index in range(4))
+  slope = a1
+  slope_norm = 1.0 + slope ** 2
+  curvature = 2.0 * a2 / slope_norm ** 1.5
+  curvature_rate = 6.0 * a3 / slope_norm ** 2 - 12.0 * slope * a2 ** 2 / slope_norm ** 3
+  command = (float(np.clip(a0, *DBC_OFFSET)),
+             float(np.clip(math.atan(slope), *DBC_ANGLE)),
+             float(np.clip(curvature, *DBC_CURVATURE)),
+             float(np.clip(curvature_rate, *DBC_CURVATURE_RATE)))
+  return NativePath(
+    *command,
+    _wire_rmse(command, x, y),
+    float(np.sqrt(np.mean(y ** 2))),
+  )
+
+
+def fit_c2_aware_path(path: ModelPath, speed: float, current_curvature: float, *, delay: float,
+                      horizon: float, target_c2: float, effective_c2: float,
+                      use_c3: bool = True) -> NativePath:
+  """Fit fast fields around the C2 curvature the PSCM is expected to realize."""
+  points = _fit_points(path, speed, current_curvature, delay, horizon)
+  if points is None:
+    return NativePath(0.0, 0.0, target_c2, 0.0, 0.0, 0.0)
+  x, y = points
+
+  slope = 0.0
+  a0 = a1 = a3 = 0.0
+  for _ in range(3):
+    a2 = 0.5 * effective_c2 * (1.0 + slope ** 2) ** 1.5
+    design = np.column_stack((np.ones(len(x)), x, x ** 3))
+    (a0, a1, a3), *_ = np.linalg.lstsq(design, y - a2 * x ** 2, rcond=None)
+    slope = float(a1)
+
+  slope_norm = 1.0 + slope ** 2
+  c3 = 6.0 * float(a3) / slope_norm ** 2 - 12.0 * slope * a2 ** 2 / slope_norm ** 3
+  c3 = float(np.clip(c3, *DBC_CURVATURE_RATE)) if use_c3 else 0.0
+  # Once C2 and C3 are fixed to what the hardware can realize, refit C0/C1 so
+  # their fast feedback preserves as much of the same path as possible.
+  _, _, fixed_a2, fixed_a3 = _wire_coefficients(0.0, math.atan(slope), effective_c2, c3)
+  (a0, a1), *_ = np.linalg.lstsq(np.column_stack((np.ones(len(x)), x)),
+                                  y - fixed_a2 * x ** 2 - fixed_a3 * x ** 3, rcond=None)
+  c0 = float(np.clip(a0, *DBC_OFFSET))
+  c1 = float(np.clip(math.atan(float(a1)), *DBC_ANGLE))
+  effective_command = (c0, c1, effective_c2, c3)
+  return NativePath(c0, c1, target_c2, c3, _wire_rmse(effective_command, x, y),
+                    float(np.sqrt(np.mean(y ** 2))))
+
+
+def _route(path: str) -> str:
+  return Path(path).name.split("--", 1)[0]
+
+
+def load_samples(paths: list[str], stride: int = 2) -> list[Sample]:
+  grouped: dict[str, list[str]] = defaultdict(list)
+  for path in paths:
+    grouped[_route(path)].append(path)
+
+  samples = []
+  for route, route_paths in sorted(grouped.items()):
+    events = []
+    for path in sorted(route_paths):
+      events.extend(LogReader(path))
+    events.sort(key=lambda event: event.logMonoTime)
+    if not events:
+      continue
+    start_time = events[0].logMonoTime
+    model_path = None
+    curvature = 0.0
+    lat_active = path_valid = False
+    sent = (0.0, 0.0, 0.0, 0.0)
+    car_state_count = 0
+    for event in events:
+      which = event.which()
+      if which == "modelV2":
+        model_path = _model_path(event.modelV2)
+      elif which == "controlsState":
+        curvature = float(event.controlsState.curvature)
+      elif which == "carControl":
+        lat_active = bool(event.carControl.latActive)
+      elif which == "carControlSP":
+        command = event.carControlSP.fordLateralPath
+        path_valid = bool(command.valid)
+        sent = (float(command.pathOffset), float(command.pathAngle),
+                float(command.curvature), float(command.curvatureRate))
+      elif which == "carState" and lat_active and path_valid and model_path is not None:
+        car_state_count += 1
+        if car_state_count % stride:
+          continue
+        samples.append(Sample(
+          route, (event.logMonoTime - start_time) * 1e-9, float(event.carState.vEgo), curvature,
+          bool(event.carState.steeringPressed), model_path, *sent,
+        ))
+  return samples
+
+
+def _percentile(values: np.ndarray, percentile: float, mask: np.ndarray | None = None) -> float:
+  selected = values if mask is None else values[mask]
+  return float(np.percentile(np.abs(selected), percentile)) if len(selected) else math.nan
+
+
+def _route_rate(samples: list[Sample], values: np.ndarray) -> np.ndarray:
+  rate = np.zeros(len(values))
+  for index in range(1, len(values)):
+    dt = samples[index].time - samples[index - 1].time
+    if samples[index].route == samples[index - 1].route and 0.005 <= dt <= 0.2:
+      rate[index] = (values[index] - values[index - 1]) / dt
+  return rate
+
+
+def _c2_response(samples: list[Sample], target: np.ndarray, tau_load: float,
+                 tau_unload: float) -> np.ndarray:
+  effective = np.zeros(len(target))
+  previous_route = None
+  previous_time = 0.0
+  state = 0.0
+  for index, sample in enumerate(samples):
+    if sample.route != previous_route:
+      state = 0.0
+      previous_time = sample.time
+    dt = float(np.clip(sample.time - previous_time, 0.005, 0.2))
+    loading = target[index] * state >= 0.0 and abs(target[index]) > abs(state)
+    tau = tau_load if loading else tau_unload
+    state += (1.0 - math.exp(-dt / tau)) * (target[index] - state)
+    effective[index] = state
+    previous_route, previous_time = sample.route, sample.time
+  return effective
+
+
+def _limit_c2_command(samples: list[Sample], target: np.ndarray) -> np.ndarray:
+  """Mirror the CAN-FD Ford curvature acceleration/jerk limiter."""
