Compare commits

..

307 Commits

Author SHA1 Message Date
Jason Wen 7a9099818f Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-08-14 17:57:37 -04:00
Jason Wen ef4fa48f33 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-08-14 17:18:06 -04:00
Jason Wen e426ced4c0 bump 2026-08-11 17:47:18 -04:00
Jason Wen 7681ba763b Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-08-11 17:47:12 -04:00
Jason Wen b04d666a68 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-08-10 04:27:58 -04:00
Jason Wen fb026b86a3 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-08-06 21:58:57 -04:00
Jason Wen cff4c5e589 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-08-06 21:58:50 -04:00
Jason Wen e0cca951f3 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-07-25 08:52:04 -04:00
Jason Wen 2439c048ed Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-07-20 15:12:17 -04:00
Jason Wen 7b54d7d7a0 bump 2026-07-20 09:51:59 -04:00
Jason Wen b2bdb5787f Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
#	openpilot/tools/plotjuggler/layouts/analyzing-panda-block-angle-hkg.xml
#	openpilot/tools/plotjuggler/layouts/analyzing-torque-angle-hkg.xml
#	openpilot/tools/plotjuggler/layouts/hkg_angle_control.xml
#	openpilot/tools/plotjuggler/layouts/safety-limits-angle-kkg.xml
#	pyproject.toml
#	scripts/lint/lint.sh
2026-07-20 09:50:52 -04:00
Jason Wen 282f517b78 upstream changes 2026-06-09 00:18:40 -04:00
Jason Wen 1779144ff9 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
#	scripts/lint/lint.sh
2026-06-08 23:53:43 -04:00
Jason Wen 54fb2750ba Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-05-09 11:47:25 -04:00
DevTekVE 14431ab77f Merge branch 'master' into hkg-angle-steering-2025 2026-05-05 10:37:34 +02:00
Jason Wen 9d45db41b3 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
#	system/version.py
2026-05-03 16:08:40 -04:00
Jason Wen b57c593d92 bump 2026-04-20 23:31:05 -04:00
nayan 0674c42866 good bot
fix state
2026-04-19 08:52:19 +02:00
nayan 1f7bcf246a Bringing sl change to validate 2026-04-18 09:25:12 +02:00
DevTekVE b0512dc523 Revert "safety: dynamically relax lateral jerk limits during accel conflicts"
This reverts commit b0644a37e3b5a7b941bd4347f4c7ef0f25f44fbc.
2026-04-12 11:25:31 +02:00
DevTekVE cd88fd3850 Bringing shane's improvements on the angle steering branch 2026-04-10 12:09:12 +02:00
DevTekVE ff78eaeba1 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-04-10 11:38:19 +02:00
DevTekVE 92c8aeeb92 lint 2026-04-10 11:34:29 +02:00
DevTekVE ecaa20e7be Add source map configuration to VSCode launch settings
- Enables better debugging by mapping sources to `${workspaceFolder}/opendbc/safety`.
2026-04-05 15:10:21 +02:00
DevTekVE 859c98c9d8 Refactor PlotJuggler layouts and optimize custom math equations
- Introduced new tabs for `Smoothing and Torque ceilings`.
- Updated custom math equations for cleaner logic and added new snippets for angle smoothing, ceiling brackets, and roll compensation.
2026-04-05 12:14:13 +02:00
DevTekVE 69cbe8c6ed Enhance torque reduction logic with speed and steering error adjustments
- Introduced speed-dependent and error-sensitive dynamic torque ceilings.
- Improved interpolation for smoother torque application.
2026-04-04 11:55:14 +02:00
DevTekVE 1aafe92fc0 Remove hyundai_canfd_ccnc.dbc and update dependencies
- Deleted `_hyundai_canfd_ccnc.dbc` and its import references across related files.
- Merged relevant signals and comments into `hyundai_canfd_og.dbc` for consolidated usage.
- Cleaned up obsolete imports in `hyundai_canfd.dbc`.
2026-04-04 08:46:09 +02:00
DevTekVE adb6b9fb12 Test changing priority for reading dbc files to in memory first 2026-04-04 08:29:57 +02:00
DevTekVE f67a9f4624 Revised steering angle smoothing matrix and logic cleanup
- Adjusted `SMOOTHING_ANGLE_VEGO_MATRIX` to refine torque smoothing at mid-range speeds.
- Removed unused deadzone logic for cleaner and more consistent angle smoothing.
2026-04-03 18:10:05 +02:00
DevTekVE 094e834ac4 cleanup: remove unused datafile references and expand ignored patterns
- Deleted `<previouslyLoaded_Datafiles>` sections from PlotJuggler layouts to streamline configuration files.
- Added `.ipynb` files to the `pyproject.toml` ignore list for cleaner tooling.
2026-04-03 17:19:18 +02:00
DevTekVE e4067060b9 Adding ioniq 9 and updating ioniq 5 pe n-line fingerprint 2026-04-03 17:06:15 +02:00
DevTekVE 86a14640b5 Tune speed-dependent steering smoothing to eliminate EPS whine
Reimplemented an Exponential Moving Average (EMA) filter on the requested
steering angle (`apply_angle`). The model's raw high-frequency micro-corrections
at low speeds cause acoustic resonance (whine) in the EPS motor. This filter
dynamically adjusts the smoothing factor (alpha) based on vehicle speed to
silence the EPS at a crawl while maintaining zero-latency precision on the highway.

Key Behaviors & Speed Matrix:
* Deadzone: Ignores angle changes ≤ 0.1° to preserve straight-line tracking.
* 0 km/h (0 mph) -> Alpha: 0.05 (Max smoothing to eliminate stationary vibration)
* 30.6 km/h (19 mph) -> Alpha: 0.10 (Heavy smoothing for stable residential turning)
* 39.6 km/h (25 mph) -> Alpha: 0.30 (Moderate smoothing)
* 49.7 km/h (31 mph) -> Alpha: 0.60 (Light smoothing for responsive city driving)
* 80.0 km/h (50 mph) -> Alpha: 1.00 (Zero smoothing / raw signal for high-speed precision)
2026-04-03 16:13:05 +02:00
DevTekVE 59fb84f0d5 Remove HKG angle control tuning components and dependencies
- Deleted HKG-specific angle tuning settings and related UI elements.
    - Removed tuning parameter handling and smoothing logic from carcontroller.
    - Simplifies codebase and eliminates unused parameters.
2026-04-03 15:33:57 +02:00
DevTekVE 78de201ce7 Bring it back to 360 for hda1s 2026-04-03 15:14:37 +02:00
DevTekVE 17e49f69cc refactor: update parameterized tests and extend Hyundai Ioniq 5 PE model years
- Replaced `parameterized.expand` with new `parameterized` syntax for cleaner test definitions.
- Added 2026 model year to Hyundai Ioniq 5 PE in `car_list.json`.
2026-04-03 14:39:45 +02:00
DevTekVE bec75ebdd8 remove: TorqueReductionGainController and its associated tests
- Fully deprecates the no longer used torque reduction logic.
- Cleans up outdated functionality for clarity and maintainability.
2026-04-03 14:14:07 +02:00
DevTekVE 473832efa7 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-04-03 14:00:54 +02:00
DevTekVE 2cceeb3552 fix: clip steering angle to respect angle limits when latActive is off
- Prevents potential out-of-bound steering angle values.
- Ensures compliance with defined steering angle constraints.
2026-04-03 01:06:37 +02:00
DevTekVE 923a47f713 Reverting all the new control changes until we properly test them on a few variants to ensure it is safe.
Revert "upstream pending tune"

This reverts commit b51d9af9a0.

Revert "show torque reduction gain"

This reverts commit ded0b506d6.

Revert "must gate"

This reverts commit 8b60649eed.

Revert "bump"

This reverts commit 221c219fca.

Revert "temp: comment out blind-spot monitoring signals due to DBC changes"

This reverts commit 790a762a05.
2026-04-01 09:29:53 +02:00
DevTekVE 790a762a05 temp: comment out blind-spot monitoring signals due to DBC changes
- Avoided crash caused by missing signals in updated DBC definitions.
- Added a TODO to revisit and validate blind-spot logic.
2026-04-01 08:55:26 +02:00
Jason Wen 221c219fca bump 2026-03-31 21:57:58 -04:00
Jason Wen 8b60649eed must gate 2026-03-31 21:42:06 -04:00
Jason Wen ded0b506d6 show torque reduction gain 2026-03-31 07:46:13 -04:00
Jason Wen b51d9af9a0 upstream pending tune 2026-03-31 06:56:52 -04:00
Jason Wen 4460ce8166 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-03-18 03:43:10 -04:00
Jason Wen f1aa0c7f78 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-03-07 01:49:09 -05:00
Jason Wen e7c8126fd9 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-03-05 02:01:04 -05:00
Jason Wen 125999c364 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-03-01 16:34:41 -05:00
Jason Wen 5b25ea7f99 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-28 15:47:57 -05:00
Jason Wen b7e2631286 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-27 21:56:34 -05:00
Jason Wen a838871189 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-19 01:51:17 -05:00
Jason Wen 1827331599 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-17 20:12:13 -05:00
Jason Wen 5c777bbe01 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-13 23:41:06 -05:00
Jason Wen fb97f993d1 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-13 17:32:10 -05:00
Jason Wen 94b67077e3 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-12 23:35:46 -05:00
Jason Wen 14f17699b9 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-11 00:35:20 -05:00
Jason Wen 80e27d5cbb Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-10 23:41:27 -05:00
Jason Wen 039dbcd877 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-02-09 01:46:00 -05:00
Jason Wen 8c134ae555 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-08 20:04:01 -05:00
Jason Wen 276c7a2b34 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-02-02 22:40:14 -05:00
Jason Wen 0e2dbcebfa Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-01-26 11:45:29 -05:00
Jason Wen bbb7760a95 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2026-01-19 01:43:21 -05:00
Jason Wen 23a27b2fbf Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2026-01-09 18:48:43 -05:00
Jason Wen 8b78107a40 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-31 00:49:56 -05:00
Jason Wen c27b6007de wrong bump? 2025-12-26 10:08:31 -05:00
Jason Wen 36c2dce247 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-26 10:08:23 -05:00
Jason Wen 8035039731 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-12-23 00:52:24 -05:00
Jason Wen 8aa6c9440f Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-20 17:01:25 -05:00
Jason Wen 34ef40fd81 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-12-18 00:19:20 -05:00
Jason Wen 4d044d7618 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-15 02:25:04 -05:00
Jason Wen 6247e3dc84 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-12-13 01:59:06 -05:00
Jason Wen b1131289b7 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-07 01:37:16 -05:00
Jason Wen 35dc7d661e Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-12-07 00:11:54 -05:00
DevTekVE c39b2dad94 Merge branch 'master' into hkg-angle-steering-2025 2025-11-29 10:12:31 +01:00
Jason Wen e6b769245c Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
#	selfdrive/ui/sunnypilot/SConscript
#	selfdrive/ui/sunnypilot/qt/offroad/settings/lateral_panel.cc
#	selfdrive/ui/sunnypilot/qt/offroad/settings/lateral_panel.h
#	selfdrive/ui/sunnypilot/qt/offroad/settings/longitudinal_panel.cc
2025-11-25 18:54:02 -05:00
DevTekVE 8b94f8b2f8 Merge branch 'master' into hkg-angle-steering-2025 2025-11-06 18:31:16 +01:00
Jason Wen dec014cd17 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	sunnypilot/selfdrive/car/interfaces.py
2025-11-04 17:45:05 -05:00
DevTekVE 7b40272866 Add sunnypilot-specific stats logging and handling
- Introduced `StatLogSP` for sunnypilot-specific metrics.
- Integrated stats collection and submission pathways for sunnylink.
- Extended parameters and handlers to support additional metrics.
- Added gzip compression and base64 encoding for oversized payload handling.
2025-11-04 21:20:16 +01:00
DevTekVE 506456e7f0 Merge branch 'master' into hkg-angle-steering-2025 2025-11-01 13:31:23 +01:00
DevTekVE 4ea4b9d177 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-10-31 06:59:39 +01:00
DevTekVE 0e2313dc31 Merge branch 'master' into hkg-angle-steering-2025 2025-10-18 11:14:45 +02:00
Jason Wen 79ea7db103 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-10-17 23:42:01 -04:00
Jason Wen f9ae9192fa Merge branch 'ui-icbm-universal' into hkg-angle-steering-2025 2025-10-17 21:55:00 -04:00
Jason Wen 7ec23006c6 check this 2025-10-17 21:54:44 -04:00
Jason Wen 2be9447a6c Merge branch 'ui-icbm-universal' into hkg-angle-steering-2025 2025-10-17 21:19:09 -04:00
Jason Wen cfd926778e always init true 2025-10-17 21:19:03 -04:00
Jason Wen a97a67e3d0 need 2025-10-17 21:17:31 -04:00
Jason Wen 518b6de08d Merge branch 'ui-icbm-universal' into hkg-angle-steering-2025 2025-10-17 21:15:59 -04:00
Jason Wen 6933e3bcdb fix cruise toggles 2025-10-17 21:15:43 -04:00
Jason Wen 05e0ca8bee some more 2025-10-17 20:46:36 -04:00
Jason Wen 410614fcf3 single location 2025-10-17 20:26:18 -04:00
Jason Wen e2bc0996ef Merge branch 'ui-icbm-universal' into hkg-angle-steering-2025 2025-10-17 12:21:47 -04:00
Jason Wen 1be0c20cf5 oops 2025-10-17 12:21:37 -04:00
Jason Wen 839143b9ed oops 2025-10-17 12:20:23 -04:00
Jason Wen bce86637ae Merge branch 'ui-icbm-universal' into hkg-angle-steering-2025 2025-10-17 12:15:23 -04:00
Jason Wen b833d3ee89 ui: update ICBM-related settings handling 2025-10-17 12:14:44 -04:00
Jason Wen e0441dfb4b Merge branch 'sla-event' into hkg-angle-steering-2025 2025-10-17 11:58:42 -04:00
Jason Wen 62ec40bba6 Speed Limit Assist: update active event handling 2025-10-17 11:58:19 -04:00
Jason Wen 15c6d38028 bump 2025-10-16 17:05:58 -04:00
Jason Wen 56eb9f555c Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	sunnypilot/selfdrive/controls/lib/e2e_alerts_helper.py
2025-10-16 01:12:10 -04:00
Jason Wen 2f9951df02 Merge branch 'e2e-alert-state-machine' into hkg-angle-steering-2025 2025-10-15 23:55:40 -04:00
Jason Wen 6030bf4da3 less 2025-10-15 23:52:03 -04:00
Jason Wen 074694d660 lead depart: only arm if we have a confirmed close lead for over a second after allowing alert 2025-10-15 23:48:13 -04:00
Jason Wen df35f48f3b magic 2025-10-15 22:56:08 -04:00
Jason Wen 4fb9704540 time based 2025-10-15 22:51:40 -04:00
Jason Wen 48cbe266fc 10 frames for both 2025-10-15 22:50:42 -04:00
Jason Wen 21aa7ff367 rename 2025-10-15 22:47:08 -04:00
Jason Wen 7caf05dd51 not used 2025-10-15 22:41:00 -04:00
Jason Wen 2d779f5db9 E2E Helper: universal state machine 2025-10-15 22:38:57 -04:00
Jason Wen 18208f1da0 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-10-15 17:41:56 -04:00
Jason Wen 5a3c6ddf57 gate lka angle steering out of alpha long 2025-10-14 23:25:00 -04:00
Jason Wen eaa8732ab0 Merge branch 'e2e-alerts-cooldown' into hkg-angle-steering-2025 2025-10-14 14:44:00 -04:00
Jason Wen 6f0284c84f try preventing startup false trigger 2025-10-14 14:43:47 -04:00
Jason Wen 999ea03f23 try preventing startup false trigger 2025-10-14 14:42:42 -04:00
Jason Wen 0975db3ff1 Merge branch 'e2e-alerts-cooldown' into hkg-angle-steering-2025 2025-10-14 14:31:59 -04:00
Jason Wen 8d70a8b80a only when long not engaged 2025-10-14 14:31:48 -04:00
Jason Wen da93f92887 rename 2025-10-14 14:26:57 -04:00
Jason Wen 9117f6c071 Merge branch 'e2e-alerts-cooldown' into hkg-angle-steering-2025 2025-10-14 14:23:46 -04:00
Jason Wen 3567ff9691 introduce recent moving check 2025-10-14 14:22:41 -04:00
Jason Wen f44ae2ced9 too complicated 2025-10-14 14:08:40 -04:00
Jason Wen 376e0ca615 only allow one trigger per standstill session 2025-10-14 14:07:16 -04:00
Jason Wen 32b7686468 Merge branch 'master' into e2e-alerts-cooldown 2025-10-14 11:40:58 -04:00
nayan b9e0f52ea9 E2E Alert Cooldown 2025-10-14 07:43:15 -04:00
Jason Wen a3163b680f Merge branch 'sla-chimes' into hkg-angle-steering-2025 2025-10-14 02:01:05 -04:00
Jason Wen 8a927d808f Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-10-14 02:00:36 -04:00
Jason Wen bc7d5e474d Speed Limit Assist: audible alerts for certain states 2025-10-14 01:45:13 -04:00
Jason Wen 36f192b5fe Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-10-13 03:10:47 -04:00
Jason Wen ffd5cd4ac2 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-10-11 02:29:47 -04:00
Jason Wen e4a00fcd6c Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025 2025-10-10 17:28:16 -04:00
Jason Wen 0bdcb41103 Merge remote-tracking branch 'sunnypilot/sunnypilot/master' into hkg-angle-steering-2025
# Conflicts:
#	common/params_keys.h
#	opendbc_repo
#	selfdrive/ui/sunnypilot/qt/offroad/settings/lateral_panel.cc
2025-10-10 17:02:14 -04:00
DevTekVE 78051085ca Merge branch 'master' into hkg-angle-steering-2025 2025-09-23 07:54:32 +02:00
DevTekVE 4910d5809a bump opendbc 2025-09-23 07:45:39 +02:00
DevTekVE 8dd862ff28 yikes, becoming picky huh? 2025-09-14 22:50:21 +02:00
DevTekVE 1b57497da9 Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-09-14 22:48:00 +02:00
DevTekVE 8d8d1ffc7a bump opendbc again 2025-09-14 22:46:20 +02:00
DevTekVE c5919d5495 wrong dbc lol 2025-09-14 22:42:19 +02:00
DevTekVE da71951c95 This is no longer in use nor needed. Bai! 2025-09-14 12:56:28 +02:00
DevTekVE 25a152cd8b Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-09-14 12:44:23 +02:00
DevTekVE 9077a1082a Sorry for C3 :( but moving you out to a last working branch before I sync it up 2025-09-14 06:52:24 +02:00
DevTekVE 7ae7000254 Rework override behavior and feeling 2025-09-14 06:38:00 +02:00
DevTekVE 7029455706 better juggle 2025-09-13 08:32:27 +02:00
DevTekVE 3a71a62215 Merge branch 'master' into hkg-angle-steering-2025 2025-09-12 10:14:52 +02:00
DevTekVE 00622e8c33 Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-09-05 09:46:41 +02:00
DevTekVE 549da3ee92 Merge branch 'master' into hkg-angle-steering-2025 2025-09-04 20:20:37 +02:00
DevTekVE e038a65ef8 Merge branch 'master' into hkg-angle-steering-2025 2025-08-31 13:14:33 +02:00
DevTekVE 8d0513c657 dbc: update CHECKSUM format for multiple messages to improve data integrity 2025-08-30 19:56:21 +02:00
DevTekVE 2cea48f4cd Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-08-30 15:27:45 +02:00
DevTekVE 8855a9ab65 Improve surprise jerk by safety blocks 2025-08-26 14:47:26 +02:00
DevTekVE 32321c01cc A bit more helpful safety block investigation help 2025-08-26 10:09:11 +02:00
DevTekVE 52cd65fefb lint dont bother me 2025-08-25 08:24:24 +02:00
DevTekVE 1fcdeccd40 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	common/params_keys.h
#	opendbc_repo
2025-08-25 08:01:51 +02:00
DevTekVE 3517c36978 Revert "Add HkgAngleDebug structure and enhance angle debugging in car controller" 2025-08-24 19:02:48 +02:00
DevTekVE fb30c3c1e8 cleanup and honour params 2025-08-23 15:42:47 +02:00
DevTekVE 1c25e568d5 Update steering pressed logic to include hands-on-wheel detection for improved safety 2025-08-23 15:11:07 +02:00
DevTekVE f172122b7c Update steering pressed logic to include hands-on-wheel detection for improved safety 2025-08-22 19:55:16 +02:00
Jason Wen 67d6cdc7cd Merge remote-tracking branch 'sunnypilot/sunnypilot/hkg-angle-steering-2025' into hkg-angle-steering-2025 2025-08-21 16:39:36 -04:00
DevTekVE 6724085cfd Refactor angle limit calculations and adjust average road roll for improved steering dynamics 2025-08-21 20:09:57 +02:00
DevTekVE 6774f34eee Refine non-linear mapping in torque reduction gain calculation for improved steering response 2025-08-21 00:21:46 +02:00
DevTekVE 6d0402896d Adjust STEER_THRESHOLD and refine non-linear mapping in torque reduction gain calculation for improved steering response 2025-08-20 23:16:04 +02:00
DevTekVE 344021a3d9 Adjust non-linear mapping in torque reduction gain calculation for improved response 2025-08-20 19:54:31 +02:00
DevTekVE a9b85ab27d Refactor HkgAngleDebug structure to include current and baseline limits for angle parameters 2025-08-20 19:54:10 +02:00
DevTekVE 17204a46e4 Add HkgAngleDebug structure and enhance angle debugging in car controller 2025-08-20 18:39:53 +02:00
DevTekVE 7c4d415462 Enhance torque reduction gain calculation with non-linear mapping and smoothing 2025-08-20 00:12:43 +02:00
DevTekVE b8985b6d72 Enhance torque reduction gain calculation with non-linear mapping and smoothing 2025-08-19 19:50:13 +02:00
DevTekVE c669473f88 Refine torque reduction parameters and update UI for angle error analysis 2025-08-19 19:35:34 +02:00
DevTekVE 8751435bf5 Improving tq redc gain and override behavior 2025-08-19 10:08:51 +02:00
DevTekVE 30ae210761 Merge branch 'master' into hkg-angle-steering-2025 2025-08-19 10:07:42 +02:00
Jason Wen 3eb693f58b Merge remote-tracking branch 'sunnypilot/sunnypilot/hkg-angle-steering-2025' into hkg-angle-steering-2025 2025-08-18 12:30:29 -04:00
DevTekVE 7b4a31c5ac bugfix 2025-08-17 16:07:45 +02:00
DevTekVE 1527c8cf88 bump opendbc 2025-08-17 15:31:31 +02:00
DevTekVE ab0a7ae666 no joystick on this branch, causing issues 2025-08-17 15:25:40 +02:00
DevTekVE 11ec2f1f21 Apply suggestions from code review 2025-08-17 15:10:17 +02:00
DevTekVE 2c6808d37e Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-08-17 15:02:28 +02:00
Jason Wen 2e96382c49 notebook init 2025-08-17 00:34:01 -04:00
DevTekVE 0239e440ca Adjust replay 2025-08-15 10:32:07 +02:00
Jason Wen 76b972daff Hyundai angle steering: STEERING_ANGLE_2 available on all cars 2025-08-14 01:56:46 -04:00
Jason Wen bc3ef3e7dd Hyundai angle steering: hugging no more - use the true steering angle signal from MDPS 2025-08-13 23:08:32 -04:00
DevTekVE 9839291dd0 Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025 2025-08-13 20:13:42 +02:00
DevTekVE 17cba328d6 refactor: update torque tuning configuration for angle steering
- Adjusted torque tuning configuration to avoid reliance on torque controller for Hyundai angle steering.
- Simplified control logic by removing unnecessary checks for torque control type.
refactor: clean up code formatting and improve test structure for torque reduction gain
2025-08-13 20:03:51 +02:00
DevTekVE 86093765d8 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-08-13 07:55:46 +02:00
DevTekVE 05fa1c8ae8 Adjust default params and cleanup 2025-08-12 21:36:22 +02:00
DevTekVE e8a40d6b85 Merge branch 'master' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
#	system/manager/process_config.py
2025-08-10 14:24:10 +02:00
DevTekVE c265e0bb85 Merge remote-tracking branch 'origin/master' into hkg-angle-steering-2025
# Conflicts:
#	common/params_keys.h
#	opendbc_repo
#	system/manager/manager.py
2025-08-02 09:56:58 +02:00
DevTekVE c6b118788b Merge branch 'master-new' into hkg-angle-steering-2025 2025-07-31 18:25:08 +02:00
DevTekVE b004f6dbdc Merge branch 'master-new' into hkg-angle-steering-2025 2025-07-31 18:17:34 +02:00
DevTekVE cd4930b680 Bump opendbc 2025-07-26 10:56:49 +02:00
DevTekVE f861aca628 Refactor vehicle model initialization and adjust angle limits for baseline model 2025-07-26 08:12:06 +02:00
DevTekVE 1ff0d8e2ee please don't bother me anymore! 2025-07-26 08:09:51 +02:00
DevTekVE d76d70764e Update slip factor precision for Hyundai steering parameters
- Adjusted `slip_factor` in Hyundai CANFD safety modes for improved consistency and accuracy.
- Ensured proper representation of `slip_factor` output in test logs.
2025-07-25 20:17:19 +02:00
DevTekVE dc73ce0b71 save tools replay 2025-07-25 19:47:31 +02:00
DevTekVE 3f666748af bump opendbc 2025-07-25 14:16:02 +02:00
DevTekVE 8de8a8838c bumo opendbc 2025-07-25 14:08:53 +02:00
DevTekVE f563b7eb71 Refactor steering angle limit application for improved safety and model compliance 2025-07-25 12:12:42 +02:00
DevTekVE 3c18b83708 save temp 2025-07-25 09:56:30 +02:00
DevTekVE bd35f5904b Enhance steering angle rate limiting and safety enforcement logic
- Introduced explicit post-rate limiting using model-specific dynamics.
- Improved low-speed smoothing and precision of applied angles.
2025-07-25 08:12:41 +02:00
DevTekVE 474f2737f6 Refactor steering angle limit logic for conservative seleion
- Removed unused lateral accel/jerk logic for simplicity.
- Updated angle limit calculations to choose the smallest delta for safer control.
2025-07-24 21:48:24 +02:00
DevTekVE ea1ac4a212 Revert "Add configurable max lateral accel and jerk parameters for Hyundai vehicles"
This reverts commit b95f8c5929.