+  limited = np.zeros(len(target))
+  previous_route = None
+  previous_time = 0.0
+  previous = 0.0
+  for index, sample in enumerate(samples):
+    if sample.route != previous_route:
+      previous = 0.0
+      previous_time = sample.time
+    dt = float(np.clip(sample.time - previous_time, 0.005, 0.2))
+    speed = max(sample.speed, 1.0)
+    value = float(np.clip(target[index], -MAX_LATERAL_ACCEL / speed ** 2,
+                          MAX_LATERAL_ACCEL / speed ** 2))
+    step = MAX_LATERAL_JERK / speed ** 2 * dt
+    value = float(np.clip(value, previous - step, previous + step))
+    limited[index] = float(np.clip(value, *DBC_CURVATURE))
+    previous = limited[index]
+    previous_route, previous_time = sample.route, sample.time
+  return limited
+
+
+def _limit_fast_fields(samples: list[Sample], c0_target: np.ndarray,
+                       c1_target: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
+  c0 = np.zeros(len(samples))
+  c1 = np.zeros(len(samples))
+  previous_route = None
+  previous_time = 0.0
+  previous_c0 = previous_c1 = 0.0
+  for index, sample in enumerate(samples):
+    if sample.route != previous_route:
+      previous_c0 = previous_c1 = 0.0
+      previous_time = sample.time
+    dt = float(np.clip(sample.time - previous_time, 0.005, 0.2))
+    c0[index] = np.clip(c0_target[index], previous_c0 - 4.0 * dt, previous_c0 + 4.0 * dt)
+    c1[index] = np.clip(c1_target[index], previous_c1 - 1.0 * dt, previous_c1 + 1.0 * dt)
+    previous_c0, previous_c1 = c0[index], c1[index]
+    previous_route, previous_time = sample.route, sample.time
+  return c0, c1
+
+
+def evaluate(samples: list[Sample], *, delay: float, horizon: float,
+             tau_load: float, tau_unload: float, horizon_time: float = 0.0,
+             assumed_tau_load: float | None = None, assumed_tau_unload: float | None = None,
+             use_c3: bool = True, c2_limit: float = DBC_CURVATURE[1]) -> dict[str, float]:
+  horizons = np.asarray([float(np.clip(sample.speed * horizon_time, 1.0, horizon))
+                         if horizon_time > 0.0 else horizon for sample in samples])
+  commands = [fit_native_path(sample.path, sample.speed, sample.curvature,
+                              delay=delay, horizon=sample_horizon)
+              for sample, sample_horizon in zip(samples, horizons, strict=True)]
+  c0 = np.asarray([command.c0 for command in commands])
+  c1 = np.asarray([command.c1 for command in commands])
+  raw_c2 = np.asarray([command.c2 for command in commands])
+  c2 = np.clip(raw_c2, -c2_limit, c2_limit)
+  c3 = np.asarray([command.c3 for command in commands])
+  fit_rmse = np.asarray([command.fit_rmse for command in commands])
+  path_rms = np.asarray([command.path_rms for command in commands])
+  transmitted_c2 = _limit_c2_command(samples, c2)
+  effective_c2 = _c2_response(samples, transmitted_c2, tau_load, tau_unload)
+  estimated_c2 = _c2_response(samples, transmitted_c2,
+                              tau_load if assumed_tau_load is None else assumed_tau_load,
+                              tau_unload if assumed_tau_unload is None else assumed_tau_unload)
+  compensated = [fit_c2_aware_path(sample.path, sample.speed, sample.curvature,
+                                   delay=delay, horizon=sample_horizon, target_c2=target,
+                                   effective_c2=estimated, use_c3=use_c3)
+                 for sample, sample_horizon, target, estimated in
+                 zip(samples, horizons, c2, estimated_c2, strict=True)]
+  compensated_c0 = np.asarray([command.c0 for command in compensated])
+  compensated_c1 = np.asarray([command.c1 for command in compensated])
+  compensated_c3 = np.asarray([command.c3 for command in compensated])
+  limited_c0, limited_c1 = _limit_fast_fields(samples, compensated_c0, compensated_c1)
+  estimated_compensated_rmse = np.asarray([command.fit_rmse for command in compensated])
+  compensated_rmse = []
+  for sample, sample_horizon, command, effective in zip(samples, horizons, compensated, effective_c2, strict=True):
+    points = _fit_points(sample.path, sample.speed, sample.curvature, delay, sample_horizon)
+    compensated_rmse.append(0.0 if points is None else _wire_rmse(
+      (command.c0, command.c1, effective, command.c3), *points))
+  compensated_rmse = np.asarray(compensated_rmse)
+  limited_compensated_rmse = []
+  for sample, sample_horizon, c0_value, c1_value, c3_value, effective in \
+      zip(samples, horizons, limited_c0, limited_c1, compensated_c3, effective_c2, strict=True):
+    points = _fit_points(sample.path, sample.speed, sample.curvature, delay, sample_horizon)
+    limited_compensated_rmse.append(0.0 if points is None else _wire_rmse(
+      (c0_value, c1_value, effective, c3_value), *points))
+  limited_compensated_rmse = np.asarray(limited_compensated_rmse)
+  missing_c2 = transmitted_c2 - effective_c2
+  # Compare channels by their lateral contribution at the fit horizon. This
+  # includes C3: treating it as zero would incorrectly blame C0/C1 for a
+  # curvature transition the native polynomial assigns to curvature rate.
+  fast = (2.0 * compensated_c0 / horizons ** 2 +
+          2.0 * np.tan(compensated_c1) / horizons +
+          compensated_c3 * horizons / 3.0)
+  lagging = np.abs(missing_c2) > 0.0005
+  unloading = lagging & (np.abs(c2) < 0.75 * np.abs(effective_c2))
+  pressed = np.asarray([sample.steering_pressed for sample in samples])
+  speed = np.asarray([sample.speed for sample in samples])
+  sent_c2 = np.asarray([sample.sent_c2 for sample in samples])
+  sent_transmitted_c2 = _limit_c2_command(samples, sent_c2)
+  sent_effective_c2 = _c2_response(samples, sent_transmitted_c2, tau_load, tau_unload)
+  sent_lpf_rmse = []
+  for sample, sample_horizon, effective in zip(samples, horizons, sent_effective_c2, strict=True):
+    points = _fit_points(sample.path, sample.speed, sample.curvature, delay, sample_horizon)
+    sent_lpf_rmse.append(0.0 if points is None else _wire_rmse(
+      (sample.sent_c0, sample.sent_c1, effective, sample.sent_c3), *points))
+  sent_lpf_rmse = np.asarray(sent_lpf_rmse)
+  raw_c2_rate = _route_rate(samples, c2)
+  c2_rate = _route_rate(samples, transmitted_c2)
+  sent_c2_rate = _route_rate(samples, sent_c2)
+  compensated_c0_rate = _route_rate(samples, compensated_c0)
+  compensated_c1_rate = _route_rate(samples, compensated_c1)
+  compensated_c3_rate = _route_rate(samples, compensated_c3)
+  normalized_fit = np.divide(fit_rmse, path_rms, out=np.zeros_like(fit_rmse), where=path_rms > 1e-4)
+  return {
+    "samples": float(len(samples)),
+    "delay": delay,
+    "horizon": horizon,
+    "horizon_time": horizon_time,
+    "assumed_tau_load": tau_load if assumed_tau_load is None else assumed_tau_load,
+    "assumed_tau_unload": tau_unload if assumed_tau_unload is None else assumed_tau_unload,
+    "use_c3": float(use_c3),
+    "c2_limit": c2_limit,
+    "actual_horizon_p50": _percentile(horizons, 50),
+    "actual_horizon_p95": _percentile(horizons, 95),
+    "fit_rmse_p50": _percentile(fit_rmse, 50),
+    "fit_rmse_p95": _percentile(fit_rmse, 95),
+    "normalized_fit_p95": _percentile(normalized_fit, 95),
+    "c2_aware_rmse_p50": _percentile(compensated_rmse, 50),
+    "c2_aware_rmse_p95": _percentile(compensated_rmse, 95),
+    "c2_aware_estimated_rmse_p95": _percentile(estimated_compensated_rmse, 95),
+    "c2_aware_limited_rmse_p95": _percentile(limited_compensated_rmse, 95),
+    "sent_lpf_rmse_p50": _percentile(sent_lpf_rmse, 50),
+    "sent_lpf_rmse_p95": _percentile(sent_lpf_rmse, 95),
+    "c0_p95": _percentile(c0, 95),
+    "c1_p95": _percentile(c1, 95),
+    "c2_p95": _percentile(c2, 95),
+    "c3_p95": _percentile(c3, 95),
+    "c0_clip_rate": float(np.mean((c0 <= DBC_OFFSET[0]) | (c0 >= DBC_OFFSET[1]))),
+    "c1_clip_rate": float(np.mean((c1 <= DBC_ANGLE[0]) | (c1 >= DBC_ANGLE[1]))),
+    "c2_clip_rate": float(np.mean((c2 <= DBC_CURVATURE[0]) | (c2 >= DBC_CURVATURE[1]))),
+    "c3_clip_rate": float(np.mean((c3 <= DBC_CURVATURE_RATE[0]) | (c3 >= DBC_CURVATURE_RATE[1]))),
+    "c2_aware_c0_p95": _percentile(compensated_c0, 95),
+    "c2_aware_c1_p95": _percentile(compensated_c1, 95),
+    "c2_aware_c3_p95": _percentile(compensated_c3, 95),
+    "c2_aware_c0_rate_p95": _percentile(compensated_c0_rate, 95),
+    "c2_aware_c1_rate_p95": _percentile(compensated_c1_rate, 95),
+    "c2_aware_c0_rate_limit_rate": float(np.mean(np.abs(compensated_c0_rate) > 4.0)),
+    "c2_aware_c1_rate_limit_rate": float(np.mean(np.abs(compensated_c1_rate) > 1.0)),
+    "c2_aware_c3_rate_p95": _percentile(compensated_c3_rate, 95),
+    "raw_c2_rate_p95": _percentile(raw_c2_rate, 95),
+    "c2_rate_p95": _percentile(c2_rate, 95),
+    "sent_c2_rate_p95": _percentile(sent_c2_rate, 95),
+    "c2_lag_p95": _percentile(missing_c2, 95),
+    "lag_samples": float(np.count_nonzero(lagging)),
+    "lag_fast_support_rate": float(np.mean(fast[lagging] * missing_c2[lagging] > 0.0)) if np.any(lagging) else math.nan,
+    "lag_fast_coverage_p50": _percentile(np.divide(fast, missing_c2, out=np.zeros_like(fast),
+                                                    where=np.abs(missing_c2) > 1e-6), 50, lagging),
+    "unload_samples": float(np.count_nonzero(unloading)),
+    "unload_fast_counter_rate": float(np.mean(fast[unloading] * effective_c2[unloading] < 0.0)) if np.any(unloading) else math.nan,
+    "unload_residual_c2_p95": _percentile(effective_c2 - c2, 95, unloading),
+    "pressed_c0_p95": _percentile(c0, 95, pressed),
+    "pressed_c1_p95": _percentile(c1, 95, pressed),
+    "low_speed_fit_p95": _percentile(fit_rmse, 95, speed < 5.0),
+    "road_speed_fit_p95": _percentile(fit_rmse, 95, speed >= 15.0),
+  }
+
+
+def _expand(patterns: list[str]) -> list[str]:
+  return sorted({path for pattern in patterns for path in glob.glob(pattern)})
+
+
+def _self_test() -> None:
+  distance = np.linspace(0.0, 20.0, 81)
+  coefficients = (0.2, 0.03, 0.004, -0.00005)
+  y = sum(coefficient * distance ** power for power, coefficient in enumerate(coefficients))
+  slope = coefficients[1] + 2.0 * coefficients[2] * distance + 3.0 * coefficients[3] * distance ** 2
+  heading = np.arctan(slope)
+  path = ModelPath(distance, y, heading, np.concatenate(([0.0], np.cumsum(np.hypot(np.diff(distance), np.diff(y))))))
+  command = fit_native_path(path, 0.0, 0.0, delay=0.1, horizon=7.0)
+  assert abs(command.c0 - coefficients[0]) < 2e-3
+  assert abs(command.c1 - math.atan(coefficients[1])) < 2e-3
+  expected_c2 = 2.0 * coefficients[2] / (1.0 + coefficients[1] ** 2) ** 1.5
+  assert abs(command.c2 - expected_c2) < 2e-4
+  assert command.fit_rmse < 1e-4
+
+
+def main() -> int:
+  parser = argparse.ArgumentParser(description=__doc__)
+  parser.add_argument("--logs", action="append", help="rlog glob", default=[])
+  parser.add_argument("--delay", type=float, default=0.1)
+  parser.add_argument("--horizon", type=float, action="append")
+  parser.add_argument("--time-horizon", type=float, default=0.0,
+                      help="if nonzero, use clamp(speed * seconds, 1 m, --horizon)")
+  parser.add_argument("--tau-load", type=float, default=0.75)
+  parser.add_argument("--tau-unload", type=float, default=1.3)
+  parser.add_argument("--assumed-tau-load", type=float)
+  parser.add_argument("--assumed-tau-unload", type=float)
+  parser.add_argument("--zero-c3", action="store_true")
+  parser.add_argument("--c2-limit", type=float, action="append",
+                      help="C2 cap to test; defaults to gentle 0.006 and full 0.02")
+  parser.add_argument("--self-test", action="store_true")
+  args = parser.parse_args()
+  if args.self_test:
+    _self_test()
+  paths = _expand(args.logs)
+  if not paths:
+    if args.self_test:
+      return 0
+    parser.error("at least one usable --logs glob is required")
+  samples = load_samples(paths)
+  if not samples:
+    parser.error("logs contain no active Ford path samples")
+  print(f"loaded_logs={len(paths)} samples={len(samples)} tau_load={args.tau_load} tau_unload={args.tau_unload}")
+  for horizon in args.horizon or [3.5, 5.0, 7.0, 10.0]:
+    for c2_limit in args.c2_limit or [0.006, DBC_CURVATURE[1]]:
+      result = evaluate(samples, delay=args.delay, horizon=horizon,
+                        tau_load=args.tau_load, tau_unload=args.tau_unload,
+                        horizon_time=args.time_horizon,
+                        assumed_tau_load=args.assumed_tau_load,
+                        assumed_tau_unload=args.assumed_tau_unload,
+                        use_c3=not args.zero_c3,
+                        c2_limit=c2_limit)
+      print(" ".join(f"{key}={value:.8g}" for key, value in result.items()))
+  return 0
+
+
+if __name__ == "__main__":
+  raise SystemExit(main())

tools/ford_pscm_lab/__init__.py

@@ -0,0 +1 @@
+"""Offline Ford candidate verification. No hardware or CAN transmission."""

tools/ford_pscm_lab/feedback_replay.py

@@ -0,0 +1,238 @@
+"""Inspect C1 feedback commands on frozen route measurements, never vehicle motion.
+
+Input: route.npz, model_paths.npz and metadata.json from the full-rlog extractor.
+The recorded desired/actual curvature, clocks, driver input and PSCM flags stay
+fixed. This verifies software behavior, not counterfactual physical tracking.
+"""
+import argparse
+from collections import Counter
+import hashlib
+import inspect
+import json
+from pathlib import Path
+import subprocess
+from types import ModuleType, SimpleNamespace
+
+import numpy as np
+
+from openpilot.selfdrive.controls.lib import ford_model_action
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController, ModelActionController
+from tools.ford_pscm_lab.model_action_replay import WireCheck, field_checks, sample, table, verify_dependency
+
+
+BASELINE = 'a7d70e2b0890184636827351e4789d866f2a7c97'
+FEEDBACK_V2 = '959ae3d6e76c479f48e081c060b0f3569a6f15f4'
+OPENDBC = '64aa61b9b3fd26e70a7caa915acab207ff3cd64a'
+
+
+def original_controller(revision=BASELINE):
+  root = Path(__file__).resolve().parents[2]
+  source = subprocess.check_output(['git', '-C', str(root), 'show',
+                                   f'{revision}:openpilot/selfdrive/controls/lib/ford_model_action.py'], text=True)
+  module = ModuleType('ford_original_v1')
+  exec(compile(source, f'{revision}:ford_model_action.py', 'exec'), module.__dict__)
+  return module.FordModelActionController(), hashlib.sha256(source.encode()).hexdigest()
+
+
+def replay(directory, output, baseline_revision=BASELINE):
+  directory, output = directory.resolve(), output.resolve()
+  if output == directory or directory in output.parents:
+    raise ValueError('Output must be outside the source route directory')
+  verify_dependency(OPENDBC)
+  metadata = json.loads((directory/'metadata.json').read_text())
+  with np.load(directory/'route.npz', allow_pickle=False) as z:
+    r = {k: table(z, k) for k in ('controls', 'cs', 'cc', 'model', 'params', 'pscm')}
+  with np.load(directory/'model_paths.npz', allow_pickle=False) as z:
+    model_ns, paths = z['ns'], z['paths']
+  for stream in r.values():
+    if np.any(np.diff(stream['t']) < 0):
+      raise ValueError('Source stream contains a backward clock')
+  c = r['controls']
+  t = c['t']
+  cs, pa, ps = (sample(r[k], t) for k in ('cs', 'params', 'pscm'))
+  cc = sample(r['cc'], t, nearest=True)
+  mi = np.clip(np.searchsorted(r['model']['ns'], c['model_ns']), 0, len(r['model']['ns'])-1)
+  exact = r['model']['ns'][mi] == c['model_ns']
+  np.testing.assert_array_equal(model_ns, r['model']['ns'])
+  models = [SimpleNamespace(position=SimpleNamespace(x=p[0], y=p[1]), orientation=SimpleNamespace(z=p[2])) for p in paths]
+  old, baseline_hash = original_controller(baseline_revision)
+  old_has_feedback = 'current_curvature' in inspect.signature(old.update).parameters
+  controller, wire_check = FordModelActionController(), WireCheck()
+  baseline = np.zeros((len(t), 4))
+  commands = np.zeros_like(baseline)
+  old_valid = np.zeros(len(t), bool)
+  valid = np.zeros(len(t), bool)
+  correction = np.zeros(len(t))
+  baseline_correction = np.zeros(len(t))
+  feedback_dt = np.zeros(len(t))
+  feedback_enabled = np.zeros(len(t), bool)
+  pscm_limited = np.zeros(len(t), bool)
+  offset_overflow = np.zeros(len(t))
+  reasons = Counter()
+  releases = []
+  for i, now in enumerate(t):
+    model_time = r['model']['t'][mi[i]]
+    service_valid = bool(c['valid'][i] and cc['valid'][i] and cs['valid'][i] and cs['can_valid'][i]
+                         and pa['valid'][i] and r['model']['valid'][mi[i]] and exact[i]
+                         and abs(cc['t'][i]-now) < .005 and 0. <= now-pa['t'][i] <= .15)
+    common = {'speed': cs['speed'][i], 'yaw_rate': cs['yaw'][i], 'now': now,
+              'measurement_time': cs['t'][i], 'model_time': model_time, 'reference_time': model_time,
+              'active': bool(cc['active'][i]), 'valid': service_valid}
+    model = models[mi[i]] if exact[i] else None
+    status = SimpleNamespace(valid=bool(ps['valid'][i] and ps['status_valid'][i]), canMonoTime=round(ps['stamp'][i]*1e9),
+                             limit=int(ps['limit'][i]), lateralState=int(ps['lateral_state'][i]), denied=bool(ps['denied'][i]))
+    feedback = {'current_curvature': c['measured'][i], 'driver_pressed': bool(cs['pressed'][i]),
+                'driver_torque': cs['torque'][i], 'pscm_status': status}
+    previous = old.update(model, c['desired'][i], **common, **(feedback if old_has_feedback else {}))
+    previous_count, previous_correction = controller.core.carryover_release_count, controller.core.correction
+    command = controller.update(model, c['desired'][i], **feedback, **common)
+    for destination, result in ((baseline, previous), (commands, command)):
+      destination[i] = result.path_offset, result.path_angle, result.curvature, result.curvature_rate
+    old_valid[i], valid[i] = previous.valid, command.valid
+    d = controller.diagnostics
+    reasons[d['status']] += 1
+    correction[i] = controller.core.correction
+    baseline_correction[i] = getattr(old.core, 'correction', 0.)