Revert "Add baseline safety model and improve steering angle limiting logic"

This reverts commit b53cbb2e18.

Revert "Disable lateral accel/jerk params and ensure float consistency in angle limits"

This reverts commit 165d7c7b36.
2025-07-24 10:02:48 +02:00
DevTekVE 165d7c7b36 Disable lateral accel/jerk params and ensure float consistency in angle limits
- Commented out unused lateral accel/jerk parameters for clarity.
- Ensured `np.clip` always returns a float for precision.
2025-07-24 09:41:52 +02:00
DevTekVE b53cbb2e18 Add baseline safety model and improve steering angle limiting logic
- Introduced a baseline safety model (`GENESIS_GV80_2025`) for comparison.
- Enhanced steer angle limit calculation using both baseline and current limits for improved safety and precision.
2025-07-24 09:38:03 +02:00
DevTekVE b95f8c5929 Add configurable max lateral accel and jerk parameters for Hyundai vehicles
- Introduced user-configurable options for max lateral acceleration and jerk.
- Enables fine-tuning of vehicle handling for smoother control.
2025-07-24 08:39:10 +02:00
DevTekVE e564bb0b85 bumo openbc 2025-07-23 18:46:52 +02:00
DevTekVE e2ec8a7b13 Refine lateral control limits and simplify safety model handling
- Reduced max lateral acceleration and jerk by 20% for smoother handling.
- Removed unused `get_safety_CP` function, simplifying `VehicleModel` initialization.
2025-07-22 08:07:51 +02:00
DevTekVE 75c6f0f10e Test with gv80 as baseline for limits 2025-07-20 22:14:18 +02:00
DevTekVE af38044b42 Merge branch 'master-new' into hkg-angle-steering-2025 2025-07-20 10:14:46 +02:00
DevTekVE 684fa846d8 Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	.codespellignore
#	opendbc_repo
#	system/manager/manager.py
2025-07-19 21:51:46 +02:00
DevTekVE 416e722855 Update baseline model to IONIQ 5 PE for improved angle safety tuning
- Replaced conservative GENESIS_GV80_2025 model with IONIQ 5 PE parameters.
- Adjusted steering parameters (ratio, slip factor, wheelbase) for better lateral control performance.
2025-07-19 21:46:17 +02:00
DevTekVE 9fd4613bbb Add 2025 Kia EV6 support with updated radar and camera fingerprints 2025-07-09 09:47:31 +02:00
DevTekVE a0362e3c5f "Refined UI labels and tooltips for HKG tuning options to improve clarity and user understanding." 2025-06-29 16:48:53 +02:00
DevTekVE e32ef1cdc0 Fix incorrect torque sign usage in torque reduction calculation
Ensure `actuators.torque` uses its absolute value in the `calculate_angle_torque_reduction_gain` method to prevent sign-related issues during Hyundai steering angle control.
2025-06-29 14:33:30 +02:00
DevTekVE 20673ec8a6 Adjust warning font size in angle tuning settings panel. 2025-06-29 13:35:09 +02:00
DevTekVE 53fbdf7329 Rename "IdleTorque" to "ActiveTorque" for clarity.
The parameter name "HkgTuningAngleIdleTorqueReductionGain" was updated to "HkgTuningAngleActiveTorqueReductionGain" across multiple files for better clarity and alignment with its functionality. This change ensures consistency in naming conventions and improves code readability.
2025-06-29 13:23:56 +02:00
DevTekVE 6f72b74fac Add idle torque reduction for Hyundai lateral control
Introduced `ANGLE_IDLE_TORQUE_REDUCTION_GAIN` to manage torque when the vehicle is stationary, ensuring smoother handling and better lane centering. Updated parsing, parameters, and UI settings to support this new idle torque parameter. Adjusted torque calculation logic and smoothing factor behavior for enhanced control flexibility.
2025-06-29 13:22:18 +02:00
DevTekVE e83705a32e Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-06-29 09:44:01 +02:00
DevTekVE 95d36b9ba2 Refactor and enhance HKG angle tuning logic.
Introduced a toggle for angle smoothing factor and renamed related parameters for clarity. Refactored backend settings to use new parameter names and expanded smoothing matrices for better tuning granularity. Updated UI elements to reflect these changes, emphasizing usability and consistency.
2025-06-28 21:25:44 +02:00
DevTekVE b9e74254bd Merge branch 'master-new' into hkg-angle-steering-2025 2025-06-27 10:46:22 +02:00
DevTekVE b4405b200d Merge remote-tracking branch 'origin/master-new' into hkg-angle-steering-2025 2025-06-25 09:27:21 +02:00
DevTekVE a8a3fdac54 Rename parameter in calculate_target_torque for clarity. 2025-06-23 22:53:45 +02:00
DevTekVE 4eddc622a7 Refactor torque calculations in Hyundai controller
Rename methods and variables for clarity in torque reduction and override calculations. Adjust logic to streamline handling of steering inputs and improve maintainability.
2025-06-23 22:51:40 +02:00
DevTekVE 4e42ada240 Refactor torque management in Hyundai controller for cleaner override and ramp logic
Extract torque ramping and override functionality into dedicated methods within `LkasTorqueManager` to improve maintainability and reduce redundancy. Simplify `update` logic by delegating state-specific operations to new methods.
2025-06-23 22:47:51 +02:00
DevTekVE 6266217655 Introduce LkasTorqueManager for LKAS torque handling in Hyundai controller
Encapsulate LKAS torque calculations, ramping, and override logic into the new `LkasTorqueManager` class to improve modularity and maintainability. Replace existing torque logic with calls to the manager.
2025-06-23 22:20:10 +02:00
DevTekVE ea09d32e98 Remove lateral acceleration logic from Hyundai steering controller 2025-06-23 21:55:17 +02:00
DevTekVE 15958c88d3 Refactor lateral acceleration scaling logic in Hyundai controller
Move scaling of `max_angle_delta` under high lateral acceleration to improve clarity and prevent redundant operations.
2025-06-23 20:22:03 +02:00
DevTekVE b80d7fb5ea Adding GV70 electrified 2026 2025-06-22 14:30:59 +02:00
DevTekVE 1c3d25c6ff Refine lateral acceleration handling in Hyundai steering logic
Enforce absolute check for `real_a_lat` against `MAX_LATERAL_ACCEL` to improve angle scaling under high lateral acceleration conditions.
2025-06-22 11:03:35 +02:00
rav4kumar c9f22b32c7 Revert "Incorporate lateral acceleration in Hyundai angle steering logic"
This reverts commit c0524985bb.
2025-06-21 11:40:58 -07:00
DevTekVE c0524985bb Incorporate lateral acceleration in Hyundai angle steering logic
Add handling for IMU lateral acceleration to refine steering angle limits in CAN FD configurations. Parse and utilize `IMU_LatAccelVal` signal for enhanced lateral control accuracy.
2025-06-21 17:34:13 +02:00
DevTekVE 83839c7ea7 Add angle steering support and refactor related logic for Hyundai CAN FD.
Introduced support for CAN FD angle steering, including updated parameters, signal parsing, and new tests. Refactored related steering logic for clarity, reducing unused code and enhancing maintainability.
2025-06-21 13:38:50 +02:00
DevTekVE c1a1d4b4c3 Update lint script to exclude .xml files in layouts directory
Added `layouts/.*\.xml` to `IGNORED_FILES` in `lint.sh` to prevent linting of layout XML files.
2025-06-20 10:50:45 +02:00
DevTekVE b5af7a905a Merge branch 'master-new' into hkg-angle-steering-2025 2025-06-18 20:13:45 +02:00
DevTekVE 96b1b2f55f Update steering request logic in Hyundai controller
Ensure steering request activation depends on lateral control being active. This adds clarity and aligns better with control logic requirements.
2025-06-17 18:51:54 +02:00
DevTekVE 9361ba5d70 Refactor Hyundai steering angle handling logic
Streamline steering angle calculations and fault avoidance logic by removing redundant comments and unused code. Simplified `round_angle` implementation for clarity and consistency.
2025-06-17 12:08:06 +02:00
DevTekVE 4e9014311e Refactor steeringPressed logic in Hyundai carstate.py.
Revised the determination of `steeringPressed` to account for both hands-on-wheel detection and torque overriding in CAN FD setups. Simplified fallback logic for non-CAN FD configurations for better code clarity and maintainability.
2025-06-12 00:31:07 +02:00
DevTekVE 232873fc70 Refine steering press detection logic.
Adjusted the sensitivity and threshold values for `HOD_Dir_Status` in steering press updates, improving accuracy in detecting steering input. This change aligns with updated parameter requirements for better responsiveness.
2025-06-12 00:14:05 +02:00
DevTekVE 0a61fca9c9 Fix steering press detection for Hyundai models.
Updated the condition to detect steering press by changing HOD_Dir_Status threshold from `> 2` to `>= 2`. This ensures the detection logic aligns correctly with expected behavior.
2025-06-12 00:06:52 +02:00
DevTekVE 480bdc34dc Add support for CANFD angle steering in Hyundai cars
Introduced handling for the `HOD_FD_01_100ms` message when the CANFD angle steering flag is enabled. This ensures proper message parsing and extends compatibility for specific Hyundai vehicle configurations.
2025-06-12 00:04:44 +02:00
DevTekVE 716b475a13 Update Hyundai controls for HOD status and steer limits
Adjusted the steering override frame window and incorporated new HOD_Dir_Status to improve hands-on detection. Added parsing for new signals in Hyundai CAN FD, enhancing steering override responsiveness and reliability.
2025-06-12 00:01:31 +02:00
DevTekVE b1ec5ec034 Adjust override angle cap in Hyundai car controller
Increased the minimum override angle cap from 0.01 to 0.1 and explicitly cast the maximum cap to a float. This change improves consistency and ensures proper handling of steering limits.
2025-06-11 23:20:19 +02:00
DevTekVE 470613c2b7 Adjust Hyundai steer override parameters for improved control.
Reduced the override frame window and updated the angle cap logic to use MAX_ANGLE_RATE. These changes aim to enhance steering responsiveness and safety by fine-tuning steer angle limits.
2025-06-11 23:07:49 +02:00
DevTekVE 336c5b4154 Remove smoothing_factor from Hyundai car controller logic
The `smoothing_factor` parameter and related logic have been removed to simplify the steering angle smoothing approach. All references and usage of this parameter have been eliminated, relying solely on speed-based dynamic interpolation. This change streamlines the code while maintaining functionality.
2025-06-11 23:04:32 +02:00
DevTekVE abdb9dc750 Adjust Hyundai steering override frame logic
Reduced `OVERRIDE_FRAME_WINDOW` and updated condition to properly respect override frame limits. This ensures smoother handling and more precise steering adjustments under certain driving scenarios.
2025-06-11 22:49:04 +02:00
DevTekVE ab98683973 Refactor steering override logic in Hyundai carcontroller
Replaced `recently_overridden` with `frames_since_override` for better granularity and added dynamic override angle limits using interpolation. These changes enhance steering control accuracy during user overrides and improve overall code readability.
2025-06-11 22:42:05 +02:00
DevTekVE 186c24dbe6 Refine Hyundai steering override handling logic
Adjusted logic for recently overridden steering to improve angle limits and torque smoothing. Removed unused or redundant code, optimizing the functionality and maintaining cleaner readability.
2025-06-11 21:49:18 +02:00
DevTekVE 9cdf6340a1 Refactor steering angle smoothing for clarity and reuse.
Extracted the steering angle smoothing logic into a standalone function `sp_smooth_angle` to enhance readability and reusability. Adjusted angle smoothing parameters and introduced a maximum vehicle speed threshold for applying smoothing. Minor updates improve maintainability and ensure consistent behavior across speed ranges.
2025-06-11 10:07:44 +02:00
DevTekVE 2855b1341c Adjust steering thresholds for Hyundai CAN FD vehicles
Updated `STEER_THRESHOLD` to 350 and `NO_LONGER_OVERRIDING_THRESHOLD` to 150 for better alignment with Hyundai CAN FD steering behavior. These changes ensure improved compatibility and more accurate steering response.
2025-06-10 09:53:08 +02:00
DevTekVE cf28f99976 Revert "Add twilsonco's LKAS torque calculator for improved lateral control"
This reverts commit b1770fb0e7aece0e160b1b083cb260edbbdc53dd.
2025-06-10 09:40:59 +02:00
DevTekVE a39d67dc47 Fix apply_angle_last reset logic in Hyundai carcontroller
Re-enables resetting `apply_angle_last` to `steering_angle` when steering is recently overridden. This ensures proper handling of steering angle limits during transitions.
2025-06-08 19:04:02 +02:00
DevTekVE 7e75257f12 Refine Hyundai steering control logic.
Simplified torque ramp-up logic by combining conditions and adjusted `STEER_THRESHOLD` for CANFD angle steering. These changes aim to enhance control precision and maintain consistency in overrides.
2025-06-08 19:02:49 +02:00
DevTekVE df38449553 Reduce override timeout for Hyundai carcontroller
Decrease the override timeout from 100 to 50 frames, ensuring quicker recognition of driver input override. This improves responsiveness and aligns with refined control behavior.
2025-06-08 18:22:44 +02:00
DevTekVE 1385ef3bc5 Fix steering control behavior during user override
Removed restrictive rate limiting during recent user overrides to improve steering response. Adjusted logic to ensure correct handling of steering angle when lateral control is inactive or overridden.
2025-06-08 18:01:47 +02:00
DevTekVE 7c23c11c51 Refine steering logic with override detection.
Adjust steering behavior to account for recent user overrides, improving safety and control. Introduced a "recently_overridden" check to limit angle rates and torque adjustments when user intervention is detected.
2025-06-08 17:52:16 +02:00
DevTekVE aeff2e12ec Refine steering logic with user override handling.
Added logic to use the current steering angle when the steering wheel is pressed, ensuring smoother transitions during user overrides. Updated function parameters and implementation to reflect this enhancement.
2025-06-08 17:38:34 +02:00
DevTekVE 7274899671 Refactor Hyundai override logic for steering thresholds
Removed redundant `recently_overridden` logic and introduced a more robust approach for tracking user steering overrides. Added `NO_LONGER_OVERRIDING_THRESHOLD` and updated conditions to improve steer override handling. Adjustments ensure smoother torque transitions and more accurate steering state detection.
2025-06-08 17:00:44 +02:00
DevTekVE 6c00fd608f pass tests? 2025-06-08 12:28:11 +02:00
DevTekVE df6a034c11 Bump opendbc 2025-06-08 12:26:09 +02:00
DevTekVE acb109c290 adding plotjuggler stuff 2025-06-08 10:02:44 +02:00
DevTekVE b227b00249 Update torque clamping to use parameterized min torque
Replaced hardcoded `angle_min_active_torque` with `ANGLE_MIN_TORQUE` from params for better configurability and consistency. This ensures the torque clamping logic aligns with defined parameters.
2025-06-07 19:43:01 +02:00
DevTekVE 3ec9d6c18a Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	common/params_keys.h
2025-06-07 15:04:16 +02:00
DevTekVE 86db8b95f0 Refactor torque calculation and deactivate live tuning.
Updated torque calculation logic with a new optional parameter for minimum active torque, streamlining control behavior. Deactivated and cleaned up references to HkgAngleLiveTuning, simplifying configuration and reducing runtime complexities. Updated relevant UI and parameter descriptions for clarity.
2025-06-07 11:55:57 +02:00
DevTekVE 4cfff8a35f Merge branch 'master-new' into hkg-angle-steering-2025 2025-06-06 23:08:37 +02:00
DevTekVE 962fedf48c Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	opendbc/car/tests/routes.py
2025-06-06 20:49:06 +02:00
DevTekVE 04494414d1 Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-06-05 09:18:53 +02:00
DevTekVE 0b83576e9b Adjust torque ramping logic and update steering thresholds
Increase the override window and refine torque ramp-up behavior to avoid conflicts during recent overrides. Updated steering driver allowance and threshold values for CANFD angle steering to improve compatibility and performance.
2025-06-02 09:49:31 +02:00
DevTekVE ce4ef0f817 Refine steering override logic in Hyundai car controller
Added logic to track recent steering overrides and adjust LKAS torque behavior accordingly. This ensures smoother transitions when the steering is overridden and reduces potential conflicts with driver input. Updated CANFD-specific steering thresholds for enhanced compatibility.
2025-06-02 09:12:03 +02:00
DevTekVE f0b15c1c56 Adding twil's torque calculation 2025-06-01 19:04:34 +02:00
DevTekVE f898e9fdfe Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-06-01 09:46:45 +02:00
DevTekVE 8ee7804b0e Bump opendbc (no tesla controls, no twil yet) 2025-05-29 16:31:42 +02:00
DevTekVE 923228194e bump opendbc to prior tesla changes until i can pass safety validations 2025-05-28 12:44:44 +02:00
DevTekVE 8837b2e3f6 Merge branch 'master-new' into hkg-angle-steering-2025
# Conflicts:
#	opendbc_repo
2025-05-28 12:36:02 +02:00
DevTekVE f48c9dc1c2 bump opendbc 2025-05-25 17:34:24 +02:00
DevTekVE 74aa07a8cd Ingore something i dont control thx 2025-05-25 17:31:37 +02:00
DevTekVE 5236e4860f Make lint happy, maybe 2025-05-25 17:31:37 +02:00
DevTekVE 3d174da1c3 adding some of my tests and validaitons 2025-05-25 17:31:25 +02:00
DevTekVE 8faa40f3a3 clean 2025-05-25 17:31:25 +02:00
DevTekVE 3e03275f28 Add PlotJuggler layout for analyzing torque and angle data
This new layout visualizes actuator data, CAN steering messages, and car state variables. It provides multiple time-series plots to aid in debugging and analysis. Plugin configurations are also included for extended functionality.
2025-05-25 17:31:22 +02:00
DevTekVE 7595cf8a25 Refine Hyundai angle and torque control logic.
Simplified control flag handling for angle steering, adjusted torque calculations for smoother ramp rates, and updated tuning parameters for the Hyundai Ioniq 5 PE. Minor adjustment to return value handling in lateral control functions.
2025-05-25 17:31:22 +02:00
DevTekVE 2675d43adb bump opendbc
Remove duplicate STEER_ANGLE_SATURATION_THRESHOLD import

Cleaned up an unnecessary duplicate import of STEER_ANGLE_SATURATION_THRESHOLD from latcontrol_angle_torque. This simplifies the module imports and prevents potential redundancy or confusion.