+    feedback_dt[i] = d.get('feedback_dt', 0.)
+    feedback_enabled[i] = d.get('feedback_enabled', False)
+    pscm_limited[i] = d.get('pscm_limited', False)
+    offset_overflow[i] = d.get('offset_overflow', 0.)
+    if controller.core.carryover_release_count > previous_count:
+      releases.append({'time_s': float(now-metadata['t0']), 'correction_before_rad': float(previous_correction),
+                       'correction_after_rad': float(correction[i]), 'base_c1_rad': float(d['heading_feedforward']),
+                       'desired_angle_deg': float(c['desired_angle'][i]), 'actual_angle_deg': float(c['actual_angle'][i]),
+                       'speed_m_s': float(cs['speed'][i]), 'baseline_c0_c1': baseline[i, :2].tolist(),
+                       'candidate_c0_c1': commands[i, :2].tolist()})
+    wire_check.check(command)
+  field_checks(commands, valid, t)
+  np.testing.assert_array_equal(valid, old_valid)
+  assert np.all(correction[~feedback_enabled] == 0.)
+  assert np.all(abs(correction) <= 1.+1e-10)
+  weight = np.minimum(np.diff(t, append=t[-1]+.01), .03)
+  report = {'scope': __doc__, 'baseline_revision': baseline_revision, 'baseline_source_sha256': baseline_hash,
+            'calibration_approved': False, 'cycles': len(t), 'active_cycles': int(valid.sum()),
+            'validity_matches_baseline_exactly': True, 'status_counts': dict(reasons),
+            'c0_matches_baseline_exactly': bool(np.array_equal(commands[:, 0], baseline[:, 0])),
+            'c0_changed_cycles': int((abs(commands[:, 0]-baseline[:, 0]) > 1e-8).sum()),
+            'max_abs_c0_change_m': float(abs(commands[:, 0]-baseline[:, 0]).max()),
+            'offset_overflow_seconds': float(weight[offset_overflow != 0.].sum()),
+            'max_abs_offset_overflow_target_m': float(abs(offset_overflow).max()),
+            'carryover_releases': releases,
+            'feedback_enabled_seconds': float(weight[feedback_enabled].sum()),
+            'pscm_limit_2_seconds': float(weight[pscm_limited & valid].sum()),
+            'c1_changed_cycles': int((abs(commands[:, 1]-baseline[:, 1]) > 1e-8).sum()),
+            'max_abs_c1_change_rad': float(abs(commands[:, 1]-baseline[:, 1]).max()),
+            'max_abs_correction_rad': float(abs(correction).max()), 'can_round_trips': wire_check.count,
+            'source_sha256': {str(p): hashlib.sha256(p.read_bytes()).hexdigest() for p in
+                              (directory/'route.npz', directory/'model_paths.npz', directory/'metadata.json',
+                               Path(__file__).resolve(), Path(ford_model_action.__file__).resolve())},
+            'timing_limit': 'Controls publication time proxies the computation clock; full SubMaster checks are unavailable.',
+            'reference_limit': 'Uses exact consumed model publication as reference; selected maneuver-plan messages are not reconstructed.'}
+  report['example_points'] = []
+  for seconds in (130.937, 235.396, 236.250, 252.493, 330.651, 674.430, 808.408, 876.419, 1534.519, 1562.507):
+    if seconds > t[-1]-metadata['t0']:
+      continue
+    i = int(np.argmin(abs(t-metadata['t0']-seconds)))
+    report['example_points'].append({'time_s': float(t[i]-metadata['t0']), 'old_c0_c1': baseline[i, :2].tolist(),
+                                     'candidate_c0_c1': commands[i, :2].tolist(), 'correction_rad': float(correction[i]),
+                                     'feedback_enabled': bool(feedback_enabled[i]), 'pscm_limited': bool(pscm_limited[i])})
+  output.mkdir(parents=True, exist_ok=True)
+  np.savez_compressed(output/'commands.npz', t=t-metadata['t0'], baseline=baseline, candidate=commands, valid=valid,
+                      correction=correction, baseline_correction=baseline_correction, feedback_dt=feedback_dt,
+                      feedback_enabled=feedback_enabled, pscm_limited=pscm_limited, offset_overflow=offset_overflow)
+  (output/'report.json').write_text(json.dumps(report, indent=2, allow_nan=False)+'\n')
+  print(json.dumps({k: v for k, v in report.items() if k not in ('source_sha256', 'carryover_releases')}
+                   | {'carryover_release_count': len(releases)}, indent=2))
+
+
+def stress(cycles, output):
+  verify_dependency(OPENDBC)
+  rng = np.random.default_rng(20260909)
+  controller, mirror, wire = ModelActionController(), ModelActionController(), WireCheck()
+  old, baseline_hash = original_controller(FEEDBACK_V2)
+  releases = 0
+  unchanged_without_overflow = 0
+  for i in range(cycles):
+    desired, measured = rng.uniform(-.1, .1, 2)
+    speed, dt, offset = rng.uniform(.3, 55.), rng.uniform(.002, .1), rng.uniform(-8., 8.)
+    active, enabled, limited = i % 211 != 0, i % 97 != 0, i % 7 == 0
+    feedback_dt = 0. if i % 5 == 0 else rng.uniform(.002, .15)
+    previous = controller.c0, controller.c1, controller.correction
+    previous_count = controller.carryover_release_count
+    args = {'speed': speed, 'dt': dt, 'feedback_dt': feedback_dt, 'active': active,
+            'feedback_enabled': enabled, 'pscm_limited': limited}
+    def model(y):
+      return SimpleNamespace(position=SimpleNamespace(x=[0., 20.], y=[y, y]), orientation=SimpleNamespace(z=[0., 0.]))
+    out = controller.update(model(offset), desired, current_curvature=measured, **args)
+    other = mirror.update(model(-offset), -desired, current_curvature=-measured, **args)
+    # Clone the pre-update state to isolate this cycle's policy from the
+    # different history that a previous release would otherwise create.
+    old.core.c0, old.core.c1, old.core.correction = previous
+    old.core.carryover_release_count = previous_count
+    baseline_out = old.core.update(model(offset), desired, current_curvature=measured, **args)
+    released = controller.carryover_release_count > previous_count
+    baseline_released = old.core.carryover_release_count > previous_count
+    raw_heading = max(7., speed)*desired
+    overflow = raw_heading-float(np.clip(raw_heading, -.5, .5))
+    if not active or overflow == 0.:
+      assert out == baseline_out
+      assert (controller.c0, controller.c1, controller.correction) == (old.core.c0, old.core.c1, old.core.correction)
+      unchanged_without_overflow += 1
+    if active:
+      expected_c0 = previous[0]+float(np.clip(np.clip(offset+7.*overflow, -5.11, 5.11)-previous[0], -4.*dt, 4.*dt))
+      assert abs(controller.c0-expected_c0) <= 1e-10
+    if released == baseline_released:
+      assert controller.c1 == old.core.c1 and controller.correction == old.core.correction
+    state = controller.c0, controller.c1, controller.correction
+    mirrored = mirror.c0, mirror.c1, mirror.correction
+    np.testing.assert_allclose(state, -np.array(mirrored), rtol=0., atol=1e-10)
+    assert controller.carryover_release_count == mirror.carryover_release_count
+    assert abs(controller.c0) <= 5.11+1e-10 and abs(controller.c1) <= .5+1e-10 and abs(controller.correction) <= 1.+1e-10
+    if active:
+      assert abs(controller.c0-previous[0]) <= 4.*dt+1e-10
+      assert abs(controller.c1-previous[1]) <= .5*dt+1e-10
+      if enabled:
+        releases += released
+        if released:
+          assert feedback_dt > 0. and desired*measured < 0. and previous[2]*desired < 0.