Refactor lateral control to combine torque and angle logic

Merged functionalities of LatControlTorque and LatControlAngle into a single LatControlAngleTorque class. Refactored code to utilize methods from both parent classes, reducing duplication and improving maintainability.

Add angle-torque hybrid lateral control for Hyundai CAN FD

Introduces `LatControlAngleTorque` to enable hybrid angle and torque-based steering for specific Hyundai models. Updates related logic in carcontroller, interface, and controlsd to accommodate this new lateral control method. Adjusts torque parameters for enhanced control in supported models.
2025-05-25 17:31:21 +02:00
DevTekVE d9f4ce82e6 clean 2025-05-25 17:31:21 +02:00
DevTekVE 648a1845d8 cleanup the mess 2025-05-25 17:31:21 +02:00
DevTekVE a87eff6d1c Add HKG Angle Live Tuning parameter and update related handling 2025-05-25 17:31:21 +02:00
DevTekVE dd6ad37e23 Absolutely zero clue on this, I did it with AI and it's for me to play. Don't take this notebook seriously please 2025-05-25 17:31:21 +02:00
DevTekVE c5e778b939 How annoying the linter on a comment lol 2025-05-25 17:31:21 +02:00
DevTekVE a9ab81a77a useless but should keep linter happy 2025-05-25 17:31:21 +02:00
DevTekVE 2d40e1d8e5 Refactor torque parameter handling in Hyundai carcontroller
Replaced direct access to `params` with instance variables for torque parameters to improve code clarity and maintainability. Updated smoothing factor description in angle tuning settings to include speed-related behavior. This enhances readability and prepares for further tuning adjustments.
2025-05-25 17:31:20 +02:00
DevTekVE 7c8f367a5d Fix data type for HkgTuningOverridingCycles value
Updated the value of HkgTuningOverridingCycles to a string for consistency with other parameters in the tuning configuration. This ensures proper handling and avoids potential issues with type mismatches.

Add overriding cycles parameter for torque adjustment

Introduced "HkgTuningOverridingCycles" for configurable user override torque ramp-down cycles. Updated relevant logic in torque control and UI settings to handle the new parameter. This improves flexibility in adjusting steering torque override behavior.
2025-05-25 17:31:20 +02:00
DevTekVE ff4cf558aa Add HKG angle tuning settings with min/max torque parameters
Introduce separate angle tuning controls for HKG vehicles, including smoothing factor, min torque, and max torque parameters. Refactor developer panel to integrate the new settings into a dedicated UI panel, enhancing modularity and customization capabilities.
2025-05-25 17:31:20 +02:00
DevTekVE 0e151e51bc Update HKG Angle Smoothing Factor description in Developer Panel
Enhanced the description to clarify its effect on steering behavior. Included details on how the smoothing factor impacts steering smoothness using EMA, aiding user understanding.
2025-05-25 17:31:20 +02:00
DevTekVE 60cc0031b0 Revert "Revert "Revert the EMA calculation on the curvature to test another approach""
This reverts commit 58fcda8c
2025-05-25 17:31:20 +02:00
DevTekVE d24cac0998 Refactor steering angle logic for smoother control adjustments
Refactored the calculation and application of the steering angle to improve code clarity and ensure smoother transitions. Removed unused parameter update logic in `latcontrol_angle.py` and enhanced handling of driver overrides in `carcontroller.py`.
2025-05-25 17:31:20 +02:00
DevTekVE 45d110830c Fix typo in parameter access method.
Replaced `self._params` with `self.params` to correctly access the parameter `HkgTuningAngleSmoothingFactor`. This ensures the smoothing factor is updated as intended during the control loop.
2025-05-25 17:31:20 +02:00
DevTekVE ea3a9ae911 Improve angle smoothing by integrating dynamic parameter tuning
Introduced a dynamic smoothing factor using the `HkgTuningAngleSmoothingFactor` parameter. This allows more granular control over curvature smoothing based on customizable user input, enhancing driving smoothness. Added necessary logic to process and apply this parameter efficiently.
2025-05-25 17:31:19 +02:00
DevTekVE 6bff8c0e7c Revert "Revert the EMA calculation on the curvature to test another approach"
This reverts commit bd471b3498.
2025-05-25 17:31:19 +02:00
DevTekVE bc6b8802b8 Add HKG angle smoothing factor for steering adjustments
Introduced a new parameter, `HkgTuningAngleSmoothingFactor`, to apply exponential moving average (EMA) smoothing to steering angle changes, reducing sudden adjustments. Added associated UI controls, parameter persistence, and integration into Hyundai carcontroller logic for improved steering stability.
2025-05-25 17:31:19 +02:00
DevTekVE 252ef572d3 Revert the EMA calculation on the curvature to test another approach 2025-05-25 17:31:19 +02:00
DevTekVE 414d397e3f Handle missing pygame import gracefully
Wrap the pygame import in a try-except block to catch ImportError. This prevents the script from crashing and provides a clear message prompting the user to install pygame if it's missing.

Remove "inputs" package and update "pygame" dependency

The "inputs" package has been removed from the lockfile and dependency list, while "pygame" is now included universally without the "dev" extra marker. This change simplifies dependencies and ensures consistency across environments.

Update dependencies: replace 'inputs' with 'pygame'

Replaced the 'inputs' library with 'pygame' for joystickd dependencies in `pyproject.toml`. Additionally, removed a redundant 'pygame' entry from the general dependencies.

Ugly, I know, but soundd is unhappy with joystick

Allowing lat with mads

Invert steering input for joystick control

The steering axis input is now multiplied by -1 to reverse its direction. This ensures correct handling of the left stick's horizontal input, aligning behavior with expected control dynamics.

Refactor joystick control to use pygame for broader support

Replaced the `inputs` library with `pygame` for joystick handling, providing improved compatibility with Xbox and PlayStation controllers. Added initialization, adaptive mappings, deadzone handling, and enhanced event processing for robust joystick operation. Updated README with dependencies and usage information for Xbox controllers.
2025-05-25 17:31:19 +02:00
DevTekVE 11b7b3789d Adjust speed thresholds in filter_speed_matrox.
Updated the `filter_speed_matrox` values to improve curvature filtering behavior at different speeds. This change ensures better handling and stability across a wider range of driving conditions.
2025-05-25 17:31:19 +02:00
DevTekVE 871ac53717 Optimize curvature filtering by adding speed-dependent logic.
Introduced speed-based dynamic alpha adjustment using interpolation for smoother curvature filtering. This improves steering angle calculations by adapting filter sensitivity to vehicle speed, enhancing control performance.
2025-05-25 17:31:19 +02:00
DevTekVE 64ea66b6e6 chsnge alpha to nicer value 2025-05-25 17:31:19 +02:00
DevTekVE 6d7c6759b3 Adjust curvature handling and filtering parameters
Updated curvature breakpoints and torque scaling for improved control in sharp turns. Increased filter alpha for faster curvature response while maintaining system stability.
2025-05-25 17:31:18 +02:00
DevTekVE 4cea013570 Adjust curvature handling and filtering parameters
Updated curvature breakpoints in Hyundai carcontroller to improve torque scaling for curved driving. Slightly refined the filter coefficient in lateral control for smoother curvature filtering and more accurate steering adjustments.
2025-05-25 17:31:18 +02:00
DevTekVE eb375c0587 Refactor curvature-based steering angle and torque logic.
Introduced dynamic torque scaling based on curvature for smoother and more adaptive steering control. Replaced raw curvature inputs with filtered curvature for enhanced stability and reduced noise in steering angle calculations. Removed unused speed scaling logic to simplify the lateral control flow.
2025-05-25 17:31:18 +02:00
DevTekVE 7fd8a5a4bd Reapply "Significant improvement on the jerkiness"
This reverts commit 85ce84e7b7.
2025-05-25 17:31:18 +02:00
DevTekVE b3c90216bb Revert "Significant improvement on the jerkiness"
This reverts commit ea1af879ba2905b076ccfe65993a9db701d689dd.

Revert "More improvement but still not quite"

This reverts commit ad95493c5c61b2ace7c459d2ebc151ddaa80040f.

Revert "Adjust low-speed scaling for lateral control angle"

This reverts commit 6f789ac1ebb66b0239b4028303573c2d7d386b39.

Revert "Refactor speed-based steering scaling logic."