+          assert offset*desired > 0. and controller.c0*desired > 0.
+        delta = controller.correction-(0. if released else previous[2])
+        request = (desired-measured)*speed*feedback_dt
+        assert delta*request >= -1e-10 and abs(delta) <= abs(request)+1e-10
+        assert (controller.correction-previous[2])*request >= -1e-10
+        if limited and request*(measured if measured else previous[1]) > 0.:
+          assert abs(controller.correction) <= abs(previous[2])+1e-10
+          assert controller.correction*previous[2] >= -1e-10
+      else:
+        assert controller.correction == 0.
+    else:
+      assert state == (0., 0., 0.)
+    assert out.curvature == out.curvature_rate == other.curvature == other.curvature_rate == 0.
+    wire.check(out)
+  report = {'cycles': cycles, 'mirrored_updates': cycles, 'can_round_trips': wire.count,
+            'carryover_release_count': releases,
+            'baseline_revision': FEEDBACK_V2, 'baseline_source_sha256': baseline_hash,
+            'exact_unchanged_state_and_commands_without_overflow': unchanged_without_overflow,
+            'checks': 'Mirror symmetry, reset/override, amplitude, slew, correction bounds, carryover direction/confirmation, integration, PSCM limits, CAN.',
+            'scope': 'Numerical software invariants only; no model of vehicle motion.', 'calibration_approved': False,
+            'controller_sha256': hashlib.sha256(Path(ford_model_action.__file__).read_bytes()).hexdigest()}
+  output.parent.mkdir(parents=True, exist_ok=True)
+  output.write_text(json.dumps(report, indent=2)+'\n')
+  print(json.dumps(report, indent=2))
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser(description=__doc__)
+  sub = parser.add_subparsers(dest='mode', required=True)
+  route = sub.add_parser('route')
+  route.add_argument('directory', type=Path)
+  route.add_argument('--output', type=Path, required=True)
+  route.add_argument('--baseline', default=BASELINE, help='Git revision of the original mapping or a feedback controller')
+  random = sub.add_parser('stress')
+  random.add_argument('--cycles', type=int, default=200_000)
+  random.add_argument('--output', type=Path, required=True)
+  args = parser.parse_args()
+  if args.mode == 'route':
+    replay(args.directory, args.output, args.baseline)
+  else:
+    stress(args.cycles, args.output)

tools/ford_pscm_lab/model_action_replay.py

@@ -0,0 +1,224 @@
+"""Check zero-error compatibility on route90/95 original-time extracts.
+
+Measured curvature is deliberately set to the requested curvature in this
+historical compatibility check, so feedback stays zero. This is not a replay
+of the new feedback controller's response to recorded steering measurements.
+
+The historical pass deliberately uses the archived eligibility mask to check
+command compatibility. The separate adapter pass reconstructs input eligibility
+from service records, never from candidate/baseline output validity. Neither
+pass scores counterfactual motion. Source extracts and archived reports are
+read-only; --output selects a separate destination.
+"""
+import argparse
+from collections import Counter
+import hashlib
+import json
+from pathlib import Path
+import subprocess
+from types import SimpleNamespace
+
+import numpy as np
+import opendbc
+from opendbc.can import CANPacker, CANParser
+from opendbc.car.ford.fordcan import CanBus, create_lat_ctl2_msg
+from openpilot.cereal import custom
+from openpilot.selfdrive.controls.lib import ford_model_action
+from openpilot.selfdrive.controls.lib.ford_model_action import FordModelActionController, ModelActionController
+from openpilot.selfdrive.controls.lib.ford_path import _model_path
+
+
+PINNED_OPENDBC = '72a775d35e54c21ff5c5798acef22016eedcc0a7'
+
+
+def revision(directory):
+  return subprocess.check_output(['git', '-C', str(directory), 'rev-parse', 'HEAD'], text=True).strip()
+
+
+def verify_dependency(expected=PINNED_OPENDBC):
+  directory = Path(opendbc.__file__).resolve().parent.parent
+  actual = revision(directory)
+  if actual != expected:
+    raise ValueError(f'Expected opendbc {expected}; imported {directory} at {actual}')
+  return directory
+
+
+def table(raw, name):
+  return dict(zip(raw[name+'_names'], raw[name].T, strict=True))
+
+
+def sample(stream, query, *, nearest=False):
+  if len(stream['t']) == 0 or np.any(np.diff(stream['t']) < 0):
+    raise ValueError('Replay requires nonempty streams in original timestamp order')
+  if nearest:
+    right = np.clip(np.searchsorted(stream['t'], query), 0, len(stream['t'])-1)
+    left = np.maximum(right-1, 0)
+    index = np.where(abs(stream['t'][right]-query) < abs(stream['t'][left]-query), right, left)
+  else:
+    index = np.clip(np.searchsorted(stream['t'], query, side='right')-1, 0, len(stream['t'])-1)
+  return {key: values[index] for key, values in stream.items()}
+
+
+def field_checks(command, valid, t):
+  assert np.isfinite(command).all()
+  assert (abs(command[:, :2]) <= [5.1100001, .5000001]).all()
+  assert (command[:, 2:] == 0.).all()
+  assert (command[~valid] == 0.).all()
+  dt = np.r_[.01, np.diff(t)]
+  consecutive = valid[1:] & valid[:-1]
+  assert (abs(np.diff(command[:, :2], axis=0))[consecutive] <=
+          (dt[1:, None]*[4., .5]+[.0100001, .0005001])[consecutive]).all()
+  return True
+
+
+class WireCheck:
+  """Real Float32 publication and in-memory CAN round trips on every cycle."""
+  def __init__(self):
+    self.packer = CANPacker('ford_lincoln_base_pt')
+    self.parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], 0)
+    self.bus = CanBus(fingerprint={0: {}})
+    self.count = 0
+
+  def check(self, path):
+    msg = custom.CarControlSP.new_message()
+    msg.fordLateralPath.valid = path.valid
+    msg.fordLateralPath.pathOffset = path.path_offset
+    msg.fordLateralPath.pathAngle = path.path_angle
+    msg.fordLateralPath.curvature = path.curvature
+    msg.fordLateralPath.curvatureRate = path.curvature_rate
+    p = msg.fordLateralPath
+    counter = self.count % 16
+    packet = create_lat_ctl2_msg(self.packer, self.bus, 2 if path.valid else 0,
+                                -p.pathOffset, -p.pathAngle, -p.curvature, -p.curvatureRate, counter)
+    self.count += 1
+    # Synthetic parser clock only; input times and gaps are never resampled.
+    self.parser.update([self.count*10_000_000, [packet]])
+    decoded = self.parser.vl['LateralMotionControl2']
+    assert abs(decoded['LatCtlPathOffst_L_Actl']+path.path_offset) < 1e-9
+    assert abs(decoded['LatCtlPath_An_Actl']+path.path_angle) < 1e-9
+    assert decoded['LatCtlCurv_No_Actl'] == decoded['LatCtlCrv_NoRate2_Actl'] == 0.