This reverts commit 1d40735ab8db8d470ff3b287a6b42847beffff7d.
2025-05-25 17:31:18 +02:00
DevTekVE 10f345f956 Refactor speed-based steering scaling logic.
Updated the steering angle computation to use a clearer and more descriptive speed-scaling configuration. Replaced low-speed-specific logic with a generalized approach based on speed breakpoints and corresponding influence factors. This improves maintainability and ensures smoother steering adjustments at varying speeds.
2025-05-25 17:31:18 +02:00
DevTekVE 956d2c36d0 Adjust low-speed scaling for lateral control angle
Refined the low-speed scaling parameters by modifying speed breakpoints and factors. This improves handling at lower speeds for smoother and more predictable behavior.
2025-05-25 17:31:18 +02:00
DevTekVE 55e688b6f2 More improvement but still not quite 2025-05-25 17:31:17 +02:00
DevTekVE f017954027 Significant improvement on the jerkiness 2025-05-25 17:31:17 +02:00
DevTekVE 7e992d11b1 bump panda and opendbc 2025-05-25 17:31:15 +02:00
72 changed files with 2638 additions and 4650 deletions
+1
View File
@@ -2,5 +2,6 @@ Wen
REGIST
PullRequest
cancelled
indeces
FOF
NoO
-1
View File
@@ -4,7 +4,6 @@
[submodule "opendbc"]
path = opendbc_repo
url = https://github.com/sunnypilot/opendbc.git
branch = tn
[submodule "msgq"]
path = msgq_repo
url = https://github.com/sunnypilot/msgq.git
+7
View File
@@ -21,5 +21,12 @@
</clean>
</configuration>
</target>
<target id="f2590b2b-9b93-49f9-8510-da3f3724a2ae" name="replay" defaultType="TOOL">
<configuration id="d475264f-6f4c-4092-9b4e-6773309f38b7" name="replay" toolchainName="Default">
<build type="TOOL">
<tool actionId="Tool_External Tools_uv build tools replay" />
</build>
</configuration>
</target>
</component>
</project>
+7
View File
@@ -20,4 +20,11 @@
<option name="WORKING_DIRECTORY" value="$ProjectFileDir$" />
</exec>
</tool>
<tool name="uv build tools replay" showInMainMenu="false" showInEditor="false" showInProject="false" showInSearchPopup="false" disabled="false" useConsole="true" showConsoleOnStdOut="false" showConsoleOnStdErr="false" synchronizeAfterRun="true">
<exec>
<option name="COMMAND" value="bash" />
<option name="PARAMETERS" value="-c &quot;source .venv/bin/activate &amp;&amp; scons -u -j$(nproc) tools/replay/&quot;" />
<option name="WORKING_DIRECTORY" value="$ProjectFileDir$" />
</exec>
</tool>
</toolSet>
+1 -1
View File
@@ -1,5 +1,5 @@
<component name="ProjectRunConfigurationManager">
<configuration default="false" name="Build Debug" type="CLionExternalRunConfiguration" factoryName="Application" REDIRECT_INPUT="false" ELEVATE="false" USE_EXTERNAL_CONSOLE="false" EMULATE_TERMINAL="false" WORKING_DIR="file://$ProjectFileDir$/selfdrive/ui" PASS_PARENT_ENVS_2="true" PROJECT_NAME="sunnypilot" TARGET_NAME="uv Scons Build Debug" CONFIG_NAME="uv Scons Build Debug" RUN_PATH="ui">
<configuration default="false" name="Build Debug" type="CLionExternalRunConfiguration" factoryName="Application" REDIRECT_INPUT="false" ELEVATE="false" USE_EXTERNAL_CONSOLE="false" EMULATE_TERMINAL="false" WORKING_DIR="file://$ProjectFileDir$/selfdrive/ui" PASS_PARENT_ENVS_2="true" PROJECT_NAME="openpilot-special" TARGET_NAME="uv Scons Build Debug" CONFIG_NAME="uv Scons Build Debug" RUN_PATH="ui">
<envs>
<env name="QT_DBL_CLICK_DIST" value="150" />
</envs>
+27
View File
@@ -0,0 +1,27 @@
<component name="ProjectRunConfigurationManager">
<configuration default="false" name="Debug Route Controls" type="PythonConfigurationType" factoryName="Python">
<module name="openpilot-special" />
<option name="ENV_FILES" value="" />
<option name="INTERPRETER_OPTIONS" value="" />
<option name="PARENT_ENVS" value="true" />
<envs>
<env name="PYTHONUNBUFFERED" value="1" />
<env name="FINGERPRINT" value="KIA_EV9" />
<env name="SKIP_FW_QUERY" value="1" />
</envs>
<option name="SDK_HOME" value="" />
<option name="WORKING_DIRECTORY" value="$PROJECT_DIR$/selfdrive/car" />
<option name="IS_MODULE_SDK" value="true" />
<option name="ADD_CONTENT_ROOTS" value="true" />
<option name="ADD_SOURCE_ROOTS" value="true" />
<EXTENSION ID="PythonCoverageRunConfigurationExtension" runner="coverage.py" />
<option name="SCRIPT_NAME" value="$PROJECT_DIR$/selfdrive/car/card.py" />
<option name="PARAMETERS" value="" />
<option name="SHOW_COMMAND_LINE" value="false" />
<option name="EMULATE_TERMINAL" value="true" />
<option name="MODULE_MODE" value="false" />
<option name="REDIRECT_INPUT" value="false" />
<option name="INPUT_FILE" value="" />
<method v="2" />
</configuration>
</component>
+7
View File
@@ -0,0 +1,7 @@
<component name="ProjectRunConfigurationManager">
<configuration default="false" name="Replay for controls + ui" type="Multirun" separateTabs="false" reuseTabsWithFailures="false" startOneByOne="true" markFailedProcess="true" hideSuccessProcess="false" delayTime="0.0">
<runConfiguration name="replay for controls" type="Native Application" />
<runConfiguration name="Build Debug" type="Custom Build Application" />
<method v="2" />
</configuration>
</component>
+7
View File
@@ -0,0 +1,7 @@
<component name="ProjectRunConfigurationManager">
<configuration default="false" name="replay for controls" type="CLionNativeAppRunConfigurationType" focusToolWindowBeforeRun="true" PROGRAM_PARAMS="&quot;$Prompt$&quot; --block &quot;sendcan,carState,carParams,carOutput,liveTracks,carParamsSP,carStateSP,bookmarkButton&quot;" REDIRECT_INPUT="false" ELEVATE="false" USE_EXTERNAL_CONSOLE="false" EMULATE_TERMINAL="true" WORKING_DIR="file://$ProjectFileDir$/tools/replay" PASS_PARENT_ENVS_2="true" PROJECT_NAME="openpilot-special" TARGET_NAME="replay" CONFIG_NAME="replay" version="1" RUN_PATH="replay">
<method v="2">
<option name="CLION.COMPOUND.BUILD" enabled="true" />
</method>
</configuration>
</component>
-30
View File
@@ -203,7 +203,6 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
aTarget @5 :Float32;
events @6 :List(OnroadEventSP.Event);
e2eAlerts @7 :E2eAlerts;
accelController @8 :AccelController;
struct DynamicExperimentalControl {
state @0 :DynamicExperimentalControlState;
@@ -306,35 +305,6 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
greenLightAlert @0 :Bool;
leadDepartAlert @1 :Bool;
}
struct AccelController {
enabled @0 :Bool;
active @1 :Bool;
shadowOnlyDEPRECATED @2 :Bool;
profile @3 :Profile;
state @4 :State;
enum Profile {
eco @0;
normal @1;
sport @2;
}
enum State {
inactive @0;
free @1;
restrict @2;
hold @3;
release @4;
stopHold @5;
}
}
enum AccelerationPersonality {
eco @0;
normal @1;
sport @2;
}
}
struct OnroadEventSP @0xda96579883444c35 {
-11
View File
@@ -187,12 +187,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
{"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
// toyota specific params
{"ToyotaAutoHold", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaEnhancedBsm", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaTSS2Long", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaDriveMode", {PERSISTENT | BACKUP, BOOL, "0"}},
// MADS params
{"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
{"MadsMainCruiseAllowed", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -233,15 +227,10 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"TeslaMadsScreenButton", {PERSISTENT | BACKUP, INT, "0"}},
{"ToyotaEnforceStockLongitudinal", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaStopAndGoHack", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaVirtualCruiseSpeed", {PERSISTENT | BACKUP, BOOL, "0"}},
{"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
{"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
// Accel Controller profiles (Eco / Normal / Sport)
{"AccelPersonalityEnabled", {PERSISTENT | BACKUP, BOOL, "0"}},
{"AccelPersonality", {PERSISTENT | BACKUP, INT, "1"}},
// sunnypilot model params
{"CameraOffset", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
{"LagdToggle", {PERSISTENT | BACKUP, BOOL, "1"}},
-4
View File
@@ -117,16 +117,12 @@ class TestParams(OpenpilotTestCase):
def test_params_default_value(self):
self.params.remove("LanguageSetting")
self.params.remove("LongitudinalPersonality")
self.params.remove("AccelPersonalityEnabled")
self.params.remove("AccelPersonality")
self.params.remove("LiveParametersV2")
assert self.params.get("LanguageSetting") is None
assert self.params.get("LanguageSetting", return_default=False) is None
assert isinstance(self.params.get("LanguageSetting", return_default=True), str)
assert isinstance(self.params.get("LongitudinalPersonality", return_default=True), int)
assert self.params.get("AccelPersonalityEnabled", return_default=True) is False
assert self.params.get("AccelPersonality", return_default=True) == 1
assert self.params.get("LiveParametersV2") is None
assert self.params.get("LiveParametersV2", return_default=True) is None
+2
View File
@@ -28,6 +28,8 @@ SP_BRANCH_MIGRATIONS = {
("tizi", "release3-staging"): "release-tizi-staging",
("mici", "release3"): "release-mici",
("mici", "release3-staging"): "release-mici-staging",
("tici", "hkg-angle-steering-2025"): "hkg-angle-steering-2025-tici",
("tici", "hkg-angle-steering-2025-prebuilt"): "hkg-angle-steering-2025-tici-prebuilt"
}
BUILD_METADATA_FILENAME = "build.json"
+1 -4
View File
@@ -11,13 +11,13 @@ from opendbc.car.structs import car
from openpilot.common.params import Params
from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
from openpilot.common.swaglog import cloudlog, ForwardingHandler
from opendbc.car import DT_CTRL, structs
from opendbc.car.can_definitions import CanData, CanRecvCallable, CanSendCallable
from opendbc.car.carlog import carlog
from opendbc.car.fw_versions import ObdCallback
from opendbc.car.car_helpers import get_car, interfaces
from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
from opendbc.safety import ALTERNATIVE_EXPERIENCE
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
@@ -123,9 +123,6 @@ class Car:
self.RI = RI
self.CP.alternativeExperience = 0
if self.params.get_bool("ToyotaAutoHold"):
self.CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.ALLOW_AEB
# mads
set_alternative_experience(self.CP, self.CP_SP, self.params)
set_car_specific_params(self.CP, self.CP_SP, self.params)
+7 -64
View File
@@ -19,7 +19,6 @@ IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1) # round here to avoid rounding err
ButtonEvent = car.CarState.ButtonEvent
ButtonType = car.CarState.ButtonEvent.Type
CRUISE_LONG_PRESS = 50
TOYOTA_VIRTUAL_CRUISE_LONG_PRESS = 65
CRUISE_NEAREST_FUNC = {
ButtonType.accelCruise: math.ceil,
ButtonType.decelCruise: math.floor,
@@ -44,30 +43,6 @@ class VCruiseHelper(VCruiseHelperSP):
def v_cruise_initialized(self):
return self.v_cruise_kph != V_CRUISE_UNSET
@property
def software_pcm_cruise_speed(self) -> bool:
return self.CP.brand == "toyota" and self.CP.pcmCruise and self.CP.openpilotLongitudinalControl and not self.CP_SP.pcmCruiseSpeed
@property
def cruise_long_press_frames(self) -> int:
return TOYOTA_VIRTUAL_CRUISE_LONG_PRESS if self.software_pcm_cruise_speed else CRUISE_LONG_PRESS
@property
def software_pcm_cruise_initialized(self) -> bool:
return 0 < self.v_cruise_kph < V_CRUISE_UNSET and 0 < self.v_cruise_cluster_kph < V_CRUISE_UNSET
def _apply_software_pcm_cruise_delta(self, delta_kph: float, is_metric: bool) -> None:
"""Move Toyota's planner/display targets together while respecting both targets' bounds."""
cluster_min_kph = self.v_cruise_min if is_metric else self.v_cruise_min * CV.MPH_TO_KPH
min_delta = max(V_CRUISE_MIN - self.v_cruise_kph, cluster_min_kph - self.v_cruise_cluster_kph)
max_delta = min(V_CRUISE_MAX - self.v_cruise_kph, V_CRUISE_MAX - self.v_cruise_cluster_kph)
if delta_kph > 0:
applied_delta = min(delta_kph, max(0., max_delta))
else:
applied_delta = max(delta_kph, min(0., min_delta))
self.v_cruise_kph = round(self.v_cruise_kph + applied_delta, 1)
self.v_cruise_cluster_kph = round(self.v_cruise_cluster_kph + applied_delta, 1)
def update_v_cruise(self, CS, enabled, is_metric):
self.v_cruise_kph_last = self.v_cruise_kph
@@ -76,21 +51,11 @@ class VCruiseHelper(VCruiseHelperSP):
_enabled = self.update_enabled_state(CS, enabled)
if CS.cruiseState.available:
software_pcm_enabled = not self.CP_SP.pcmCruiseSpeed and _enabled
if self.software_pcm_cruise_speed:
software_pcm_enabled = software_pcm_enabled and self.software_pcm_cruise_initialized
if not self.CP.pcmCruise or software_pcm_enabled:
if not self.CP.pcmCruise or (not self.CP_SP.pcmCruiseSpeed and _enabled):
# if stock cruise is completely disabled, then we can use our own set speed logic
self._update_v_cruise_non_pcm(CS, _enabled, is_metric)
v_cruise_kph_before_sla = self.v_cruise_kph
self.update_speed_limit_assist_v_cruise_non_pcm()
if self.software_pcm_cruise_speed:
sla_delta_kph = self.v_cruise_kph - v_cruise_kph_before_sla
self.v_cruise_kph = v_cruise_kph_before_sla
self._apply_software_pcm_cruise_delta(sla_delta_kph, is_metric)
else:
self.v_cruise_cluster_kph = self.v_cruise_kph
self.v_cruise_cluster_kph = self.v_cruise_kph
else:
self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH
self.v_cruise_cluster_kph = CS.cruiseState.speedCluster * CV.MS_TO_KPH
@@ -120,13 +85,13 @@ class VCruiseHelper(VCruiseHelperSP):
for b in CS.buttonEvents:
if b.type.raw in self.button_timers and not b.pressed:
if self.button_timers[b.type.raw] > self.cruise_long_press_frames:
if self.button_timers[b.type.raw] > CRUISE_LONG_PRESS:
return # end long press
button_type = b.type.raw
break
else:
for k, timer in self.button_timers.items():
if timer and timer % self.cruise_long_press_frames == 0:
if timer and timer % CRUISE_LONG_PRESS == 0:
button_type = k
long_press = True
break
@@ -150,26 +115,10 @@ class VCruiseHelper(VCruiseHelperSP):
return
long_press, v_cruise_delta = VCruiseHelperSP.update_v_cruise_delta(self, long_press, v_cruise_delta)
# Toyota's canonical PCM set speed and displayed cluster set speed can differ. In
# software-owned PCM mode, round the value the driver sees and apply the same delta
# to both targets so the planner/cluster calibration offset remains intact.
v_cruise_reference = self.v_cruise_cluster_kph if self.software_pcm_cruise_speed else self.v_cruise_kph
if long_press and v_cruise_reference % v_cruise_delta != 0: # partial interval
v_cruise_reference_new = CRUISE_NEAREST_FUNC[button_type](v_cruise_reference / v_cruise_delta) * v_cruise_delta
if long_press and self.v_cruise_kph % v_cruise_delta != 0: # partial interval
self.v_cruise_kph = CRUISE_NEAREST_FUNC[button_type](self.v_cruise_kph / v_cruise_delta) * v_cruise_delta
else:
v_cruise_reference_new = v_cruise_reference + v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
if self.software_pcm_cruise_speed:
delta_kph = v_cruise_reference_new - v_cruise_reference
# If SET is pressed while overriding, do not lower the target below the current speed.
if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
delta_kph = max(delta_kph, CS.vEgo * CV.MS_TO_KPH - self.v_cruise_kph)
self._apply_software_pcm_cruise_delta(delta_kph, is_metric)
return
self.v_cruise_kph += v_cruise_reference_new - v_cruise_reference
self.v_cruise_kph += v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
# If set is pressed while overriding, clip cruise speed to minimum of vEgo
if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
@@ -178,12 +127,6 @@ class VCruiseHelper(VCruiseHelperSP):
self.v_cruise_kph = np.clip(round(self.v_cruise_kph, 1), self.v_cruise_min, V_CRUISE_MAX)
def update_button_timers(self, CS, enabled):
if self.software_pcm_cruise_speed and (not enabled or not CS.cruiseState.available or not self.software_pcm_cruise_initialized):
for k in self.button_timers:
self.button_timers[k] = 0
self.button_change_states[k] = {"standstill": False, "enabled": False}
return
# increment timer for buttons still pressed
for k in self.button_timers:
if self.button_timers[k] > 0:
@@ -4,7 +4,6 @@ from openpilot.common.realtime import DT_CTRL
from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
from openpilot.common.pid import PIDController
from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import LongControlSP
CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
@@ -40,9 +39,8 @@ def long_control_state_trans(CP_SP, active, long_control_state,
return long_control_state
class LongControl(LongControlSP):
class LongControl:
def __init__(self, CP, CP_SP):
LongControlSP.__init__(self)
self.CP = CP
self.CP_SP = CP_SP
self.long_control_state = LongCtrlState.off
@@ -62,7 +60,6 @@ class LongControl(LongControlSP):
self.long_control_state = long_control_state_trans(self.CP_SP, active, self.long_control_state,
should_stop, CS.brakePressed,
CS.cruiseState.standstill)
LongControlSP.update_state(self, self.long_control_state == LongCtrlState.stopping)
if self.long_control_state == LongCtrlState.off:
self.reset()
output_accel = 0.
@@ -72,7 +69,7 @@ class LongControl(LongControlSP):
if output_accel > self.CP.stopAccel:
output_accel = min(output_accel, 0.0)
# TODO: can we just go straight to stopAccel?
output_accel -= LongControlSP.stopping_decel_rate(self, CS, a_target) * DT_CTRL
output_accel -= 1.0 * DT_CTRL # m/s^2/s while trying to stop
self.reset()
else: # LongCtrlState.pid
@@ -77,7 +77,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
def update(self, sm):
LongitudinalPlannerSP.update(self, sm)
self.previous_plan_accel = self.output_a_target
if len(sm['carControl'].orientationNED) == 3:
accel_coast = get_coast_accel(sm['carControl'].orientationNED[1])
@@ -100,10 +99,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
throttle_probs = sm['modelV2'].meta.disengagePredictions.gasPressProbs
throttle_prob = throttle_probs[1] if len(throttle_probs) > 1 else 1.0
stock_allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
self.allow_throttle = self.accel_controller.update_allow_throttle(
stock_allow_throttle, throttle_prob, force_allow=v_ego <= MIN_ALLOW_THROTTLE_SPEED,
)
self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['vehicleParameters'].angleOffsetDeg
@@ -143,25 +139,25 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
output_should_stop_e2e = sm['modelV2'].action.shouldStop
is_e2e = self.is_e2e(sm)
output_a_target_model = self.select_model_accel(
output_a_target_mpc, output_a_target_e2e, blended=is_e2e,
should_stop=output_should_stop_e2e or output_should_stop_mpc, fcw=self.fcw, reset=reset_state,
)
if self.is_e2e(sm):
output_a_target = min(output_a_target_e2e, output_a_target_mpc)
self.output_should_stop = output_should_stop_e2e or output_should_stop_mpc
if output_a_target < output_a_target_mpc:
self.mpc.source = LongitudinalPlanSource.e2e
else:
output_a_target = output_a_target_mpc
self.output_should_stop = output_should_stop_mpc
self.a_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego,
self.a_cruise = get_cruise_accel(sm['selfdriveState'].experimentalMode, v_cruise, v_ego,
self.a_cruise, steer_angle_without_offset, self.CP, self.dt,
accel_coast, self.allow_throttle)
cruise_should_stop = should_stop(v_ego, self.a_cruise)
candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
(self.a_cruise, LongitudinalPlanSource.cruise, cruise_should_stop)]
if is_e2e:
candidates.append((output_a_target_model, LongitudinalPlanSource.e2e, output_should_stop_e2e))
elif self.model_accel_transition.active:
candidates[0] = (output_a_target_model, self.mpc.source, output_should_stop_mpc)
if sm['selfdriveState'].experimentalMode:
candidates.append((output_a_target_e2e, LongitudinalPlanSource.e2e, output_should_stop_e2e))
candidates = self.update_accel_controller(sm, candidates)
output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
@@ -11,14 +11,6 @@ from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPl
from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
class PlannerSM(dict):
def __init__(self, radar_frame: int, services: dict):
super().__init__(services)
self.logMonoTime = {"radarState": radar_frame}
self.valid = {"radarState": True}
self.alive = {"radarState": True}
class Plant:
messaging_initialized = False
@@ -140,7 +132,7 @@ class Plant:
car_control.carControl.orientationNED = [0., float(pitch), 0.]
# ******** get controlsState messages for plotting ***
sm = PlannerSM(self.rk.frame, {'radarState': radar.radarState,
sm = {'radarState': radar.radarState,
'carState': car_state.carState,
'carControl': car_control.carControl,
'controlsState': control.controlsState,
@@ -149,7 +141,7 @@ class Plant:
'modelV2': model.modelV2,
'carStateSP': car_state_sp.carStateSP,
'liveMapDataSP': live_map_data_sp.liveMapDataSP,
'gpsLocation': gps_data.gpsLocation})
'gpsLocation': gps_data.gpsLocation}
self.planner.update(sm)
self.acceleration = self.planner.output_a_target
if self.planner.output_should_stop:
@@ -27,12 +27,6 @@ DESCRIPTIONS = {
"In relaxed mode sunnypilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with " +
"your steering wheel distance button."
),
"AccelPersonalityEnabled": tr_noop(
"Begin slowing early and smoothly behind lead vehicles. Stock longitudinal control retains braking and stopping authority."
),
"AccelPersonality": tr_noop(
"Eco slows earliest and recovers gently, Normal balances comfort and response, and Sport reacts and recovers more quickly."
),
"IsLdwEnabled": tr_noop(
"Receive alerts to steer back into the lane when your vehicle drifts over a detected lane line " +
"without a turn signal activated while driving over 31 mph (50 km/h)."
@@ -112,24 +106,6 @@ class TogglesLayout(Widget):
icon="speed_limit.png"
)
self._accel_personality_enabled = toggle_item(
lambda: tr("Enable Accel Controller"),
lambda: tr(DESCRIPTIONS["AccelPersonalityEnabled"]),
self._params.get_bool("AccelPersonalityEnabled"),
callback=self._set_accel_personality_enabled,
icon="speed_limit.png",
)
self._accel_personality_setting = multiple_button_item(
lambda: tr("Acceleration Profile"),
lambda: tr(DESCRIPTIONS["AccelPersonality"]),
buttons=[lambda: tr("Eco"), lambda: tr("Normal"), lambda: tr("Sport")],
button_width=300,
callback=self._set_accel_personality,