+    assert decoded['LatCtl_D2_Rq'] == (2 if path.valid else 0)
+    assert decoded['LatCtlPath_No_Cnt'] == counter
+
+
+def run(directory, output):
+  directory, output = directory.resolve(), output.resolve()
+  if output == directory or directory in output.parents:
+    raise ValueError('Output must be outside the source route directory')
+  dependency = verify_dependency()
+  with np.load(directory/'route.npz', allow_pickle=False) as raw:
+    streams = {name: table(raw, name) for name in ('controls', 'cs', 'cc', 'model', 'params', 'path')}
+    if len(raw['maneuver']):
+      raise ValueError('This extract cannot identify the selected maneuver service per cycle; use the integration tests for that source')
+    models = [SimpleNamespace(position=SimpleNamespace(x=p[1], y=p[2]), orientation=SimpleNamespace(z=p[3])) for p in raw['model_paths']]
+  with np.load(directory/'encoder_comparison.npz', allow_pickle=False) as archive:
+    baseline = {key: archive[key] for key in ('t', 'valid', 'action_heading')}
+  with np.load(directory/'pose_candidate/pose_replay.npz', allow_pickle=False) as pose:
+    np.testing.assert_array_equal(pose['t'], baseline['t'])
+    clean = pose['clean']
+  controls = streams['controls']
+  t = controls['t']
+  np.testing.assert_array_equal(t, baseline['t'])
+  cs, params = (sample(streams[name], t) for name in ('cs', 'params'))
+  cc = sample(streams['cc'], t, nearest=True)  # same-cycle publication match, never a motion sample
+  mi = np.clip(np.searchsorted(streams['model']['ns'], controls['model_ns']), 0, len(models)-1)
+  model = {key: values[mi] for key, values in streams['model'].items()}
+  exact = model['ns'] == controls['model_ns']
+  services_valid = ((controls['valid'] == 1) & (cc['valid'] == 1) & (abs(cc['t']-t) < .005) &
+                    (cs['valid'] == 1) & (cs['can_valid'] == 1) & (params['valid'] == 1) &
+                    (t-params['t'] >= 0.) & (t-params['t'] <= .15) & exact & (model['valid'] == 1))
+  dt = np.r_[.01, np.diff(t)]
+  core, entry_clock_core, adapter, wire = ModelActionController(), ModelActionController(), FordModelActionController(), WireCheck()
+  commands = np.zeros((len(t), 4))
+  adapted = np.zeros_like(commands)
+  valid = np.zeros(len(t), bool)
+  adapter_valid = np.zeros_like(valid)
+  reasons = Counter()
+  for i, now in enumerate(t):
+    selected_model = models[mi[i]] if exact[i] else None
+    old_gate = core.update(selected_model, controls['desired'][i], current_curvature=controls['desired'][i],
+                           speed=cs['speed'][i], dt=dt[i], active=bool(baseline['valid'][i]))
+    commands[i] = old_gate.path_offset, old_gate.path_angle, old_gate.curvature, old_gate.curvature_rate
+    valid[i] = old_gate.valid
+    wire.check(old_gate)
+    new_gate = adapter.update(selected_model, controls['desired'][i], current_curvature=controls['desired'][i],
+                              speed=cs['speed'][i], yaw_rate=cs['yaw'][i], now=now,
+                              measurement_time=cs['t'][i], model_time=model['t'][i], reference_time=model['t'][i],
+                              active=bool(cc['active'][i]), valid=bool(services_valid[i]))
+    adapted[i] = new_gate.path_offset, new_gate.path_angle, new_gate.curvature, new_gate.curvature_rate
+    adapter_valid[i] = new_gate.valid
+    reasons[adapter.diagnostics['status']] += 1
+    wire.check(new_gate)
+    # Isolate the adapter's fresh 10 ms engagement tick from the archived
+    # harness, which used the preceding publication interval even on engage.
+    entry_dt = dt[i] if i > 0 and baseline['valid'][i-1] else .01
+    expected_adapter = entry_clock_core.update(selected_model, controls['desired'][i], current_curvature=controls['desired'][i],
+                                               speed=cs['speed'][i], dt=entry_dt,
+                                               active=bool(baseline['valid'][i]))
+    assert new_gate == expected_adapter, f'Unexplained adapter difference at cycle {i}'
+  np.testing.assert_array_equal(valid, baseline['valid'])
+  np.testing.assert_array_equal(commands[:, :2], baseline['action_heading'])
+  field_checks(commands, valid, t)
+  field_checks(adapted, adapter_valid, t)
+
+  # Recompute the archived cohorts from actual commands, retaining the original
+  # interval-clean driver mask and time weights. No recorded yaw performance score.
+  v = cs['speed']
+  demand = abs(controls['desired'])*v**2
+  masks = {'small_request': clean & (demand < .15), 'turn': clean & (demand >= .5)}
+  for low, high in ((2, 8), (8, 15), (15, 55)):
+    for name in ('small', 'turn'):
+      masks[f'{name}_speed_{low}_{high}'] = masks['small_request' if name == 'small' else name] & (v >= low) & (v < high)
+  paths = [_model_path(m) for m in models]
+  y10 = np.array([np.interp(10., p[0], p[2]) if p is not None else np.nan for p in paths])
+  h10 = np.array([np.interp(10., p[0], p[3]) if p is not None else np.nan for p in paths])
+  coverage = np.array([p[0][-1] if p is not None else 0. for p in paths])[mi]
+  masks['pose_quiet'] = masks['small_request'] & (v >= 8) & (abs(y10[mi]) <= .1) & (abs(h10[mi]) <= np.radians(.5))
+  recorded = sample(streams['path'], t, nearest=True)
+  recorded = np.column_stack((recorded['c0'], recorded['c1']))
+  weight = np.minimum(np.diff(t, append=t[-1]+.01), .03)
+  cohorts = {}
+  previous_report = json.loads((directory/'encoder_comparison.json').read_text())
+  for name, mask in masks.items():
+    def rms(values, selected=mask):
+      return np.sqrt(np.average(values[selected, :2]**2, weights=weight[selected], axis=0)).tolist() if selected.any() else None
+    cohorts[name] = {'seconds': float(weight[mask].sum()), 'core_c0_c1_rms': rms(commands), 'recorded_v8_c0_c1_rms': rms(recorded),
+                     'adapter_eligible_seconds': float(weight[mask & adapter_valid].sum()),
+                     'adapter_c0_c1_rms': rms(adapted, mask & adapter_valid)}
+    expected = previous_report['cohorts'][name]
+    np.testing.assert_allclose(cohorts[name]['seconds'], expected['seconds'], rtol=0., atol=1e-8)
+    np.testing.assert_allclose(cohorts[name]['core_c0_c1_rms'], expected['candidates']['action_heading']['c0_c1_rms'], rtol=0., atol=1e-12)
+    np.testing.assert_allclose(cohorts[name]['recorded_v8_c0_c1_rms'], expected['v8_c0_c1_rms'], rtol=0., atol=1e-12)
+  root = Path(__file__).resolve().parents[2]
+  sources = [Path(__file__), Path(ford_model_action.__file__),
+             root/'openpilot/selfdrive/controls/lib/ford_path.py', directory/'route.npz', directory/'metadata.json',
+             directory/'encoder_comparison.npz', directory/'encoder_comparison.json', directory/'pose_candidate/pose_replay.npz']
+  report = {'scope': 'Zero-error compatibility only: measured curvature is set to requested curvature. No physical tracking score.',
+            'calibration_approved': False, 'executes_live_selector': False, 'cycles': len(t),
+            'core_active_cycles': int(valid.sum()), 'core_exact_archived_match': True, 'cohorts_reproduced': True,
+            'adapter_active_cycles': int(adapter_valid.sum()), 'adapter_status_counts': dict(reasons),
+            'adapter_exact_match_with_fresh_engagement_dt': True,
+            'core_active_path_shorter_than_7m_cycles': int(np.sum(valid & (coverage < 7.))),
+            'adapter_validity_differs_from_archive_cycles': int(np.sum(adapter_valid != valid)),
+            'adapter_command_differs_from_archive_cycles': int(np.any(abs(adapted-commands) > 1e-9, axis=1).sum()),
+            'adapter_max_absolute_command_difference_c0_c1': np.max(abs(adapted[:, :2]-commands[:, :2]), axis=0).tolist(),
+            'field_slew_zero_c2_c3_pass': True, 'float32_can_round_trips': wire.count,
+            'timing': 'Original controls publication timestamps proxy computation time; repeated frames and gaps retained. No identified delay.',
+            'eligibility': 'Adapter checks recorded services independently; full SubMaster health is unavailable. Core uses archived validity.',
+            'reference': 'Recorded controlsState.desiredCurvature, already selected/limited. These two routes have no maneuver publications.',
+            'host_yaw': 'Extract cs.yaw already equals -carState.yawRate. Used only for inherited finite/range gate, never feedback.',
+            'cohorts': cohorts, 'workspace_head': revision(root), 'opendbc_import_head': revision(dependency),
+            'opendbc_import_path': str(dependency),
+            'source_sha256': {str(p.resolve()): hashlib.sha256(p.read_bytes()).hexdigest() for p in sources}}
+  output.mkdir(parents=True, exist_ok=True)
+  np.savez_compressed(output/'commands.npz', t=t, core=commands, core_valid=valid, adapter=adapted, adapter_valid=adapter_valid)
+  (output/'report.json').write_text(json.dumps(report, indent=2, allow_nan=False)+'\n')
+  print(json.dumps({k: v for k, v in report.items() if k not in ('cohorts', 'source_sha256')}, indent=2))
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser(description=__doc__)
+  parser.add_argument('route_directory', type=Path)
+  parser.add_argument('--output', type=Path, required=True)
+  args = parser.parse_args()
+  run(args.route_directory, args.output)

tools/ford_pscm_lab/stress_model_action.py

@@ -0,0 +1,131 @@
+"""Zero-error numerical stress and exhaustive field-boundary CAN checks.
+
+Measured curvature equals requested curvature here to preserve the independent
+feedforward oracle. Feedback behavior is covered by its own tests and replay.
+
+Analytic straight/rotated paths supply an independent y(7) oracle. The
+reference slew uses scalar arithmetic. Packing is checked against direct
+Float32/CAN packing of the continuous state, independently of host _packed.
+No synthetic plant is fitted or used to claim vehicle tracking performance.
+"""
+import argparse
+import hashlib
+import json
+import math
+from pathlib import Path
+from types import SimpleNamespace
+
+import numpy as np
+
+from openpilot.cereal import custom
+from openpilot.selfdrive.controls.lib import ford_model_action
+from openpilot.selfdrive.controls.lib.ford_model_action import ModelActionController
+from opendbc.car.ford.fordcan import create_lat_ctl2_msg
+from tools.ford_pscm_lab.model_action_replay import PINNED_OPENDBC, WireCheck, verify_dependency, revision
+
+
+def line(offset, heading=0.):
+  s = np.linspace(0., 30., 33)
+  return SimpleNamespace(position=SimpleNamespace(x=s*math.cos(heading), y=offset+s*math.sin(heading)),
+                         orientation=SimpleNamespace(z=np.full_like(s, heading)))
+
+
+def check_raw_packing(wire, controller, path):
+  # Set a raw Float32 publication independently of the host quantization helper.
+  msg = custom.CarControlSP.new_message()
+  msg.fordLateralPath.pathOffset = controller.c0
+  msg.fordLateralPath.pathAngle = controller.c1
+  raw = create_lat_ctl2_msg(wire.packer, wire.bus, 2 if path.valid else 0, -msg.fordLateralPath.pathOffset,
+                            -msg.fordLateralPath.pathAngle, 0., 0., wire.count % 16)
+  wire.check(path)
+  wire.parser.update([wire.count*10_000_000, [raw]])
+  decoded = wire.parser.vl['LateralMotionControl2']
+  assert abs(decoded['LatCtlPathOffst_L_Actl']+path.path_offset) < 1e-9
+  assert abs(decoded['LatCtlPath_An_Actl']+path.path_angle) < 1e-9
+
+
+def run(cycles, seed, output, opendbc_revision=PINNED_OPENDBC):
+  dependency = verify_dependency(opendbc_revision)
+  if cycles < 1:
+    raise ValueError('cycles must be positive')
+  rng = np.random.default_rng(seed)
+  controller, mirrored, wire = ModelActionController(), ModelActionController(), WireCheck()
+  c0 = c1 = 0.
+  resets = 0
+  rates = (4., .5)
+  dt_values = (.002, .003, .01, .013, .05, .1)
+  max_continuous_step = np.zeros(2)
+  for i in range(cycles):
+    offset, heading = float(rng.uniform(-8., 8.)), float(rng.uniform(-1.2, 1.2))
+    speed = float(rng.uniform(.3, 55.))
+    desired = float(rng.uniform(-.15, .15))
+    dt = dt_values[i % len(dt_values)]
+    active = i % 137 != 0
+    valid = i % 211 != 0
+    if i % 307 == 0:
+      dt = .101
+    model, mirror = line(offset, heading), line(-offset, -heading)
+    if i % 401 == 0:
+      model.position.y[4] = mirror.position.y[4] = math.nan
+    out = controller.update(model, desired, current_curvature=desired, speed=speed, dt=dt, active=active, valid=valid)
+    other = mirrored.update(mirror, -desired, current_curvature=-desired, speed=speed, dt=dt, active=active, valid=valid)
+    expected_valid = active and valid and dt <= .1 and i % 401 != 0
+    assert out.valid == other.valid == expected_valid
+    previous = np.array([c0, c1])
+    if expected_valid:
+      raw_heading = max(7., speed)*desired
+      limited_heading = max(-.5, min(.5, raw_heading))
+      target = (max(-5.11, min(5.11, offset+7.*math.sin(heading)+7.*(raw_heading-limited_heading))), limited_heading)
+      c0 += max(-4.*dt, min(4.*dt, target[0]-c0))
+      c1 += max(-.5*dt, min(.5*dt, target[1]-c1))
+      step = abs(np.array([controller.c0, controller.c1])-previous)
+      assert (step <= np.array(rates)*dt+1e-10).all()
+      max_continuous_step = np.maximum(max_continuous_step, step)
+    else:
+      c0 = c1 = 0.
+      resets += 1
+      assert out.path_offset == out.path_angle == 0.
+    assert abs(controller.c0-c0) < 1e-10 and abs(controller.c1-c1) < 1e-10
+    assert abs(controller.c0+mirrored.c0) < 1e-10 and abs(controller.c1+mirrored.c1) < 1e-10
+    assert abs(out.path_offset+other.path_offset) <= .0100001
+    assert abs(out.path_angle+other.path_angle) <= .0005001
+    assert out.curvature == out.curvature_rate == other.curvature == other.curvature_rate == 0.
+    check_raw_packing(wire, controller, out)
+
+  # Every representable host C0/C1 value, plus the float32 immediately below,
+  # at, and above each half-quantum transition. Seed the slew positions only
+  # here to isolate packing from slew; the sequence above checks actual slew.
+  boundary_cases = 0
+  for field, resolution, low, high in ((0, .01, -5.11, 5.11), (1, .0005, -.5, .5)):
+    grid = np.arange(round(low/resolution), round(high/resolution)+1)*resolution
+    for value in np.r_[grid, (grid[:-1]+grid[1:])/2.]:
+      raw = np.float32(value)
+      for scalar in (np.nextafter(raw, np.float32(-np.inf)), raw, np.nextafter(raw, np.float32(np.inf))):
+        selected = float(np.clip(scalar, low, high))
+        offset, heading = (selected, 0.) if field == 0 else (0., selected)
+        controller.c0, controller.c1 = offset, heading
+        out = controller.update(line(offset), heading/20., current_curvature=heading/20., speed=20., dt=.01)
+        check_raw_packing(wire, controller, out)
+        boundary_cases += 1
+  report = {'seed': seed, 'random_cycles': cycles, 'mirrored_core_updates': cycles,
+            'invalid_or_inactive_resets': resets, 'field_boundary_cases': boundary_cases,
+            'float32_can_round_trips': wire.count, 'analytic_targets_scalar_slew_and_mirror_checks_pass': True,
+            'direct_raw_float32_packing_matches_host_output': True, 'max_continuous_step_c0_c1': max_continuous_step.tolist(),
+            'calibration_approved': False, 'scope': 'Zero-error numerical construction: measured equals requested curvature. No PSCM response claims.',
+            'opendbc_import_head': revision(dependency),
+            'source_sha256': {str(p.resolve()): hashlib.sha256(p.read_bytes()).hexdigest() for p in
+                              (Path(__file__), Path(ford_model_action.__file__), Path(__file__).with_name('model_action_replay.py'))}}
+  output.parent.mkdir(parents=True, exist_ok=True)
+  output.write_text(json.dumps(report, indent=2, allow_nan=False)+'\n')
+  print(json.dumps({k: v for k, v in report.items() if k != 'source_sha256'}, indent=2))
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser(description=__doc__)
+  parser.add_argument('--cycles', type=int, default=200_000)
+  parser.add_argument('--seed', type=int, default=20260907)
+  parser.add_argument('--output', type=Path, required=True)
+  parser.add_argument('--opendbc-revision', default=PINNED_OPENDBC,
+                      help='Exact required dependency commit; defaults to the historical replay pin.')
+  args = parser.parse_args()
+  run(args.cycles, args.seed, args.output, args.opendbc_revision)

tools/ford_pscm_lab/test_model_action_replay.py

@@ -0,0 +1,62 @@
+import numpy as np
+import pytest
+
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+from tools.ford_pscm_lab import model_action_replay as replay
+
+
+def test_service_sampling_keeps_original_gaps_and_never_pulls_future_inputs():
+  stream = {'t': np.array([1., 1.01, 2.]), 'value': np.array([3., 4., 5.])}
+  sampled = replay.sample(stream, np.array([1.005, 1.5, 2.]))