selected_index=self._params.get("AccelPersonality", return_default=True),
icon="speed_limit.png"
)
self._toggles = {}
self._locked_toggles = set()
for param, (title, desc, icon, needs_restart) in self._toggle_defs.items():
@@ -159,11 +135,9 @@ class TogglesLayout(Widget):
self._toggles[param] = toggle
# insert longitudinal personality and Accel Controller settings after NDOG toggle
# insert longitudinal personality after NDOG toggle
if param == "DisengageOnAccelerator":
self._toggles["LongitudinalPersonality"] = self._long_personality_setting
self._toggles["AccelPersonalityEnabled"] = self._accel_personality_enabled
self._toggles["AccelPersonality"] = self._accel_personality_setting
self._update_experimental_mode_icon()
self._scroller = Scroller(list(self._toggles.values()), line_separator=True, spacing=0)
@@ -184,7 +158,6 @@ class TogglesLayout(Widget):
def _update_toggles(self):
ui_state.update_params()
accel_personality_enabled = self._params.get_bool("AccelPersonalityEnabled")
e2e_description = tr(
"sunnypilot defaults to driving in chill mode. Experimental mode enables alpha-level features that aren't ready for chill mode. " +
@@ -203,15 +176,11 @@ class TogglesLayout(Widget):
self._toggles["ExperimentalMode"].action_item.set_enabled(True)
self._toggles["ExperimentalMode"].set_description(e2e_description)
self._long_personality_setting.action_item.set_enabled(True)
self._accel_personality_enabled.action_item.set_enabled(True)
self._accel_personality_setting.action_item.set_enabled(accel_personality_enabled)
else:
# no long for now
self._toggles["ExperimentalMode"].action_item.set_enabled(False)
self._toggles["ExperimentalMode"].action_item.set_state(False)
self._long_personality_setting.action_item.set_enabled(False)
self._accel_personality_enabled.action_item.set_enabled(False)
self._accel_personality_setting.action_item.set_enabled(False)
self._params.remove("ExperimentalMode")
unavailable = tr("Experimental mode is currently unavailable on this car since the car's stock ACC is used for longitudinal control.")
@@ -234,10 +203,6 @@ class TogglesLayout(Widget):
# refresh toggles from params to mirror external changes
for param in self._toggle_defs:
self._toggles[param].action_item.set_state(self._params.get_bool(param))
self._accel_personality_enabled.action_item.set_state(accel_personality_enabled)
self._accel_personality_setting.action_item.set_selected_button(
self._params.get("AccelPersonality", return_default=True)
)
# these toggles need restart, block while engaged
for toggle_def in self._toggle_defs:
@@ -282,10 +247,3 @@ class TogglesLayout(Widget):
def _set_longitudinal_personality(self, button_index: int):
self._params.put("LongitudinalPersonality", button_index, block=True)
def _set_accel_personality(self, button_index: int):
self._params.put("AccelPersonality", button_index, block=True)
def _set_accel_personality_enabled(self, state: bool):
self._params.put_bool("AccelPersonalityEnabled", state, block=True)
self._accel_personality_setting.action_item.set_enabled(state and ui_state.has_longitudinal_control)
+2 -8
View File
@@ -14,7 +14,6 @@ from openpilot.system.ui.lib.application import gui_app
if gui_app.sunnypilot_ui():
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.settings import SettingsLayoutSP as SettingsLayout
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.home import MiciHomeLayoutSP as MiciHomeLayout
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad import OnroadViewContainerSP as AugmentedRoadView
ONROAD_DELAY = 2.5 # seconds
@@ -73,9 +72,6 @@ class MiciMainLayout(Scroller):
# For scroll_to
return self._body_onroad_layout if ui_state.is_body else self._car_onroad_layout
def _should_auto_scroll_to_onroad(self) -> bool:
return True
def _setup_callbacks(self):
self._home_layout.set_callbacks(
on_settings=lambda: gui_app.push_widget(self._settings_layout),
@@ -126,15 +122,13 @@ class MiciMainLayout(Scroller):
# 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:
if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
self._onroad_time_delay = None
# When car leaves standstill, pop nav stack and scroll to onroad
CS = ui_state.sm["carState"]
if not CS.standstill and self._prev_standstill:
if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
self._prev_standstill = CS.standstill
def _on_interactive_timeout(self):
@@ -42,8 +42,6 @@ class TogglesLayoutMici(NavScroller):
super().__init__()
self._personality_toggle = BigMultiParamToggle("driving personality", "LongitudinalPersonality", ["aggressive", "standard", "relaxed"])
self._accel_personality_enabled = BigParamControl("enable accel controller", "AccelPersonalityEnabled")
self._accel_personality_toggle = BigMultiParamToggle("acceleration profile", "AccelPersonality", ["eco", "normal", "sport"])
self._experimental_btn = BigToggle("experimental mode", initial_state=ui_state.params.get_bool("ExperimentalMode"),
toggle_callback=self._on_experimental_mode)
is_metric_toggle = BigParamControl("use metric units", "IsMetric")
@@ -55,8 +53,6 @@ class TogglesLayoutMici(NavScroller):
self._scroller.add_widgets([
self._personality_toggle,
self._accel_personality_enabled,
self._accel_personality_toggle,
self._experimental_btn,
is_metric_toggle,
ldw_toggle,
@@ -69,7 +65,6 @@ class TogglesLayoutMici(NavScroller):
# Toggle lists
self._refresh_toggles = (
("ExperimentalMode", self._experimental_btn),
("AccelPersonalityEnabled", self._accel_personality_enabled),
("IsMetric", is_metric_toggle),
("IsLdwEnabled", ldw_toggle),
("AlwaysOnDM", always_on_dm_toggle),
@@ -79,9 +74,6 @@ class TogglesLayoutMici(NavScroller):
)
enable_openpilot.set_enabled(lambda: not ui_state.engaged)
self._accel_personality_toggle.set_enabled(
lambda: ui_state.has_longitudinal_control and ui_state.params.get_bool("AccelPersonalityEnabled")
)
record_front.set_enabled(False if ui_state.params.get_bool("RecordFrontLock") else (lambda: not ui_state.engaged))
record_mic.set_enabled(lambda: not ui_state.engaged)
@@ -112,23 +104,17 @@ class TogglesLayoutMici(NavScroller):
if ui_state.has_longitudinal_control:
self._experimental_btn.set_visible(True)
self._personality_toggle.set_visible(True)
self._accel_personality_enabled.set_visible(True)
self._accel_personality_toggle.set_visible(True)
else:
# no long for now
self._experimental_btn.set_visible(False)
self._experimental_btn.set_checked(False)
self._personality_toggle.set_visible(False)
self._accel_personality_enabled.set_visible(False)
self._accel_personality_toggle.set_visible(False)
ui_state.params.remove("ExperimentalMode")
# Refresh toggles from params to mirror external changes
for key, item in self._refresh_toggles:
item.set_checked(ui_state.params.get_bool(key))
self._accel_personality_toggle.refresh()
def _on_experimental_mode(self, state: bool):
if state and not ui_state.params.get_bool("ExperimentalModeConfirmed"):
# Don't show enabled state until confirm
@@ -154,8 +154,8 @@ class ModelRenderer(Widget, ModelRendererSP):
self._draw_lane_lines()
self._draw_path(sm)
if render_lead_indicator and radar_state:
self._draw_lead_indicator()
# if render_lead_indicator and radar_state:
# self._draw_lead_indicator()
def _update_raw_points(self, model):
"""Update raw 3D points from model data"""
@@ -385,18 +385,13 @@ class BigMultiParamToggle(BigMultiToggle):
self._load_value()
def _load_value(self):
value = self._params.get(self._param, return_default=True)
index = value if isinstance(value, int) else 0
self.set_value(self._options[max(0, min(index, len(self._options) - 1))])
self.set_value(self._options[self._params.get(self._param) or 0])
def _handle_mouse_release(self, mouse_pos: MousePos):
super()._handle_mouse_release(mouse_pos)
new_idx = self._options.index(self.value)
self._params.put(self._param, new_idx)
def refresh(self):
self._load_value()
class BigParamControl(BigToggle):
def __init__(self, text: str, param: str, toggle_callback: Callable | None = None):
@@ -143,8 +143,7 @@ class CruiseLayout(Widget):
self.icbm_toggle.show_description(True)
if has_long or has_icbm:
software_cruise_speed = has_long and (not ui_state.CP.pcmCruise or not ui_state.CP_SP.pcmCruiseSpeed)
self.custom_acc_toggle.action_item.set_enabled((software_cruise_speed or has_icbm) and ui_state.is_offroad())
self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
self.dec_toggle.action_item.set_enabled(has_long)
self.scc_v_toggle.action_item.set_enabled(True)
self.scc_m_toggle.action_item.set_enabled(True)
@@ -170,7 +169,7 @@ class CruiseLayout(Widget):
show_custom_acc_desc = True
else:
if has_long or has_icbm:
if has_long and ui_state.CP.pcmCruise and ui_state.CP_SP.pcmCruiseSpeed:
if has_long and ui_state.CP.pcmCruise:
new_custom_acc_desc = tr(ACC_PCMCRUISE_DISABLED_DESCRIPTION)
show_custom_acc_desc = True
else:
@@ -11,12 +11,10 @@ from openpilot.system.ui.lib.multilang import tr, tr_noop
from openpilot.system.ui.widgets import DialogResult
from openpilot.system.ui.widgets.confirm_dialog import ConfirmDialog
from openpilot.system.ui.sunnypilot.widgets.list_view import toggle_item_sp
from opendbc.sunnypilot.car.toyota.values import ToyotaFlagsSP
ONROAD_ONLY_DESCRIPTION = tr_noop("Start the vehicle to check vehicle compatibility.")
SNG_HACK_UNAVAILABLE = tr_noop("sunnypilot Longitudinal Control must be available and enabled for your vehicle to use this feature.")
VIRTUAL_CRUISE_UNAVAILABLE = tr_noop("Virtual Cruise Speed is available only on supported Toyota TSS2 configurations with sunnypilot Longitudinal Control.")
DESCRIPTIONS = {
'enforce_stock_longitudinal': tr_noop(
@@ -25,14 +23,7 @@ DESCRIPTIONS = {
'stop_and_go_hack': tr_noop(
'sunnypilot will allow some Toyota/Lexus cars to auto resume during stop and go traffic. ' +
'This feature is only applicable to certain models that are able to use longitudinal control. This is an alpha feature. Use at your own risk.'
),
'virtual_cruise_speed': tr_noop(
'Use a sunnypilot-owned cruise target with the Toyota RES/SET buttons while sunnypilot longitudinal control is active. ' +
'This unlocks Custom ACC Speed Increments; set the short interval to 5 for next-5-unit tap behavior. ' +
'The Toyota cluster will continue to show the factory target and may differ from sunnypilot. ' +
'The direct button signals are route-validated on Corolla Cross and Prius TSS2, but held-button timing differs by platform. ' +
'This is an alpha feature; validate acceleration above the factory target in a controlled setting.'
),
)
}
@@ -56,17 +47,8 @@ class ToyotaSettings(BrandSettings):
enabled=lambda: not ui_state.engaged,
)
self.virtual_cruise_speed = toggle_item_sp(
lambda: tr("Virtual Cruise Speed (Alpha)"),
description=lambda: tr(DESCRIPTIONS["virtual_cruise_speed"]),
initial_state=ui_state.params.get_bool("ToyotaVirtualCruiseSpeed"),
callback=self._on_enable_virtual_cruise_speed,
enabled=lambda: not ui_state.engaged,
)
self.items = [
self.enforce_stock_longitudinal,
self.virtual_cruise_speed,
self.stop_and_go_hack,
]
@@ -78,9 +60,7 @@ class ToyotaSettings(BrandSettings):
if ui_state.params.get_bool("AlphaLongitudinalEnabled"):
ui_state.params.put_bool("AlphaLongitudinalEnabled", False)
ui_state.params.put_bool("ToyotaStopAndGoHack", False)
ui_state.params.put_bool("ToyotaVirtualCruiseSpeed", False)
self.stop_and_go_hack.action_item.set_state(False)
self.virtual_cruise_speed.action_item.set_state(False)
ui_state.params.put_bool("OnroadCycleRequested", True)
else:
self.enforce_stock_longitudinal.action_item.set_state(False)
@@ -114,46 +94,10 @@ class ToyotaSettings(BrandSettings):
ui_state.params.put_bool("ToyotaStopAndGoHack", False)
ui_state.params.put_bool("OnroadCycleRequested", True)
def _on_enable_virtual_cruise_speed(self, state: bool):
if state:
def confirm_callback(result: int):
enabled = result == DialogResult.CONFIRM
ui_state.params.put_bool("ToyotaVirtualCruiseSpeed", enabled)
self.virtual_cruise_speed.action_item.set_state(enabled)
if enabled:
ui_state.params.put_bool("OnroadCycleRequested", True)
content = (f"<h1>{self.virtual_cruise_speed.title}</h1><br>" +
f"<p>{self.virtual_cruise_speed.description}</p>")
dlg = ConfirmDialog(content, tr("Enable"), rich=True, callback=confirm_callback)
gui_app.push_widget(dlg)
else:
ui_state.params.put_bool("ToyotaVirtualCruiseSpeed", False)
ui_state.params.put_bool("OnroadCycleRequested", True)
def update_settings(self):
if ui_state.CP is not None:
longitudinal = ui_state.CP.openpilotLongitudinalControl
enforce_stock = self.enforce_stock_longitudinal.action_item.get_state()
virtual_cruise_available = bool(ui_state.CP_SP is not None and
ui_state.CP_SP.flags & ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE)
if longitudinal and virtual_cruise_available:
self.virtual_cruise_speed.action_item.set_enabled(not ui_state.engaged)
virtual_cruise_desc = tr(DESCRIPTIONS["virtual_cruise_speed"])
show_virtual_cruise_desc = False
else:
self.virtual_cruise_speed.action_item.set_enabled(False)
if self.virtual_cruise_speed.action_item.get_state():
self.virtual_cruise_speed.action_item.set_state(False)
ui_state.params.put_bool("ToyotaVirtualCruiseSpeed", False)
virtual_cruise_desc = "<b>" + tr(VIRTUAL_CRUISE_UNAVAILABLE) + "</b>\n\n" + tr(DESCRIPTIONS["virtual_cruise_speed"])
show_virtual_cruise_desc = True
if self.virtual_cruise_speed.description != virtual_cruise_desc:
self.virtual_cruise_speed.set_description(virtual_cruise_desc)
if show_virtual_cruise_desc:
self.virtual_cruise_speed.show_description(True)
if longitudinal and not enforce_stock:
self.stop_and_go_hack.action_item.set_enabled(not ui_state.engaged)
@@ -170,12 +114,6 @@ class ToyotaSettings(BrandSettings):
if show_desc:
self.stop_and_go_hack.show_description(True)
else:
self.virtual_cruise_speed.action_item.set_enabled(False)
virtual_cruise_desc = "<b>" + tr(ONROAD_ONLY_DESCRIPTION) + "</b>\n\n" + tr(DESCRIPTIONS["virtual_cruise_speed"])
if self.virtual_cruise_speed.description != virtual_cruise_desc:
self.virtual_cruise_speed.set_description(virtual_cruise_desc)
self.virtual_cruise_speed.show_description(True)
self.stop_and_go_hack.action_item.set_enabled(False)
new_desc = "<b>" + tr(ONROAD_ONLY_DESCRIPTION) + "</b>\n\n" + tr(DESCRIPTIONS["stop_and_go_hack"])
if self.stop_and_go_hack.description != new_desc:
@@ -1,19 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
class MiciMainLayoutSP(MiciMainLayout):
def __init__(self):
super().__init__()
scroller = self._scroller
scroller.scroll_panel = GuiScrollPanel2SP(scroller._horizontal, handle_out_of_bounds=not scroller._snap_items)
def _should_auto_scroll_to_onroad(self) -> bool:
return not self._onroad_layout.is_on_info_panel()
@@ -1,64 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from collections.abc import Callable
import pyray as rl
from openpilot.system.ui.lib.application import gui_app
from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroller_sp import ScrollerSP
from openpilot.selfdrive.ui.sunnypilot.mici.onroad.augmented_road_view import AugmentedRoadViewSP
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad_info_panel import OnroadInfoPanel
CONFIDENCE_BALL_VISIBLE_RATIO = 0.4
HORIZONTAL_SETTLE_PX = 5
HORIZONTAL_RESET_RATIO = 0.5
class OnroadViewContainerSP(ScrollerSP):
def __init__(self, bookmark_callback=None):
super().__init__(horizontal=False, snap_items=True, spacing=0, pad=0, scroll_indicator=False, edge_shadows=False)
self.road_view = AugmentedRoadViewSP(bookmark_callback=bookmark_callback)
self.onroad_info_panel = OnroadInfoPanel(bookmark_callback=bookmark_callback)
self._scroller.add_widgets([
self.road_view,
self.onroad_info_panel,
])
self._scroller.set_reset_scroll_at_show(False)
self._scroller.set_scrolling_enabled(lambda: abs(self.rect.x) < HORIZONTAL_SETTLE_PX)
for child in (self.road_view, self.onroad_info_panel):
inner_touch_valid = child._touch_valid_callback
child.set_touch_valid_callback(
lambda inner=inner_touch_valid: self._touch_valid() and (inner() if inner else True)
)
def set_rect(self, rect: rl.Rectangle):
super().set_rect(rect)
self.road_view.set_rect(rect)
self.onroad_info_panel.set_rect(rect)
return self
def is_swiping_left(self) -> bool:
return self.road_view.is_swiping_left() or self.onroad_info_panel.is_swiping_left()
def set_click_callback(self, click_callback: Callable[[], None] | None) -> None:
self.road_view.set_click_callback(click_callback)
self.onroad_info_panel.set_click_callback(click_callback)
def is_on_info_panel(self) -> bool:
"""True when scrolled past halfway toward onroad_info_panel (used by main layout
to skip auto-pop-back-to-camera while user is reading the info panel)."""
return abs(self._scroller.scroll_panel.get_offset()) > self._rect.height / 2
def _render(self, rect: rl.Rectangle):
if abs(self.rect.x) > gui_app.width * HORIZONTAL_RESET_RATIO:
self._scroller.scroll_panel.set_offset(0)
vertical_offset = self._scroller.scroll_panel.get_offset()
show_ball = abs(vertical_offset) < rect.height * CONFIDENCE_BALL_VISIBLE_RATIO
self.road_view.set_show_confidence_ball(show_ball)
super()._render(rect)
@@ -1,403 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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 pyray as rl
from dataclasses import dataclass, field
from openpilot.common.constants import CV
from openpilot.common.filter_simple import FirstOrderFilter
from openpilot.selfdrive.ui.ui_state import ui_state
from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
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
from openpilot.selfdrive.ui.mici.onroad.alert_renderer import AlertRenderer
from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import BookmarkIcon
METER_TO_KM = 0.001
METER_TO_MILE = 0.000621371
CONTENT_MARGIN = 16
SPEED_LIMIT_SIGN_WIDTH = 146
VIENNA_SIGN_SIZE = 146
MUTCD_SIGN_HEIGHT = 178
OFFSET_BADGE_SIZE = 50
OFFSET_BADGE_PANEL_PADDING = 4
MUTCD_OFFSET_SIGN_Y_SHIFT = 6
VIENNA_BADGE_X_RATIO = 0.80
VIENNA_BADGE_UPCOMING_X_RATIO = 0.70
VIENNA_BADGE_Y_RATIO = -0.82
UPCOMING_SIGN_SIZE_RATIO = 0.76
UPCOMING_SIGN_OVERLAP_RATIO = 0.05
UNIT_FONT_SIZE = 40
SPEED_FONT_SIZE = 114
ROAD_FONT_SIZE = 32
SCC_TAG_WIDTH = 78
SCC_TAG_HEIGHT = 30
SCC_TAG_GAP = 5
COLUMN_GAP = 12
@dataclass(frozen=True)
class OnroadInfoPanelColors:
white: rl.Color = rl.WHITE
black: rl.Color = rl.BLACK
red: rl.Color = field(default_factory=lambda: rl.Color(255, 0, 0, 255))
green: rl.Color = field(default_factory=lambda: rl.Color(0, 255, 0, 255))
grey: rl.Color = field(default_factory=lambda: rl.Color(190, 195, 190, 255))
light_grey: rl.Color = field(default_factory=lambda: rl.Color(200, 200, 200, 255))
dark_grey: rl.Color = field(default_factory=lambda: rl.Color(100, 100, 100, 255))
bg_dark: rl.Color = field(default_factory=lambda: rl.Color(0, 0, 0, 255))
card_bg: rl.Color = field(default_factory=lambda: rl.Color(50, 50, 50, 200))
badge_bg: rl.Color = field(default_factory=lambda: rl.Color(60, 60, 60, 255))
COLORS = OnroadInfoPanelColors()
class OnroadInfoPanel(Widget):
def __init__(self, bookmark_callback=None):
super().__init__()
self.speed_limit: float = 0.0
self.speed_limit_valid: bool = False
self.speed_limit_offset: float = 0.0
self.next_speed_limit: float = 0.0
self.next_speed_limit_distance: float = 0.0
self.road_name: str = ""
self.current_speed: float = 0.0
self.set_speed: float = 0.0
self.cruise_enabled: bool = False
self._sign_slide: float = 0.0
self._font_bold: rl.Font = gui_app.font(FontWeight.BOLD)
self._font_semi_bold: rl.Font = gui_app.font(FontWeight.SEMI_BOLD)
self._font_medium: rl.Font = gui_app.font(FontWeight.MEDIUM)
self._marquee_offset: float = 0.0
self._marquee_direction: int = 1
self._marquee_pause_timer: float = 0.0
self._marquee_speed: float = 40.0
self._marquee_pause_duration: float = 1.5
self._alert_renderer = AlertRenderer()
self._alert_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
self._bookmark_icon = BookmarkIcon(bookmark_callback)
def is_swiping_left(self) -> bool:
return self._bookmark_icon.is_swiping_left()
def _handle_mouse_release(self, mouse_pos: MousePos) -> None:
# Mirror stock AugmentedRoadView: suppress click while bookmark gesture active
if not self._bookmark_icon.interacting():
super()._handle_mouse_release(mouse_pos)
def _update_state(self) -> None:
sm = ui_state.sm
speed_conv = CV.MS_TO_KPH if ui_state.is_metric else CV.MS_TO_MPH
if sm.valid["longitudinalPlanSP"]:
lp_sp = sm["longitudinalPlanSP"]
resolver = lp_sp.speedLimit.resolver
self.speed_limit = resolver.speedLimit * speed_conv
self.speed_limit_valid = resolver.speedLimitValid
self.speed_limit_offset = resolver.speedLimitOffset * speed_conv
if sm.valid["liveMapDataSP"]:
lmd = sm["liveMapDataSP"]
self.next_speed_limit = lmd.speedLimitAhead * speed_conv
self.next_speed_limit_distance = lmd.speedLimitAheadDistance
self.road_name = lmd.roadName
if sm.updated["carState"]:
self.current_speed = sm["carState"].vEgo * speed_conv
if sm.valid["carState"] and sm.valid["controlsState"]:
self.cruise_enabled = sm["carState"].cruiseState.enabled
v_cruise_cluster = sm["carState"].vCruiseCluster
set_speed_kph = sm["controlsState"].vCruiseDEPRECATED if v_cruise_cluster == 0.0 else v_cruise_cluster
self.set_speed = set_speed_kph * (METER_TO_MILE / METER_TO_KM) if not ui_state.is_metric else set_speed_kph
def _render(self, rect: rl.Rectangle) -> None:
self._update_state()
rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), COLORS.bg_dark)
left_x = rect.x + CONTENT_MARGIN
if self.cruise_enabled:
unit = tr("MAX")
display_speed = self.set_speed
else:
unit = tr("km/h") if ui_state.is_metric else tr("MPH")
display_speed = self.current_speed
display_speed_text = str(round(display_speed))
if self.speed_limit_valid and display_speed > self.speed_limit:
speed_color = COLORS.red
else:
speed_color = COLORS.white
sign_width = min(SPEED_LIMIT_SIGN_WIDTH, rect.width * 0.30)
sign_height = VIENNA_SIGN_SIZE if ui_state.is_metric else MUTCD_SIGN_HEIGHT
has_upcoming_limit = self.next_speed_limit > 0 and self.next_speed_limit != self.speed_limit