+  np.testing.assert_array_equal(sampled['t'], [1., 1.01, 2.])
+  np.testing.assert_array_equal(sampled['value'], [3., 4., 5.])
+  assert 1.5-sampled['t'][1] > .15  # The adapter sees the gap, not a resampled fresh input.
+
+
+@pytest.mark.parametrize('times', [[], [1., .9]])
+def test_replay_does_not_sort_away_backward_time_or_invent_missing_streams(times):
+  with pytest.raises(ValueError):
+    replay.sample({'t': np.array(times)}, np.array([1.]))
+
+
+def test_dependency_mismatch_fails_before_replaying(monkeypatch):
+  monkeypatch.setattr(replay, 'revision', lambda _: 'wrong_revision')
+  with pytest.raises(ValueError, match='Expected opendbc'):
+    replay.verify_dependency()
+
+
+def test_explicit_stress_dependency_still_requires_an_exact_match(monkeypatch):
+  monkeypatch.setattr(replay, 'revision', lambda _: 'deployment_commit')
+  replay.verify_dependency('deployment_commit')
+  with pytest.raises(ValueError, match='Expected opendbc'):
+    replay.verify_dependency('different_commit')
+  with pytest.raises(ValueError, match='Expected opendbc'):
+    replay.verify_dependency()  # Historical replay never silently follows the local checkout.
+
+
+def test_source_route_directory_cannot_be_overwritten(tmp_path):
+  with pytest.raises(ValueError, match='outside the source'):
+    replay.run(tmp_path, tmp_path/'selected_controller')
+
+
+@pytest.mark.parametrize('field,value', [(0, 5.12), (1, .501), (2, .00002), (3, .000001), (0, np.nan)])
+def test_field_validation_catches_range_and_zero_c2_c3_violations(field, value):
+  command = np.zeros((2, 4))
+  command[0, field] = value
+  with pytest.raises(AssertionError):
+    replay.field_checks(command, np.array([True, True]), np.array([1., 1.01]))
+
+
+def test_invalid_cycles_cannot_publish_a_retained_command():
+  with pytest.raises(AssertionError):
+    replay.field_checks(np.array([[.01, 0., 0., 0.]]), np.array([False]), np.array([1.]))
+
+
+def test_field_validation_catches_excessive_slew_with_original_dt():
+  with pytest.raises(AssertionError):
+    replay.field_checks(np.array([[0., 0., 0., 0.], [.08, 0., 0., 0.]]), np.array([True, True]), np.array([1., 1.01]))
+
+
+def test_wire_validator_checks_real_curvature_fields_instead_of_filling_them_with_zero():
+  with pytest.raises(AssertionError):
+    replay.WireCheck().check(FordPath(True, 0., 0., .001, 0.))

tools/ford_pscm_lab/upstream_fallback_check.py

@@ -0,0 +1,97 @@
+"""Compare all outgoing Ford packets with pinned upstream and custom senders.
+
+Uses trusted local Git sources, identical synthetic inputs, and the actual CAN
+packers. Establishes software equivalence, not physical steering performance.
+"""
+import argparse
+from collections import defaultdict
+import hashlib
+import json
+from pathlib import Path
+import subprocess
+from types import ModuleType, SimpleNamespace
+
+import numpy as np
+import opendbc
+from opendbc.car import structs
+from opendbc.car.ford.carcontroller import CarController
+from opendbc.car.ford.interface import CarInterface
+from opendbc.car.ford.values import CAR, DBC, FordFlags
+
+
+UPSTREAM = 'f95f996f5917dcbbf2e32fe51b606a24cf836af6'
+PREVIOUS_CUSTOM = 'c21a9013700734dd20b09e05aa68329ad8cc20f9'
+
+
+def reference(directory, revision):
+  modules, hashes = {}, {}
+  for name in ('fordcan', 'carcontroller'):
+    path = f'opendbc/car/ford/{name}.py'
+    source = subprocess.check_output(['git', '-C', str(directory), 'show', f'{revision}:{path}'], text=True)
+    module = ModuleType(f'ford_reference_{name}')
+    exec(compile(source, f'{revision}:{path}', 'exec'), module.__dict__)
+    modules[name] = module
+    hashes[path] = hashlib.sha256(source.encode()).hexdigest()
+  modules['carcontroller'].fordcan = modules['fordcan']
+  return modules['carcontroller'].CarController, hashes
+
+
+def run(cycles, output):
+  if cycles < 1:
+    raise ValueError('cycles per platform must be positive')
+  directory = Path(opendbc.__file__).resolve().parent.parent
+  upstream, upstream_hashes = reference(directory, UPSTREAM)
+  previous, previous_hashes = reference(directory, PREVIOUS_CUSTOM)
+  rng = np.random.default_rng(20260911)
+  results = []
+  for fingerprint in CAR:
+    cp = CarInterface.get_non_essential_params(fingerprint)
+    cp_sp = CarInterface.get_non_essential_params_sp(cp, fingerprint)
+    for enabled in (False, True) if cp.flags & FordFlags.CANFD else (False,):
+      candidate = CarController(DBC[fingerprint], cp, cp_sp)
+      baseline = (previous if enabled else upstream)(DBC[fingerprint], cp, cp_sp)
+      cc, cc_sp = structs.CarControl(), structs.CarControlSP()
+      cc_sp.fordLateralPath.enabled = enabled
+      vehicle = SimpleNamespace(out=structs.CarState(), buttons_stock_values=defaultdict(int),
+                                acc_tja_status_stock_values=defaultdict(int), lkas_status_stock_values=defaultdict(int))
+      packets_checked = 0
+      for frame in range(cycles):
+        cc.latActive = frame % 97 < 75
+        cc.actuators.curvature = float(rng.uniform(-.08, .08))
+        speed = (0., .3, 5., 9., 9.001, 10., 35., 55.)[frame % 8] if frame % 3 else float(rng.uniform(0., 55.))
+        vehicle.out.vEgo = vehicle.out.vEgoRaw = speed
+        vehicle.out.yawRate = float(rng.uniform(-1., 1.))
+        # Disabled selection must ignore even valid nonzero custom commands.
+        path = cc_sp.fordLateralPath
+        path.valid = frame % 31 != 0
+        path.pathOffset = float(rng.uniform(-5.11, 5.11))
+        path.pathAngle = float(rng.uniform(-.5, .5))
+        path.curvature = float(rng.uniform(-.02, .02))
+        path.curvatureRate = float(rng.uniform(-.001, .001))
+        actual, actual_can = candidate.update(cc.as_reader(), cc_sp, vehicle, frame*10_000_000)
+        expected, expected_can = baseline.update(cc.as_reader(), cc_sp, vehicle, frame*10_000_000)
+        assert actual_can == expected_can, (fingerprint, enabled, frame, actual_can, expected_can)
+        assert actual.to_dict() == expected.to_dict(), (fingerprint, enabled, frame)
+        packets_checked += len(actual_can)
+      results.append({'fingerprint': str(fingerprint), 'custom_enabled': enabled, 'cycles': cycles,
+                      'identical_packets': packets_checked})
+  report = {'scope': __doc__, 'seed': 20260911, 'upstream_revision': UPSTREAM,
+            'previous_custom_revision': PREVIOUS_CUSTOM, 'upstream_source_sha256': upstream_hashes,
+            'previous_custom_source_sha256': previous_hashes, 'results': results,
+            'total_cycles': sum(r['cycles'] for r in results),
+            'total_identical_packets': sum(r['identical_packets'] for r in results),
+            'candidate_source_sha256': {str(p.relative_to(directory)): hashlib.sha256(p.read_bytes()).hexdigest() for p in
+                                        (directory/'opendbc/car/ford/carcontroller.py', directory/'opendbc/car/ford/fordcan.py',
+                                         directory/'opendbc/car/structs.py')},
+            'checker_sha256': hashlib.sha256(Path(__file__).read_bytes()).hexdigest()}
+  output.parent.mkdir(parents=True, exist_ok=True)
+  output.write_text(json.dumps(report, indent=2)+'\n')
+  print(json.dumps(report, indent=2))
+
+
+if __name__ == '__main__':
+  parser = argparse.ArgumentParser(description=__doc__)
+  parser.add_argument('--cycles', type=int, default=5000, help='Control cycles per platform and selection')
+  parser.add_argument('--output', type=Path, required=True)
+  args = parser.parse_args()
+  run(args.cycles, args.output)