target_sign_slide = 1.0 if has_upcoming_limit else 0.0
slide_speed = 3.0 * rl.get_frame_time()
if self._sign_slide < target_sign_slide:
self._sign_slide = min(self._sign_slide + slide_speed, target_sign_slide)
elif self._sign_slide > target_sign_slide:
self._sign_slide = max(self._sign_slide - slide_speed, target_sign_slide)
upcoming_width = int(sign_width * UPCOMING_SIGN_SIZE_RATIO)
upcoming_height = int(sign_height * UPCOMING_SIGN_SIZE_RATIO)
upcoming_reserved_width = int(upcoming_width * 0.85) + 5
sign_x_without_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN
sign_x_with_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN - upcoming_reserved_width
sign_x = sign_x_without_upcoming + (sign_x_with_upcoming - sign_x_without_upcoming) * self._sign_slide
sign_y = rect.y + (rect.height - sign_height) / 2
if not ui_state.is_metric and self.speed_limit_offset != 0 and self.speed_limit_valid:
sign_y += MUTCD_OFFSET_SIGN_Y_SHIFT
readout_right = sign_x - COLUMN_GAP
readout_width = max(1, readout_right - left_x)
road_y = rect.y + rect.height - 44
unit_font_size = self._fit_font_size(self._font_semi_bold, unit, readout_width, 46, UNIT_FONT_SIZE, 28)
speed_font_size = self._fit_font_size(self._font_bold, display_speed_text, readout_width, road_y - (rect.y + 54) - 8,
SPEED_FONT_SIZE, 76)
speed_size = measure_text_cached(self._font_bold, display_speed_text, speed_font_size)
speed_y = min(rect.y + 54, road_y - speed_size.y - 8)
unit_y = max(rect.y + 14, speed_y - unit_font_size - 6)
rl.draw_text_ex(self._font_semi_bold, unit, rl.Vector2(left_x, unit_y), unit_font_size, 0, COLORS.grey)
rl.draw_text_ex(self._font_bold, display_speed_text, rl.Vector2(left_x, speed_y), speed_font_size, 0, speed_color)
self._draw_road_name(left_x, road_y, readout_width)
if has_upcoming_limit and self._sign_slide > 0.01:
upcoming_speed_text = str(round(self.next_speed_limit))
distance_text = self._format_distance(self.next_speed_limit_distance)
upcoming_x = sign_x + sign_width - int(upcoming_width * UPCOMING_SIGN_OVERLAP_RATIO)
upcoming_y = sign_y + (sign_height - upcoming_height) / 2
upcoming_speed_color = COLORS.black
if ui_state.is_metric:
self._draw_vienna_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
else:
self._draw_mutcd_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
distance_font_size = self._fit_font_size(self._font_medium, distance_text, upcoming_width, 30, 24, 16)
distance_size = measure_text_cached(self._font_medium, distance_text, distance_font_size)
rl.draw_text_ex(self._font_medium, distance_text, rl.Vector2(upcoming_x + upcoming_width / 2 - distance_size.x / 2, upcoming_y + upcoming_height),
distance_font_size, 0, COLORS.grey)
self._draw_speed_limit_sign(sign_x, sign_y, sign_width, sign_height)
if self.speed_limit_offset != 0 and self.speed_limit_valid:
offset_text = str(abs(round(self.speed_limit_offset)))
badge_size = OFFSET_BADGE_SIZE
badge_rect = self._offset_badge_rect(rect, sign_x, sign_y, sign_width, sign_height, badge_size, has_upcoming_limit)
if ui_state.is_metric:
badge_radius = badge_size / 2
badge_center_x = badge_rect.x + badge_radius
badge_center_y = badge_rect.y + badge_radius
rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius + 2, COLORS.dark_grey)
rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius, COLORS.badge_bg)
self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_center_x, badge_center_y), COLORS.white,
badge_size - 10, badge_size - 8, min_size=24)
else:
rl.draw_rectangle_rounded(badge_rect, 0.25, 10, COLORS.badge_bg)
rl.draw_rectangle_rounded_lines_ex(badge_rect, 0.25, 10, 2, COLORS.dark_grey)
self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_rect.x + badge_size / 2, badge_rect.y + badge_size / 2),
COLORS.white, badge_size - 10, badge_size - 8, min_size=24)
scc_tag_x = min(left_x + speed_size.x + COLUMN_GAP, readout_right - SCC_TAG_WIDTH)
scc_tag_y = speed_y + (speed_size.y - (SCC_TAG_HEIGHT * 2 + SCC_TAG_GAP)) / 2
if scc_tag_x >= left_x + speed_size.x + 8:
self._draw_scc_icons(scc_tag_x, scc_tag_y, readout_right)
self._bookmark_icon.render(rect)
if ui_state.started:
alert_obj, no_alert = self._alert_renderer.will_render()
self._alert_alpha_filter.update(0 if no_alert else 1)
alpha = self._alert_alpha_filter.x
if alpha > 0.01:
rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), rl.Color(0, 0, 0, int(150 * alpha)))
self._alert_renderer.render(rect)
def _draw_scc_icons(self, x: float, y: float, right_limit: float) -> None:
sm = ui_state.sm
if not sm.valid["longitudinalPlanSP"]:
return
scc = sm["longitudinalPlanSP"].smartCruiseControl
drawn = 0
for label, active in [("SCC-V", scc.vision.active), ("SCC-M", scc.map.active)]:
if not active:
continue
tag_x = x
if tag_x + SCC_TAG_WIDTH > right_limit:
return
tag_y = y + drawn * (SCC_TAG_HEIGHT + SCC_TAG_GAP)
rl.draw_rectangle_rounded(rl.Rectangle(tag_x, tag_y, SCC_TAG_WIDTH, SCC_TAG_HEIGHT), 0.3, 10, COLORS.green)
self._draw_text_centered_fit(self._font_bold, label, 18, rl.Vector2(tag_x + SCC_TAG_WIDTH / 2, tag_y + SCC_TAG_HEIGHT / 2), COLORS.black,
SCC_TAG_WIDTH - 10, SCC_TAG_HEIGHT - 4, min_size=14)
drawn += 1
def _draw_speed_limit_sign(self, x: float, y: float, sign_width: float, sign_height: float) -> None:
speed_str = str(round(self.speed_limit)) if self.speed_limit_valid and self.speed_limit > 0 else "--"
speed_color = COLORS.black if not self.speed_limit_valid or self.current_speed <= self.speed_limit else COLORS.red
if ui_state.is_metric:
self._draw_vienna_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
else:
self._draw_mutcd_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
def _draw_road_name(self, x: float, y: float, width: float) -> None:
if width <= 0:
return
road_display = self.road_name if self.road_name else "--"
font_size = self._fit_font_size(self._font_semi_bold, road_display, width, 38, ROAD_FONT_SIZE, 28)
road_size = measure_text_cached(self._font_semi_bold, road_display, font_size)
text_width = road_size.x
if text_width <= width:
self._marquee_offset = 0.0
self._marquee_direction = 1
self._marquee_pause_timer = 0.0
rl.draw_text_ex(self._font_semi_bold, road_display, rl.Vector2(x, y), font_size, 0, COLORS.white)
else:
overflow = text_width - width
dt = rl.get_frame_time()
if self._marquee_pause_timer > 0:
self._marquee_pause_timer -= dt
else:
self._marquee_offset += self._marquee_direction * self._marquee_speed * dt
if self._marquee_offset >= overflow:
self._marquee_offset = overflow
self._marquee_direction = -1
self._marquee_pause_timer = self._marquee_pause_duration
elif self._marquee_offset <= 0:
self._marquee_offset = 0
self._marquee_direction = 1
self._marquee_pause_timer = self._marquee_pause_duration
rl.begin_scissor_mode(int(x), int(y), int(width), int(road_size.y + 4))
text_pos = rl.Vector2(x - self._marquee_offset, y)
rl.draw_text_ex(self._font_semi_bold, road_display, text_pos, font_size, 0, COLORS.white)
rl.end_scissor_mode()
def _draw_vienna_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
center = rl.Vector2(x + width / 2, y + height / 2)
outer_radius = min(width, height) / 2
rl.draw_circle_v(center, outer_radius, COLORS.white)
ring_width = outer_radius * 0.18
rl.draw_ring(center, outer_radius - ring_width, outer_radius, 0, 360, 36, COLORS.red)
font_size = outer_radius * (0.7 if len(speed_str) >= 3 else 0.9)
self._draw_text_centered_fit(self._font_bold, speed_str, int(font_size), center, speed_color, width * 0.72, height * 0.50, min_size=24)
def _draw_mutcd_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
sign_rect = rl.Rectangle(x, y, width, height)
rl.draw_rectangle_rounded(sign_rect, 0.35, 10, COLORS.white)
inset = max(4, width * 0.05)
inner_rect = rl.Rectangle(x + inset, y + inset, width - inset * 2, height - inset * 2)
outer_radius = 0.35 * width / 2.0
inner_radius = outer_radius - inset
inner_roundness = inner_radius / (inner_rect.width / 2.0)
rl.draw_rectangle_rounded_lines_ex(inner_rect, inner_roundness, 10, 3, COLORS.black)
mid_x = x + width / 2
label_size = max(18, int(width * 0.26))
if is_upcoming:
self._draw_text_centered_fit(self._font_bold, tr("AHEAD"), int(width * 0.34), rl.Vector2(mid_x, y + height * 0.28), COLORS.black,
width * 0.94, height * 0.32, min_size=20)
else:
self._draw_text_centered_fit(self._font_bold, tr("SPEED"), label_size, rl.Vector2(mid_x, y + height * 0.20), COLORS.black,
width * 0.84, height * 0.24, min_size=16)
self._draw_text_centered_fit(self._font_bold, tr("LIMIT"), label_size, rl.Vector2(mid_x, y + height * 0.40), COLORS.black,
width * 0.84, height * 0.24, min_size=16)
speed_font_size = int(width * 0.60) if len(speed_str) >= 3 else int(width * 0.72)
self._draw_text_centered_fit(self._font_bold, speed_str, speed_font_size, rl.Vector2(mid_x, y + height * 0.72), speed_color,
width * 0.90, height * 0.52, min_size=32)
def _draw_text_centered(self, font, text, size, pos_center, color):
sz = measure_text_cached(font, text, size)
rl.draw_text_ex(font, text, rl.Vector2(pos_center.x - sz.x / 2, pos_center.y - sz.y / 2), size, 0, color)
def _draw_text_centered_fit(self, font, text, size, pos_center, color, max_width: float, max_height: float, min_size: int = 10):
size = self._fit_font_size(font, text, max_width, max_height, size, min_size)
self._draw_text_centered(font, text, size, pos_center, color)
def _fit_font_size(self, font, text: str, max_width: float, max_height: float, max_size: int | float, min_size: int) -> int:
size = int(max_size)
while size > min_size:
text_size = measure_text_cached(font, text, size)
if text_size.x <= max_width and text_size.y <= max_height:
return size
size -= 2
return min_size
def _offset_badge_rect(self, panel_rect: rl.Rectangle, sign_x: float, sign_y: float, sign_width: float, sign_height: float,
badge_size: float, has_upcoming_limit: bool) -> rl.Rectangle:
if ui_state.is_metric:
radius = min(sign_width, sign_height) / 2
center_x = sign_x + sign_width / 2
center_y = sign_y + sign_height / 2
badge_x_ratio = VIENNA_BADGE_UPCOMING_X_RATIO if has_upcoming_limit else VIENNA_BADGE_X_RATIO
badge_center_x = center_x + radius * badge_x_ratio
badge_center_y = center_y + radius * VIENNA_BADGE_Y_RATIO
badge_x = badge_center_x - badge_size / 2
badge_y = badge_center_y - badge_size / 2
else:
badge_x = sign_x + sign_width - badge_size * 0.45
badge_y = sign_y - badge_size * 0.75
return rl.Rectangle(
self._clamp(
badge_x,
panel_rect.x + OFFSET_BADGE_PANEL_PADDING,
panel_rect.x + panel_rect.width - badge_size - OFFSET_BADGE_PANEL_PADDING,
),
self._clamp(
badge_y,
panel_rect.y + OFFSET_BADGE_PANEL_PADDING,
panel_rect.y + panel_rect.height - badge_size - OFFSET_BADGE_PANEL_PADDING,
),
badge_size,
badge_size,
)
@staticmethod
def _clamp(value: float, min_value: float, max_value: float) -> float:
return max(min_value, min(max_value, value))
def _format_distance(self, distance: float) -> str:
if ui_state.is_metric:
if distance < 50:
return tr("Near")
if distance >= 1000:
return f"{distance * METER_TO_KM:.1f}" + tr("km")
if distance < 200:
rounded = max(10, int(distance / 10) * 10)
else:
rounded = int(distance / 100) * 100
return str(rounded) + tr("m")
else:
distance_mi = distance * METER_TO_MILE
if distance_mi < 0.1:
return tr("Near")
return f"{distance_mi:.1f}" + tr("mi")
@@ -1,29 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import AugmentedRoadView
class _SuppressedConfidenceBall:
def render(self, *_):
pass
class AugmentedRoadViewSP(AugmentedRoadView):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self._show_confidence_ball: bool = True
self._real_confidence_ball = self._confidence_ball
self._confidence_ball = _SuppressedConfidenceBall()
def set_show_confidence_ball(self, show: bool) -> None:
self._show_confidence_ball = show
def _render(self, _) -> None:
super()._render(_)
if self._show_confidence_ball:
self._real_confidence_ball.render(self.rect)
@@ -1,83 +0,0 @@
import pyray as rl
from openpilot.common.test import OpenpilotTestCase
from openpilot.system.ui.lib.application import MouseEvent, MousePos, gui_app
from openpilot.system.ui.lib.scroll_panel2 import ScrollState
from openpilot.system.ui.widgets import Widget
from openpilot.system.ui.widgets import scroller as scroller_mod
from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
class DummyScrollIndicator:
def update(self, *_) -> None:
pass
def render(self) -> None:
pass
class DummyWidget(Widget):
def __init__(self, rect: rl.Rectangle):
super().__init__()
self.set_rect(rect)
def _render(self, _) -> None:
pass
def _mouse_event(x: float, y: float, *, pressed: bool = False, released: bool = False,
down: bool = True, t: float = 0.0) -> MouseEvent:
return MouseEvent(MousePos(x, y), 0, pressed, released, down, t)
class TestScrollerSP(OpenpilotTestCase):
def test_vertical_snap_items_are_supported(self, monkeypatch):
monkeypatch.setattr(scroller_mod, "ScrollIndicator", DummyScrollIndicator)
scroller = scroller_mod._Scroller([], horizontal=False, snap_items=True, scroll_indicator=False)
scroller.set_rect(rl.Rectangle(0, 0, 100, 100))
scroller.scroll_panel.set_offset(-60)
captured_snap_target = None
def update(_, __, snap_target=None):
nonlocal captured_snap_target
captured_snap_target = snap_target
return scroller.scroll_panel.get_offset()
monkeypatch.setattr(scroller.scroll_panel, "update", update)
visible_items: list[Widget] = [
DummyWidget(rl.Rectangle(0, -60, 100, 100)),
DummyWidget(rl.Rectangle(0, 40, 100, 100)),
]
scroller._get_scroll(visible_items, 200)
assert captured_snap_target == -100
def test_scroll_panel_sp_rejects_orthogonal_drags(self, monkeypatch):
panel = GuiScrollPanel2SP(horizontal=True)
bounds = rl.Rectangle(0, 0, 100, 100)
monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(10, 10, pressed=True, t=1.0)])
panel.update(bounds, 200)
assert panel.state == ScrollState.PRESSED
monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(23, 60, t=1.1)])
panel.update(bounds, 200)
assert panel.state == ScrollState.STEADY
assert panel.get_offset() == 0
def test_scroll_panel_sp_can_disable_out_of_bounds_handling(self, monkeypatch):
panel = GuiScrollPanel2SP(horizontal=False, handle_out_of_bounds=False)
bounds = rl.Rectangle(0, 0, 100, 100)
monkeypatch.setattr(gui_app, "_mouse_events", [])
panel.set_offset(20)
panel.update(bounds, 200)
assert panel.get_offset() == 0
panel.set_offset(-150)
panel.update(bounds, 200)
assert panel.get_offset() == -100
@@ -1,33 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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 pyray as rl
from openpilot.system.ui.lib.application import MouseEvent
from openpilot.system.ui.lib.scroll_panel2 import GuiScrollPanel2, ScrollState
class GuiScrollPanel2SP(GuiScrollPanel2):
"""Scroll panel behavior for nested Mici pagers."""
def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
super().__init__(horizontal, handle_out_of_bounds=handle_out_of_bounds)
def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
content_size: float) -> None:
state_before_update = self._state
super()._handle_mouse_event(mouse_event, bounds, bounds_size, content_size)
if self._state == ScrollState.MANUAL_SCROLL and state_before_update == ScrollState.PRESSED and \
self._initial_click_event is not None:
drag_x = abs(mouse_event.pos.x - self._initial_click_event.pos.x)
drag_y = abs(mouse_event.pos.y - self._initial_click_event.pos.y)
primary_drag = drag_x if self._horizontal else drag_y
cross_drag = drag_y if self._horizontal else drag_x
if cross_drag > primary_drag:
self._state = ScrollState.STEADY
self._velocity = 0.0
self._velocity_buffer.clear()
@@ -1,16 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from openpilot.system.ui.widgets.scroller import Scroller
from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
class ScrollerSP(Scroller):
def __init__(self, **kwargs):
super().__init__(**kwargs)
inner = self._scroller
inner.scroll_panel = GuiScrollPanel2SP(inner._horizontal, handle_out_of_bounds=not inner._snap_items)
@@ -252,7 +252,7 @@ class FrictionCoefficientElement:
ltp = sm['lateralTorqueParameters']
value = f"{ltp.frictionCoefficientFiltered:.3f}"
color = rl.Color(0, 255, 0, 255) if ltp.valid else rl.WHITE
color = rl.Color(0, 255, 0, 255) if ltp.liveValid else rl.WHITE
return UiElement(value, "FRIC.", self.unit, color)
@@ -266,7 +266,7 @@ class LatAccelFactorElement:
ltp = sm['lateralTorqueParameters']
value = f"{ltp.latAccelFactorFiltered:.3f}"
color = rl.Color(0, 255, 0, 255) if ltp.valid else rl.WHITE
color = rl.Color(0, 255, 0, 255) if ltp.liveValid else rl.WHITE
return UiElement(value, "L.A.F.", self.unit, color)
-3
View File
@@ -10,9 +10,6 @@ from openpilot.selfdrive.ui.layouts.main import MainLayout
from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
from openpilot.selfdrive.ui.ui_state import ui_state
if gui_app.sunnypilot_ui():
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.main import MiciMainLayoutSP as MiciMainLayout
BIG_UI = gui_app.big_ui()
@@ -115,7 +115,7 @@ class IntelligentCruiseButtonManagement:
self.is_ready = ready and not button_pressed
def run(self, CS: car.CarState, CC: car.CarControl, LP_SP: custom.LongitudinalPlanSP, is_metric: bool) -> None:
if self.CP_SP.pcmCruiseSpeed or not self.CP_SP.intelligentCruiseButtonManagementAvailable:
if self.CP_SP.pcmCruiseSpeed:
return
self.is_metric = is_metric
@@ -136,10 +136,6 @@ def initialize_params(params) -> list[dict[str, Any]]:
keys.extend([
"ToyotaEnforceStockLongitudinal",
"ToyotaStopAndGoHack",
"ToyotaTSS2Long",
"ToyotaEnhancedBsm",
"ToyotaAutoHold",
"ToyotaVirtualCruiseSpeed",
])
return [{k: params.get(k, return_default=True)} for k in keys]
@@ -1,26 +1,14 @@
from opendbc.can.parser import CANParser
from opendbc.car import create_button_events
from opendbc.car.structs import car
from opendbc.car.toyota.carstate import get_virtual_cruise_button, VIRTUAL_CRUISE_BUTTONS
from openpilot.cereal import custom
from openpilot.common.constants import CV
from openpilot.common.parameterized import parameterized, parameterized_class
from openpilot.common.params import Params
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.car.cruise import TOYOTA_VIRTUAL_CRUISE_LONG_PRESS, VCruiseHelper, V_CRUISE_INITIAL, V_CRUISE_UNSET
from openpilot.selfdrive.car.cruise import V_CRUISE_INITIAL
from openpilot.selfdrive.car.tests.test_cruise_speed import TestVCruiseHelper
from openpilot.sunnypilot.selfdrive.car.interfaces import initialize_params
ButtonEvent = car.CarState.ButtonEvent
ButtonType = car.CarState.ButtonEvent.Type
class TestToyotaParamsHandoff(OpenpilotTestCase):
def test_tss2_long_tuning_param_is_forwarded_to_opendbc(self):
keys = {next(iter(entry)) for entry in initialize_params(Params())}
assert "ToyotaTSS2Long" in keys
# TODO: test pcmCruise and pcmCruiseSpeed
@parameterized_class(('pcm_cruise', 'pcm_cruise_speed'), [(False, True)])
class TestCustomAccIncrements(TestVCruiseHelper):
@@ -126,8 +114,8 @@ class TestCustomAccIncrements(TestVCruiseHelper):
def test_rounding_behavior(self):
"""Test rounding behavior for 5 and 10 increments"""
test_cases = [
(47, 5, 50), # 47 -> 50 (round up to next 5)
(45, 5, 50), # 45 -> 50 (already at 5, increment by 5)
(47, 5, 50), # 47 -> 50 (round up to next 5)
(45, 5, 50), # 45 -> 50 (already at 5, increment by 5)
(43, 10, 50), # 43 -> 50 (round up to next 10)
(40, 10, 50), # 40 -> 50 (already at 10, increment by 10)
]
@@ -158,302 +146,3 @@ class TestCustomAccIncrements(TestVCruiseHelper):
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_long(ButtonType.accelCruise)
assert self.v_cruise_helper.v_cruise_kph == initial_speed + 10 # Should fallback to 10
class TestToyotaVirtualCruiseSpeed(OpenpilotTestCase):
def setup_method(self):
self.params = Params()
self.params.put_bool("CustomAccIncrementsEnabled", True, block=True)
self.params.put("CustomAccShortPressIncrement", 5, block=True)
self.params.put("CustomAccLongPressIncrement", 5, block=True)
CP = car.CarParams(brand="toyota", pcmCruise=True, openpilotLongitudinalControl=True)
CP_SP = custom.CarParamsSP(pcmCruiseSpeed=False)
self.v_cruise_helper = VCruiseHelper(CP, CP_SP)
self.v_cruise_helper.read_custom_set_speed_params()
self.route_parser = CANParser("toyota_nodsu_pt_generated", [("CLUTCH", 16)], 0)
self.route_button = 0
@staticmethod
def car_state(canonical_kph, cluster_kph, *, available=True, standstill=False, gas_pressed=False, v_ego_kph=0.0, button_events=None):
CS = car.CarState(
gasPressed=gas_pressed,
vEgo=v_ego_kph * CV.KPH_TO_MS,
cruiseState={
"available": available,
"speed": canonical_kph * CV.KPH_TO_MS,
"speedCluster": cluster_kph * CV.KPH_TO_MS,
"standstill": standstill,
},
)
CS.buttonEvents = button_events or []
return CS
def seed_enabled(self, canonical_kph, cluster_kph, *, is_metric=True):
CS = self.car_state(canonical_kph, cluster_kph)
self.v_cruise_helper.update_v_cruise(CS, enabled=False, is_metric=is_metric)
self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
assert self.v_cruise_helper.v_cruise_kph == canonical_kph
assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
def press(self, button_type, canonical_kph, cluster_kph, hold_frames=0, *, standstill=False, gas_pressed=False, v_ego_kph=0.0, is_metric=True):
pressed = [ButtonEvent(type=button_type, pressed=True)]
self.v_cruise_helper.update_v_cruise(
self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=pressed),
enabled=True,
is_metric=is_metric,
)
for _ in range(hold_frames):
self.v_cruise_helper.update_v_cruise(
self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph),
enabled=True,
is_metric=is_metric,
)
released = [ButtonEvent(type=button_type, pressed=False)]
self.v_cruise_helper.update_v_cruise(
self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=released),
enabled=True,
is_metric=is_metric,
)
def set_increments(self, short_increment, long_increment):
self.params.put("CustomAccShortPressIncrement", short_increment, block=True)
self.params.put("CustomAccLongPressIncrement", long_increment, block=True)
self.v_cruise_helper.read_custom_set_speed_params()
def assert_kph_almost_equal(self, actual, expected):
self.assertAlmostEqual(actual, expected, delta=abs(expected) * 1e-6)
def route_button_events(self, payload):
self.route_parser.update((1, [(0x361, bytes.fromhex(payload), 0)]))
current = get_virtual_cruise_button(
self.route_parser.vl["CLUTCH"]["CRUISE_RES"],
self.route_parser.vl["CLUTCH"]["CRUISE_SET"],
)
events = create_button_events(current, self.route_button, VIRTUAL_CRUISE_BUTTONS)
self.route_button = current
return events
def test_short_press_rounds_display_target_and_preserves_offset(self):
self.seed_enabled(27, 31)
self.press(ButtonType.accelCruise, 28, 32)
assert self.v_cruise_helper.v_cruise_kph == 31
assert self.v_cruise_helper.v_cruise_cluster_kph == 35
def test_decel_at_display_minimum_does_not_increase_target(self):
self.seed_enabled(26, 30)
self.press(ButtonType.decelCruise, 25, 29)
assert self.v_cruise_helper.v_cruise_kph == 26
assert self.v_cruise_helper.v_cruise_cluster_kph == 30
@parameterized.expand((52, TOYOTA_VIRTUAL_CRUISE_LONG_PRESS - 1))
def test_route_length_short_press_is_not_a_long_press(self, hold_frames):
self.set_increments(short_increment=2, long_increment=5)
self.seed_enabled(27, 31)
self.press(ButtonType.accelCruise, 28, 32, hold_frames=hold_frames)
assert self.v_cruise_helper.v_cruise_kph == 29
assert self.v_cruise_helper.v_cruise_cluster_kph == 33
def test_toyota_long_press_uses_route_validated_cadence_and_suppresses_release(self):
self.set_increments(short_increment=2, long_increment=5)
self.seed_enabled(27, 31)
pressed = [ButtonEvent(type=ButtonType.accelCruise, pressed=True)]
self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
self.v_cruise_helper.update_v_cruise(self.car_state(31, 35), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == 31
assert self.v_cruise_helper.v_cruise_cluster_kph == 35
released = [ButtonEvent(type=ButtonType.accelCruise, pressed=False)]
self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=released), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == 31
assert self.v_cruise_helper.v_cruise_cluster_kph == 35
def test_route_4_32_second_hold_repeats_six_times(self):
self.seed_enabled(26, 30)
self.press(ButtonType.accelCruise, 30, 34, hold_frames=432)
assert self.v_cruise_helper.v_cruise_kph == 56
assert self.v_cruise_helper.v_cruise_cluster_kph == 60
def test_maximum_boundary_caps_pair_and_preserves_offset(self):
self.seed_enabled(141, 145)
self.press(ButtonType.accelCruise, 142, 146)
assert self.v_cruise_helper.v_cruise_kph == 141
assert self.v_cruise_helper.v_cruise_cluster_kph == 145
self.press(ButtonType.accelCruise, 143, 147)
assert self.v_cruise_helper.v_cruise_kph == 141
assert self.v_cruise_helper.v_cruise_cluster_kph == 145
@parameterized.expand(
(
(25, 29, ButtonType.decelCruise),
(141, 147, ButtonType.accelCruise),
)
)
def test_out_of_range_raw_pair_is_not_moved_in_opposite_direction(self, canonical_kph, cluster_kph, button_type):
self.seed_enabled(canonical_kph, cluster_kph)
self.press(button_type, canonical_kph, cluster_kph)
assert self.v_cruise_helper.v_cruise_kph == canonical_kph
assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
def test_imperial_increment_preserves_canonical_cluster_pair(self):
self.seed_enabled(45, 50, is_metric=False)
self.press(ButtonType.accelCruise, 46, 51, is_metric=False)
assert self.v_cruise_helper.v_cruise_kph == 51
assert self.v_cruise_helper.v_cruise_cluster_kph == 56
def test_engagement_button_held_does_not_change_target(self):
initial = self.car_state(27, 31)
self.v_cruise_helper.update_v_cruise(initial, enabled=False, is_metric=True)
pressed = [ButtonEvent(type=ButtonType.decelCruise, pressed=True)]
self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=False, is_metric=True)
for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS + 10):
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
released = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == 28
assert self.v_cruise_helper.v_cruise_cluster_kph == 32
def test_delayed_pcm_target_seeds_before_software_ownership(self):
invalid = self.car_state(0, 0)
self.v_cruise_helper.update_v_cruise(invalid, enabled=False, is_metric=True)
release = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
for _ in range(4):
self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, button_events=release), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
self.v_cruise_helper.update_v_cruise(self.car_state(27, 31), enabled=True, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
def test_route_payload_short_press_drives_virtual_target(self):
self.seed_enabled(27, 31)
pressed = self.route_button_events("a61a0000561a1a81")
self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
for _ in range(52):
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
released = self.route_button_events("861a0000561b1a81")
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == 31
assert self.v_cruise_helper.v_cruise_cluster_kph == 35
def test_prius_route_payload_short_set_drives_virtual_target(self):
self.seed_enabled(31, 35)
pressed = self.route_button_events("965f000056666585")
self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
for _ in range(45):
self.v_cruise_helper.update_v_cruise(self.car_state(30, 34), enabled=True, is_metric=True)
released = self.route_button_events("865f000056666585")
self.v_cruise_helper.update_v_cruise(self.car_state(30, 34, button_events=released), enabled=True, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == 26
assert self.v_cruise_helper.v_cruise_cluster_kph == 30
def test_prius_route_payload_standstill_res_does_not_change_target(self):
self.seed_enabled(27, 31)
pressed = self.route_button_events("a61b0000561c1c80")
self.v_cruise_helper.update_v_cruise(
self.car_state(27, 31, standstill=True, button_events=pressed),
enabled=True,
is_metric=True,
)
for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, standstill=True), enabled=True, is_metric=True)
released = self.route_button_events("865f000056666585")
self.v_cruise_helper.update_v_cruise(
self.car_state(27, 31, standstill=True, button_events=released),
enabled=True,
is_metric=True,
)
assert self.v_cruise_helper.v_cruise_kph == 27
assert self.v_cruise_helper.v_cruise_cluster_kph == 31
def test_route_payload_disengage_mid_hold_clears_pending_action(self):
self.seed_enabled(27, 31)
pressed = self.route_button_events("a61a0000561a1a81")
self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
for _ in range(30):
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
released = self.route_button_events("861a0000561b1a81")
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, available=False, button_events=released), enabled=False, is_metric=True)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
def test_standstill_resume_does_not_change_target(self):
self.seed_enabled(27, 31)
self.press(ButtonType.accelCruise, 27, 31, standstill=True)
assert self.v_cruise_helper.v_cruise_kph == 27
assert self.v_cruise_helper.v_cruise_cluster_kph == 31
def test_disengagement_discards_virtual_target_and_reseeds_raw_pair(self):
self.seed_enabled(27, 31)
self.press(ButtonType.accelCruise, 28, 32)
assert self.v_cruise_helper.v_cruise_kph == 31
raw = self.car_state(28, 32)
self.v_cruise_helper.update_v_cruise(raw, enabled=False, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
def test_unavailable_and_mads_handback_discard_virtual_target(self):
self.seed_enabled(27, 31)
self.press(ButtonType.accelCruise, 28, 32)
assert self.v_cruise_helper.v_cruise_kph == 31
self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, available=False), enabled=False, is_metric=True)
assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
self.v_cruise_helper.update_v_cruise(self.car_state(29, 33), enabled=False, is_metric=True)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 29)
self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 33)
def test_set_during_gas_override_clips_target_to_ego_speed(self):
self.seed_enabled(27, 31)
self.press(ButtonType.decelCruise, 26, 30, gas_pressed=True, v_ego_kph=50)
assert self.v_cruise_helper.v_cruise_kph == 50
assert self.v_cruise_helper.v_cruise_cluster_kph == 54
@@ -1,160 +0,0 @@
import math
from dataclasses import dataclass
from openpilot.cereal import custom
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.sunnypilot import get_sanitize_int_param
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.constants import (
COMFORT_DECEL, EARLY_DECEL_EPSILON, EARLY_DECEL_RELEASE_RATE, EARLY_DECEL_RESPONSE_TIME,
EARLY_DECEL_SPEED_DEADBAND, EARLY_DECEL_TIGHTEN_RATE, PARAM_READ_INTERVAL, THROTTLE_REENABLE_PROB,
VEGO_NOISE_TOLERANCE, AccelProfile, profile_accel_max, sanitize_profile,
)
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.lead import LeadPlan, calculate_lead_plan
AccelControllerState = custom.LongitudinalPlanSP.AccelController.State
@dataclass(frozen=True)
class AccelDecision:
cruise_accel_max: float | None = None
early_decel: float | None = None
active: bool = False
class AccelController:
def __init__(self, CP, dt: float = DT_MDL):
if not math.isfinite(dt) or dt <= 0.0:
raise ValueError("dt must be finite and positive")
self.dt = float(dt)
self.delay = float(CP.longitudinalActuatorDelay) + DT_MDL
self.params = Params()
self.available = bool(CP.openpilotLongitudinalControl)
self.enabled = False
self.profile = AccelProfile.normal
self._param_read_frames = max(1, int(round(PARAM_READ_INTERVAL / self.dt)))
self._param_frame = 0
self._early_decel: float | None = None
self.is_active = False
self.cruise_accel_max: float | None = None
self.early_decel: float | None = None
self.state = AccelControllerState.inactive
self.selected_lead = -1
self.selected_lead_track_id = -1
self.required_decel = 0.0
self._allow_throttle = True
@property
def is_enabled(self) -> bool:
return self.available and self.enabled
def update_params(self) -> None:
if self._param_frame % self._param_read_frames == 0:
self.enabled = self.params.get_bool("AccelPersonalityEnabled")
self.profile = get_sanitize_int_param("AccelPersonality", AccelProfile.eco, AccelProfile.sport, self.params)
self._param_frame += 1
def reset(self) -> None:
self._early_decel = None
self._allow_throttle = True
self.is_active = False
self.cruise_accel_max = None
self.early_decel = None
self.state = AccelControllerState.inactive
self.selected_lead = -1
self.selected_lead_track_id = -1
self.required_decel = 0.0
def update_allow_throttle(self, stock_allowed: bool, throttle_prob: float, *, force_allow: bool = False) -> bool:
if not self.is_enabled or force_allow:
self._allow_throttle = bool(stock_allowed)
elif self._allow_throttle:
self._allow_throttle = bool(stock_allowed)
elif stock_allowed and math.isfinite(throttle_prob) and throttle_prob > THROTTLE_REENABLE_PROB:
self._allow_throttle = True
return self._allow_throttle
def _valid_context(self, *, v_ego: float, a_ego: float, v_cruise: float, stock_accel_max: float,
engaged: bool, cruise_initialized: bool) -> bool:
values = (v_ego, a_ego, v_cruise, stock_accel_max, self.delay)
return (engaged and cruise_initialized and v_ego >= -VEGO_NOISE_TOLERANCE and v_cruise >= 0.0
and self.delay >= 0.0 and all(math.isfinite(value) for value in values))
def _raw_early_decel(self, lead_plan: LeadPlan) -> float:
speed_error = lead_plan.speed_ceiling - lead_plan.v_ego_projected
if (lead_plan.selected_lead < 0 or lead_plan.closing_speed <= 0.0
or speed_error >= -EARLY_DECEL_SPEED_DEADBAND):
return 0.0
comfort_decel = COMFORT_DECEL[self.profile]
return max(speed_error / EARLY_DECEL_RESPONSE_TIME, -comfort_decel)
def _update_early_decel(self, raw_target: float, previous_plan_accel: float) -> None:
raw_target = min(float(raw_target), 0.0)
plan_accel = float(previous_plan_accel) if math.isfinite(previous_plan_accel) else 0.0
previous = self._early_decel if self._early_decel is not None else max(plan_accel, 0.0)
if raw_target < previous - EARLY_DECEL_EPSILON:
updated = max(raw_target, previous - EARLY_DECEL_TIGHTEN_RATE * self.dt)
state = AccelControllerState.restrict
elif raw_target > previous + EARLY_DECEL_EPSILON:
updated = min(raw_target, previous + EARLY_DECEL_RELEASE_RATE * self.dt)
state = AccelControllerState.release
else:
updated = raw_target
state = AccelControllerState.hold if updated < -EARLY_DECEL_EPSILON else AccelControllerState.free
if raw_target >= -EARLY_DECEL_EPSILON and updated >= -EARLY_DECEL_EPSILON:
self._early_decel = None
self.early_decel = None
self.state = AccelControllerState.free
else:
self._early_decel = updated
self.early_decel = updated
self.state = state
def update(self, radar_state, *, v_ego: float, a_ego: float, v_cruise: float, follow_personality,
engaged: bool, cruise_initialized: bool, acc_selected: bool, stock_accel_max: float,
radar_fresh: bool = True, radar_healthy: bool = True, force_decel: bool = False,
previous_plan_accel: float = 0.0) -> AccelDecision:
self.profile = sanitize_profile(self.profile)
valid_context = self._valid_context(
v_ego=v_ego, a_ego=a_ego, v_cruise=v_cruise, stock_accel_max=stock_accel_max,
engaged=engaged, cruise_initialized=cruise_initialized,
)
if not (self.is_enabled and valid_context and bool(acc_selected) and not force_decel):
self.reset()
return AccelDecision()
sanitized_v_ego = max(float(v_ego), 0.0)
positive_stock_max = max(float(stock_accel_max), 0.0)
self.cruise_accel_max = profile_accel_max(self.profile, sanitized_v_ego, positive_stock_max)
if radar_healthy and not radar_fresh:
if self._early_decel is not None:
self.state = AccelControllerState.hold
else:
lead_plan = LeadPlan(v_ego_projected=sanitized_v_ego)
if radar_healthy and radar_state is not None:
try:
lead_plan = calculate_lead_plan(
radar_state, sanitized_v_ego, float(a_ego), self.delay, self.profile, follow_personality,
)
except (AttributeError, TypeError, ValueError):
lead_plan = LeadPlan(v_ego_projected=sanitized_v_ego)
self.selected_lead = lead_plan.selected_lead
self.selected_lead_track_id = lead_plan.selected_lead_track_id
self.required_decel = lead_plan.required_decel
self._update_early_decel(self._raw_early_decel(lead_plan), previous_plan_accel)
profile_binding = self.cruise_accel_max < positive_stock_max - EARLY_DECEL_EPSILON
self.is_active = profile_binding or self.early_decel is not None
return AccelDecision(
cruise_accel_max=self.cruise_accel_max,
early_decel=self.early_decel,
active=self.is_active,
)
@@ -1,54 +0,0 @@
import math
import numpy as np
from openpilot.cereal import custom
AccelProfile = custom.LongitudinalPlanSP.AccelController.Profile
ACCEL_PROFILES = tuple(AccelProfile.schema.enumerants.values())
# Scale the stock cruise candidate; stock turn and throttle limits stay authoritative.
ACCEL_SCALE_BP = [0.0, 3.0, 10.0, 25.0, 40.0]
ACCEL_SCALE_V = {
AccelProfile.eco: [0.82, 0.76, 0.63, 0.53, 0.42],
AccelProfile.normal: [0.95, 0.90, 0.84, 0.76, 0.63],
AccelProfile.sport: [1.00, 1.00, 1.00, 1.00, 1.00],
}
# Smaller values start slowing earlier; stock MPC still owns lead braking.
COMFORT_DECEL = {
AccelProfile.eco: 0.25,
AccelProfile.normal: 0.30,
AccelProfile.sport: 0.35,
}
EARLY_DECEL_RESPONSE_TIME = 1.0
EARLY_DECEL_SPEED_DEADBAND = 0.15
EARLY_DECEL_TIGHTEN_RATE = 1.0
EARLY_DECEL_RELEASE_RATE = 0.35
EARLY_DECEL_EPSILON = 1e-6
STOP_GAP_RESERVE = 0.75
MAX_LEAD_ACCEL_TAU = 10.0
MIN_LEAD_SPEED = -1.0
VEGO_NOISE_TOLERANCE = 0.10
PARAM_READ_INTERVAL = 0.25
THROTTLE_REENABLE_PROB = 0.45
def sanitize_profile(profile: int) -> int:
return profile if profile in ACCEL_PROFILES else AccelProfile.normal
def profile_accel_scale(profile: int, v_ego: float) -> float:
if not math.isfinite(v_ego):
return math.nan
return float(np.interp(max(v_ego, 0.0), ACCEL_SCALE_BP, ACCEL_SCALE_V[sanitize_profile(profile)]))
def profile_accel_max(profile: int, v_ego: float, stock_accel_max: float) -> float:
if not math.isfinite(stock_accel_max):
return math.nan
stock_positive_max = max(float(stock_accel_max), 0.0)
return stock_positive_max * profile_accel_scale(profile, v_ego)
@@ -1,107 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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
from typing import NamedTuple
import numpy as np
from openpilot.cereal import log
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import (
LongitudinalMpc, STOP_DISTANCE, T_IDXS, get_T_FOLLOW,
)
from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.constants import (
COMFORT_DECEL, MAX_LEAD_ACCEL_TAU, MIN_LEAD_SPEED, STOP_GAP_RESERVE, sanitize_profile,
)
class LeadPlan(NamedTuple):
speed_ceiling: float = math.inf
selected_lead: int = -1
selected_lead_track_id: int = -1
closing_speed: float = 0.0
required_decel: float = 0.0
v_ego_projected: float = 0.0
def _project_ego(v_ego: float, a_ego: float, delay: float) -> tuple[float, float]:
if a_ego < 0.0:
stop_time = -v_ego / a_ego if v_ego > 0.0 else 0.0
if stop_time <= delay:
distance = -v_ego**2 / (2.0 * a_ego) if v_ego > 0.0 else 0.0
return distance, 0.0
return max(v_ego * delay + 0.5 * a_ego * delay**2, 0.0), max(v_ego + a_ego * delay, 0.0)
def _lead_values(lead) -> tuple[float, float, float, float, int] | None:
if not lead.present:
return None
d_rel = float(lead.dRel)
v_lead = float(lead.vLeadK)
if not math.isfinite(d_rel) or d_rel < 0.0 or not math.isfinite(v_lead) or v_lead < MIN_LEAD_SPEED:
return None
a_lead = float(lead.aLeadK)
if not math.isfinite(a_lead):
a_lead = 0.0
a_lead_tau = float(lead.aLeadTau)
if not math.isfinite(a_lead_tau) or not 0.0 < a_lead_tau <= MAX_LEAD_ACCEL_TAU:
a_lead_tau = _LEAD_ACCEL_TAU
track_id = max(int(lead.radarTrackId), -1) if math.isfinite(lead.radarTrackId) else -1
return d_rel, max(v_lead, 0.0), float(np.clip(a_lead, -10.0, 5.0)), a_lead_tau, track_id
def calculate_lead_plan(radar_state, v_ego: float, a_ego: float, delay: float, profile: int,
follow_personality=log.LongitudinalPersonality.standard) -> LeadPlan:
if not all(math.isfinite(value) for value in (v_ego, a_ego, delay)) or v_ego < 0.0 or delay < 0.0:
return LeadPlan()
try:
t_follow = float(get_T_FOLLOW(follow_personality))
except (NotImplementedError, TypeError, ValueError):
return LeadPlan()
if not math.isfinite(t_follow) or t_follow < 0.0:
return LeadPlan()
profile = sanitize_profile(profile)
x_ego, v_ego_projected = _project_ego(v_ego, a_ego, delay)
comfort_decel = COMFORT_DECEL[profile]
candidates: list[LeadPlan] = []
for lead_index, lead in enumerate((radar_state.leadOne, radar_state.leadTwo)):
values = _lead_values(lead)
if values is None:
continue
d_rel, v_lead, a_lead, a_lead_tau, track_id = values
lead_xv = LongitudinalMpc.extrapolate_lead(d_rel, v_lead, a_lead, a_lead_tau)
x_lead = float(np.interp(delay, T_IDXS, lead_xv[:, 0]))
v_lead_projected = float(np.interp(delay, T_IDXS, lead_xv[:, 1]))
# Match the stock MPC gap convention, including ego-speed time headway.
safety_gap = max(x_lead - x_ego - STOP_DISTANCE - t_follow * v_ego_projected, 0.0)
closing_speed = max(v_ego_projected - v_lead_projected, 0.0)
required_decel = 0.0 if closing_speed == 0.0 else math.inf if safety_gap == 0.0 else closing_speed**2 / (2.0 * safety_gap)
usable_gap = max(safety_gap - STOP_GAP_RESERVE, 0.0)
speed_ceiling = v_lead_projected + math.sqrt(2.0 * comfort_decel * usable_gap)
finite_values = (x_lead, v_lead_projected, safety_gap, usable_gap, closing_speed, speed_ceiling)
if (not all(math.isfinite(value) and value >= 0.0 for value in finite_values) or math.isnan(required_decel)
or required_decel < 0.0):
continue
candidates.append(LeadPlan(
speed_ceiling=speed_ceiling,
selected_lead=lead_index,
selected_lead_track_id=track_id,
closing_speed=closing_speed,
required_decel=required_decel,
v_ego_projected=v_ego_projected,
))
return min(candidates, key=lambda candidate: candidate.speed_ceiling) if candidates else LeadPlan(v_ego_projected=v_ego_projected)
@@ -1,242 +0,0 @@
import math
from dataclasses import FrozenInstanceError
from types import SimpleNamespace
from openpilot.cereal import log
from openpilot.common.realtime import DT_MDL
from openpilot.common.test import OpenpilotTestCase
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
AccelController, AccelControllerState, AccelDecision,
)
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.constants import (
ACCEL_PROFILES, ACCEL_SCALE_BP, ACCEL_SCALE_V, EARLY_DECEL_RELEASE_RATE, EARLY_DECEL_TIGHTEN_RATE,
AccelProfile, profile_accel_max, profile_accel_scale, sanitize_profile,
)
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.lead import calculate_lead_plan
def lead(*, present=False, distance=0.0, speed=0.0, accel=0.0, tau=1.5, track_id=-1):
return SimpleNamespace(
present=present, dRel=distance, vLeadK=speed, aLeadK=accel,
aLeadTau=tau, radarTrackId=track_id,
)
def radar(lead_one=None, lead_two=None):
return SimpleNamespace(leadOne=lead_one or lead(), leadTwo=lead_two or lead())
def controller(*, enabled=True, profile=AccelProfile.normal, dt=DT_MDL):
instance = AccelController(SimpleNamespace(longitudinalActuatorDelay=0.10, openpilotLongitudinalControl=True), dt=dt)
instance.enabled = enabled
instance.profile = profile
return instance
def update(instance, radar_state=None, **overrides):
arguments = {
"v_ego": 10.0,
"a_ego": 0.0,
"v_cruise": 25.0,
"follow_personality": log.LongitudinalPersonality.standard,
"engaged": True,
"cruise_initialized": True,
"acc_selected": True,
"stock_accel_max": 1.0,
"radar_fresh": True,
"radar_healthy": True,
"force_decel": False,
}
arguments.update(overrides)
return instance.update(radar() if radar_state is None else radar_state, **arguments)
def restrictive_radar():
return radar(lead(present=True, distance=25.0, speed=5.0, accel=-0.2, track_id=101))
class TestProfiles(OpenpilotTestCase):
def test_profiles_are_faster_without_exceeding_stock(self):
self.assertEqual(ACCEL_SCALE_V[AccelProfile.eco], [0.82, 0.76, 0.63, 0.53, 0.42])
self.assertEqual(ACCEL_SCALE_V[AccelProfile.normal], [0.95, 0.90, 0.84, 0.76, 0.63])
self.assertEqual(ACCEL_SCALE_V[AccelProfile.sport], [1.0] * len(ACCEL_SCALE_BP))
def test_profile_order_and_stock_scaling(self):
for speed in (*ACCEL_SCALE_BP, 17.0, 50.0):
with self.subTest(speed=speed):
scales = [profile_accel_scale(profile, speed) for profile in ACCEL_PROFILES]
self.assertLess(scales[0], scales[1])
self.assertLess(scales[1], scales[2])
self.assertEqual(scales[2], 1.0)
for profile, scale in zip(ACCEL_PROFILES, scales, strict=True):
self.assertAlmostEqual(profile_accel_max(profile, speed, 0.73), 0.73 * scale)
def test_profiles_never_expand_stock_candidate(self):
for profile in ACCEL_PROFILES:
for stock_limit in (-0.5, 0.0, 0.4, 1.6):
with self.subTest(profile=profile, stock_limit=stock_limit):
limit = profile_accel_max(profile, 12.0, stock_limit)
self.assertGreaterEqual(limit, 0.0)
self.assertLessEqual(limit, max(stock_limit, 0.0))
def test_invalid_profile_is_normal_and_nonfinite_propagates(self):
self.assertEqual(sanitize_profile(999), AccelProfile.normal)
self.assertTrue(math.isnan(profile_accel_scale(AccelProfile.normal, math.nan)))
self.assertTrue(math.isnan(profile_accel_max(AccelProfile.normal, 10.0, math.inf)))
class TestAccelDecision(OpenpilotTestCase):
def test_decision_is_a_small_immutable_contract(self):
decision = AccelDecision(cruise_accel_max=0.4, early_decel=-0.2, active=True)
self.assertEqual((decision.cruise_accel_max, decision.early_decel, decision.active), (0.4, -0.2, True))
field = "active"
with self.assertRaises(FrozenInstanceError):
setattr(decision, field, False)
def test_context_gates_reset_without_actuating(self):
cases = (
{"enabled": False},
{"engaged": False},
{"cruise_initialized": False},
{"acc_selected": False},
{"force_decel": True},
{"v_ego": math.nan},
{"v_cruise": -1.0},
{"stock_accel_max": math.inf},
)
for case in cases:
with self.subTest(case=case):
arguments = dict(case)
enabled = arguments.pop("enabled", True)
instance = controller(enabled=enabled)
decision = update(instance, restrictive_radar(), **arguments)
self.assertEqual(decision, AccelDecision())
self.assertFalse(instance.is_active)
self.assertEqual(instance.state, AccelControllerState.inactive)
def test_allow_throttle_hysteresis_filters_route_chatter(self):
instance = controller()
outputs = []
for probability in (0.32, 0.41, 0.36, 0.42, 0.31, 0.44, 0.35):
stock_allowed = probability > 0.4
outputs.append(instance.update_allow_throttle(stock_allowed, probability))
self.assertEqual(outputs, [False] * len(outputs))
self.assertTrue(instance.update_allow_throttle(True, 0.46))
def test_allow_throttle_uses_stock_when_disabled_and_low_speed_override(self):
instance = controller(enabled=False)
self.assertFalse(instance.update_allow_throttle(False, 0.39))
self.assertTrue(instance.update_allow_throttle(True, 0.0, force_allow=True))
instance.enabled = True
self.assertFalse(instance.update_allow_throttle(False, 0.0))
self.assertTrue(instance.update_allow_throttle(True, 0.0, force_allow=True))
def test_allow_throttle_hysteresis_resets_with_controller(self):
instance = controller()
self.assertFalse(instance.update_allow_throttle(False, 0.39))
instance.reset()
self.assertTrue(instance.update_allow_throttle(True, 0.41))
def test_profile_limit_is_only_active_when_binding(self):
for profile in ACCEL_PROFILES:
with self.subTest(profile=profile):
instance = controller(profile=profile)
decision = update(instance, v_ego=10.0, stock_accel_max=1.0)
expected = profile_accel_max(profile, 10.0, 1.0)
self.assertAlmostEqual(decision.cruise_accel_max, expected)
self.assertEqual(decision.active, expected < 1.0)
class TestEarlyDecel(OpenpilotTestCase):
def test_early_decel_starts_from_the_previous_positive_plan(self):
instance = controller()
decision = update(instance, restrictive_radar(), previous_plan_accel=0.48)
self.assertIsNotNone(decision.early_decel)
self.assertAlmostEqual(decision.early_decel, 0.48 - EARLY_DECEL_TIGHTEN_RATE * DT_MDL)
def test_early_decel_is_nonpositive_and_tightens_at_bound(self):
instance = controller()
samples = [0.0]
for _ in range(10):
decision = update(instance, restrictive_radar())
samples.append(decision.early_decel or 0.0)
self.assertTrue(all(value <= 0.0 for value in samples))
self.assertTrue(any(value < 0.0 for value in samples))
for before, after in zip(samples[:-1], samples[1:], strict=True):
self.assertGreaterEqual(after - before, -EARLY_DECEL_TIGHTEN_RATE * DT_MDL - 1e-9)
def test_fresh_dropout_and_unhealthy_radar_release_at_bound(self):
releases = ((radar(), True, True), (restrictive_radar(), False, False))
for radar_state, radar_fresh, radar_healthy in releases:
with self.subTest(radar_fresh=radar_fresh, radar_healthy=radar_healthy):
instance = controller()
for _ in range(10):
update(instance, restrictive_radar())
previous = instance.early_decel
self.assertIsNotNone(previous)
for _ in range(30):
decision = update(instance, radar_state, radar_fresh=radar_fresh, radar_healthy=radar_healthy)
current = decision.early_decel or 0.0
self.assertLessEqual(current, 0.0)
self.assertGreaterEqual(current, previous - 1e-9)
self.assertLessEqual(current - previous, EARLY_DECEL_RELEASE_RATE * DT_MDL + 1e-9)
previous = current
if decision.early_decel is None:
break
self.assertIsNone(instance.early_decel)
def test_healthy_duplicate_radar_holds_early_decel(self):
instance = controller()
for _ in range(10):
update(instance, restrictive_radar())
previous = instance.early_decel
decision = update(instance, restrictive_radar(), radar_fresh=False, radar_healthy=True)
self.assertEqual(decision.early_decel, previous)
self.assertEqual(instance.state, AccelControllerState.hold)
def test_early_decel_is_bounded_by_profile_comfort(self):
for profile in ACCEL_PROFILES:
with self.subTest(profile=profile):
instance = controller(profile=profile)
for _ in range(30):
decision = update(instance, restrictive_radar())
self.assertIsNotNone(decision.early_decel)
self.assertLessEqual(decision.early_decel, 0.0)
self.assertGreaterEqual(decision.early_decel, -0.35)
class TestLeadPlan(OpenpilotTestCase):
def test_more_restrictive_of_two_leads_is_selected(self):
radar_state = radar(
lead(present=True, distance=80.0, speed=12.0, track_id=10),
lead(present=True, distance=25.0, speed=6.0, track_id=20),
)
plan = calculate_lead_plan(radar_state, 10.0, 0.0, 0.15, AccelProfile.normal)
self.assertEqual((plan.selected_lead, plan.selected_lead_track_id), (1, 20))
self.assertGreater(plan.closing_speed, 0.0)
self.assertGreater(plan.required_decel, 0.0)
def test_malformed_lead_is_ignored_without_hiding_valid_second_lead(self):
malformed = lead(present=True, distance=math.nan, speed=8.0)
valid = lead(present=True, distance=30.0, speed=7.0, accel=math.nan, tau=math.inf, track_id=math.nan)
plan = calculate_lead_plan(radar(malformed, valid), 10.0, 0.0, 0.15, AccelProfile.normal)
self.assertEqual(plan.selected_lead, 1)
self.assertEqual(plan.selected_lead_track_id, -1)
self.assertTrue(math.isfinite(plan.speed_ceiling))
def test_malformed_radar_and_scalar_inputs_fail_closed_to_no_extension(self):
for radar_state in (None, SimpleNamespace(), radar(lead(present=True, distance=-1.0, speed=5.0))):
with self.subTest(radar_state=radar_state):
instance = controller(profile=AccelProfile.sport)
decision = update(instance, radar_state)
self.assertIsNone(decision.early_decel)
self.assertFalse(decision.active)
@@ -1,252 +0,0 @@
from types import SimpleNamespace
from typing import Any
from openpilot.cereal import custom, log
from openpilot.common.realtime import DT_MDL
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalPlanSource as MpcSource
from openpilot.selfdrive.controls.lib.longitudinal_planner import get_coast_accel, get_cruise_accel, get_max_accel
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelController, AccelControllerState
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.constants import (
ACCEL_PROFILES, EARLY_DECEL_TIGHTEN_RATE, AccelProfile, profile_accel_scale,
)
from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP, LongitudinalPlanSource
def lead(*, present=False, distance=0.0, speed=0.0):
return SimpleNamespace(
present=present, dRel=distance, vLeadK=speed, aLeadK=0.0,
aLeadTau=1.5, radarTrackId=-1,
)
def radar(lead_one=None, lead_two=None):
return SimpleNamespace(leadOne=lead_one or lead(), leadTwo=lead_two or lead())
class PlannerSM(dict):
def __init__(self, *, experimental=False, force_decel=False, radar_state=None, radar_time=100):
super().__init__(
radarState=radar_state or radar(),
carState=SimpleNamespace(vEgo=10.0, aEgo=0.0, vCruise=72.0),
selfdriveState=SimpleNamespace(
enabled=True, experimentalMode=experimental, personality=log.LongitudinalPersonality.standard,
),
controlsState=SimpleNamespace(forceDecel=force_decel, longControlState=LongCtrlState.pid),
)
self.valid = {"radarState": True}
self.alive = {"radarState": True}
self.logMonoTime = {"radarState": radar_time}
def all_checks(self, service_list=None):
return True
def accel_controller(*, enabled=True, profile=AccelProfile.normal):
cp = SimpleNamespace(longitudinalActuatorDelay=0.1, openpilotLongitudinalControl=True)
instance = AccelController(cp)
instance.enabled = enabled
instance.profile = profile
return instance
def planner_for_hook(*, enabled=True, profile=AccelProfile.normal):
planner = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
dynamic_planner: Any = planner
dynamic_planner.accel_controller = accel_controller(enabled=enabled, profile=profile)
dynamic_planner.dec = SimpleNamespace(active=lambda: False)
dynamic_planner.output_v_target = 30.0
dynamic_planner.previous_plan_accel = 0.0
dynamic_planner.a_cruise = 0.0
dynamic_planner._radar_fresh_this_cycle = True
dynamic_planner._radar_healthy_this_cycle = True
return planner
class TestPlannerHook(OpenpilotTestCase):
def test_disabled_e2e_and_force_decel_preserve_exact_candidate_tuple(self):
candidates = (
(-0.4, MpcSource.lead0, True),
(0.6, MpcSource.cruise, False),
(0.2, MpcSource.e2e, False),
)
cases = (
(planner_for_hook(enabled=False), PlannerSM()),
(planner_for_hook(profile=AccelProfile.eco), PlannerSM(experimental=True)),
(planner_for_hook(profile=AccelProfile.eco), PlannerSM(force_decel=True)),
)
for planner, sm in cases:
with self.subTest(experimental=sm["selfdriveState"].experimentalMode,
force_decel=sm["controlsState"].forceDecel,
enabled=planner.accel_controller.enabled):
result = planner.update_accel_controller(sm, candidates)
self.assertIs(result, candidates)
self.assertEqual(result, candidates)
def test_missing_cruise_candidate_is_exact_noop(self):
planner = planner_for_hook(profile=AccelProfile.eco)
candidates = ((-0.4, MpcSource.lead0, True), (0.2, MpcSource.e2e, False))
self.assertIs(planner.update_accel_controller(PlannerSM(), candidates), candidates)
def test_inactive_acc_does_not_publish_a_stale_positive_cruise_candidate(self):
planner = planner_for_hook(profile=AccelProfile.eco)
sm = PlannerSM()
sm["controlsState"].longControlState = LongCtrlState.off
candidates = [(-0.4, MpcSource.lead0, True), (0.6, MpcSource.cruise, False)]
result = planner.update_accel_controller(sm, candidates)
self.assertEqual(result, [candidates[0], (0.0, MpcSource.cruise, False)])
self.assertEqual(planner.a_cruise, 0.0)
self.assertEqual(planner.accel_controller.state, AccelControllerState.inactive)
stale_positive = [(1.3, MpcSource.lead0, False), (0.9, MpcSource.cruise, False)]
self.assertEqual(min(candidate[0] for candidate in planner.update_accel_controller(sm, stale_positive)), 0.0)
braking = [(-0.4, MpcSource.lead0, True), (-0.2, MpcSource.cruise, True)]
self.assertIs(planner.update_accel_controller(sm, braking), braking)
disabled = planner_for_hook(enabled=False)
self.assertIs(disabled.update_accel_controller(sm, candidates), candidates)
blended = planner_for_hook(profile=AccelProfile.eco)
self.assertIs(blended.update_accel_controller(PlannerSM(experimental=True), candidates), candidates)
def test_profiles_scale_final_stock_turn_and_coast_candidates(self):
cp = SimpleNamespace(steerRatio=15.0, wheelbase=2.7)
scenarios = (
(25.0, 9.0, 0.35, 2.0, True),
(4.0, 0.0, 0.40, get_coast_accel(0.0), False),
)
for v_ego, steering_angle, previous, accel_coast, allow_throttle in scenarios:
stock = get_cruise_accel(
False, 30.0, v_ego, previous, steering_angle, cp, DT_MDL, accel_coast, allow_throttle,
)
self.assertGreater(stock, 0.0)
self.assertLess(stock, get_max_accel(v_ego))
for profile in ACCEL_PROFILES:
with self.subTest(v_ego=v_ego, profile=profile):
planner = planner_for_hook(profile=profile)
sm = PlannerSM()
sm["carState"].vEgo = v_ego
candidates = [(-0.5, MpcSource.lead0, True), (stock, MpcSource.cruise, False)]
result = planner.update_accel_controller(sm, candidates)
self.assertEqual(result[0], candidates[0])
self.assertEqual(result[1][1:], candidates[1][1:])
self.assertAlmostEqual(result[1][0], stock * profile_accel_scale(profile, v_ego))
def test_early_decel_is_an_additive_nonpositive_cruise_candidate(self):
planner = planner_for_hook(profile=AccelProfile.sport)
sm = PlannerSM(radar_state=radar(lead(present=True, distance=25.0, speed=5.0)))
candidates = [(-0.02, MpcSource.lead0, False), (0.6, MpcSource.cruise, False)]
result = planner.update_accel_controller(sm, candidates)
self.assertEqual(result[:2], candidates)
self.assertEqual(len(result), 3)
self.assertEqual(result[-1][1:], (MpcSource.cruise, False))
self.assertLessEqual(result[-1][0], 0.0)
def test_early_decel_enters_from_the_previous_positive_command(self):
planner = planner_for_hook(profile=AccelProfile.sport)
planner.previous_plan_accel = 0.48
sm = PlannerSM(radar_state=radar(lead(present=True, distance=25.0, speed=5.0)))
candidates = [(-0.02, MpcSource.lead0, False), (0.60, MpcSource.cruise, False)]
result = planner.update_accel_controller(sm, candidates)
self.assertEqual(result[:2], candidates)
self.assertAlmostEqual(result[-1][0], 0.48 - EARLY_DECEL_TIGHTEN_RATE * DT_MDL)
self.assertEqual(result[-1][1:], (MpcSource.cruise, False))
def test_radar_freshness_requires_a_healthy_advanced_message(self):
planner = planner_for_hook()
planner._radar_log_mono_time = None
sm = PlannerSM(radar_time=100)
self.assertTrue(planner._update_radar_freshness(sm))
self.assertFalse(planner._update_radar_freshness(sm))
sm.logMonoTime["radarState"] = 101
self.assertTrue(planner._update_radar_freshness(sm))
sm.valid["radarState"] = False
sm.logMonoTime["radarState"] = 102
self.assertFalse(planner._update_radar_freshness(sm))
self.assertFalse(planner._radar_healthy_this_cycle)
class TestParamsSchemaAndTelemetry(OpenpilotTestCase):
def test_params_enable_and_sanitize_profile(self):
instance = accel_controller(enabled=False)
instance.params.put_bool("AccelPersonalityEnabled", True, block=True)
instance.params.put("AccelPersonality", 99, block=True)
instance.update_params()
self.assertTrue(instance.is_enabled)
self.assertEqual(instance.profile, AccelProfile.sport)
self.assertEqual(instance.params.get("AccelPersonality"), AccelProfile.sport)
instance.params.put_bool("AccelPersonalityEnabled", False, block=True)
instance._param_frame = 0
instance.update_params()
self.assertFalse(instance.is_enabled)
def test_schema_contract_and_round_trip(self):
fields = custom.LongitudinalPlanSP.AccelController.schema.fields
self.assertEqual(
{name: field.proto.ordinal.explicit for name, field in fields.items()},
{"enabled": 0, "active": 1, "shadowOnlyDEPRECATED": 2, "profile": 3, "state": 4},
)
self.assertEqual(
custom.LongitudinalPlanSP.AccelController.Profile.schema.enumerants,
{"eco": 0, "normal": 1, "sport": 2},
)
message = custom.LongitudinalPlanSP.new_message()
message.accelController.enabled = True
message.accelController.active = True
message.accelController.profile = AccelProfile.sport
message.accelController.state = AccelControllerState.release
with custom.LongitudinalPlanSP.from_bytes(message.to_bytes()) as reader:
self.assertTrue(reader.accelController.enabled)
self.assertTrue(reader.accelController.active)
self.assertEqual(reader.accelController.profile, AccelProfile.sport)
self.assertEqual(reader.accelController.state, AccelControllerState.release)
def test_minimal_controller_telemetry_is_published(self):
planner = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
dynamic_planner: Any = planner
dynamic_planner.source = LongitudinalPlanSource.cruise
dynamic_planner.output_v_target = 20.0
dynamic_planner.output_a_target = -0.1
dynamic_planner.events_sp = SimpleNamespace(to_msg=list)
dynamic_planner.dec = SimpleNamespace(mode=lambda: "acc", enabled=lambda: False, active=lambda: False)
dynamic_planner.accel_controller = accel_controller(profile=AccelProfile.eco)
dynamic_planner.accel_controller.is_active = True
dynamic_planner.accel_controller.state = AccelControllerState.restrict
dynamic_planner.scc = SimpleNamespace(
vision=SimpleNamespace(
state=0, output_v_target=20.0, output_a_target=0.0, current_lat_acc=0.0,
max_pred_lat_acc=0.0, is_enabled=False, is_active=False,
),
map=SimpleNamespace(state=0, output_v_target=20.0, output_a_target=0.0, is_enabled=False, is_active=False),
)
dynamic_planner.resolver = SimpleNamespace(
speed_limit=0.0, speed_limit_last=0.0, speed_limit_final=0.0, speed_limit_final_last=0.0,
speed_limit_valid=False, speed_limit_last_valid=False, speed_limit_offset=0.0, distance=0.0,
source=custom.LongitudinalPlanSP.SpeedLimit.Source.none,
)
dynamic_planner.sla = SimpleNamespace(
state=custom.LongitudinalPlanSP.SpeedLimit.AssistState.disabled, is_enabled=False,
is_active=False, output_v_target=20.0, output_a_target=0.0,
)
dynamic_planner.e2e_alerts_helper = SimpleNamespace(green_light_alert=False, lead_depart_alert=False)
sent = {}
dynamic_planner.publish_longitudinal_plan_sp(
PlannerSM(), SimpleNamespace(send=lambda service, message: sent.update({service: message})),
)
telemetry = sent["longitudinalPlanSP"].longitudinalPlanSP.accelController
self.assertTrue(telemetry.enabled)
self.assertTrue(telemetry.active)
self.assertEqual(telemetry.profile, AccelProfile.eco)
self.assertEqual(telemetry.state, AccelControllerState.restrict)
self.assertEqual(set(custom.LongitudinalPlanSP.AccelController.schema.fields), {
"enabled", "active", "shadowOnlyDEPRECATED", "profile", "state",
})
@@ -1,6 +1,4 @@
class WMACConstants:
MODEL_ACCEL_TRANSITION_RATE = 3.0
# Lead detection parameters
LEAD_WINDOW_SIZE = 6 # Stable detection window
LEAD_PROB = 0.45 # Balanced threshold for lead detection
@@ -6,15 +6,13 @@ See the LICENSE.md file in the root directory for more details.
"""
# Version = 2025-6-30
import math
from typing import Literal
from openpilot.cereal import messaging
from opendbc.car import structs
from numpy import interp
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
from typing import Literal
# d-e2e, from modeldata.h
TRAJECTORY_SIZE = 33
@@ -132,51 +130,6 @@ class ModeTransitionManager:
return self.current_mode
class ModelAccelTransition:
"""Smooths acceleration while DEC changes modes."""
def __init__(self, dt: float = DT_MDL):
self._max_step = WMACConstants.MODEL_ACCEL_TRANSITION_RATE * dt
self._accel = 0.0
self._active = False
self._blended = False
def reset(self) -> None:
self._active = False
self._blended = False
@property
def active(self) -> bool:
return self._active
def update(self, mpc_accel: float, model_accel: float, previous_accel: float, *, blended: bool,
urgent: bool = False, reset: bool = False) -> float:
selected_accel = min(mpc_accel, model_accel) if blended else mpc_accel
if reset or not all(math.isfinite(accel) for accel in (mpc_accel, model_accel, previous_accel)):
self.reset()
return selected_accel
if blended != self._blended:
self._accel = previous_accel
self._active = True
self._blended = blended
if urgent and selected_accel <= self._accel:
self._accel = selected_accel
self._active = True
return selected_accel
if not self._active:
return selected_accel
transition_target = model_accel if blended else mpc_accel
preview_accel = max(self._accel - self._max_step, min(self._accel + self._max_step, transition_target))
output_accel = min(mpc_accel, preview_accel)
self._accel = output_accel
if mpc_accel >= transition_target and math.isclose(preview_accel, transition_target, abs_tol=1e-9):
self._active = False
return output_accel
class DynamicExperimentalController:
def __init__(self, CP: structs.CarParams, mpc, params=None):
self._CP = CP
@@ -1,112 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from typing import cast
from openpilot.cereal import custom, messaging
from opendbc.car import structs
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanner, LongitudinalPlanSource
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
V_EGO = 20.0
E2E_ACCEL = -3.0 # low enough that e2e wins the min() whenever it is a candidate
class MockDec:
def __init__(self, active: bool, mode: str):
self._active = active
self._mode = mode
def update(self, sm):
pass
def active(self) -> bool:
return self._active
def mode(self) -> str:
return self._mode
def enabled(self) -> bool:
return True
class MockSubMaster(dict):
def __init__(self, services: dict):
super().__init__(services)
self.valid = dict.fromkeys(services, True)
self.alive = dict.fromkeys(services, True)
self.logMonoTime = dict.fromkeys(services, 0)
self.updated = dict.fromkeys(services, True)
self.recv_frame = dict.fromkeys(services, 1)
def all_checks(self, service_list=None) -> bool:
return True
def build_sm(experimental_mode: bool) -> MockSubMaster:
services = {}
for service in ("radarState", "controlsState", "vehicleParameters", "carStateSP",
"liveMapDataSP", "gpsLocationExternal", "gpsLocation"):
services[service] = getattr(messaging.new_message(service), service)
car_state = messaging.new_message('carState')
car_state.carState.vEgo = V_EGO
car_state.carState.vCruise = 100.0
car_state.carState.vCruiseCluster = 100.0
services['carState'] = car_state.carState.as_reader()
selfdrive_state = messaging.new_message('selfdriveState')
selfdrive_state.selfdriveState.experimentalMode = experimental_mode
selfdrive_state.selfdriveState.enabled = True
services['selfdriveState'] = selfdrive_state.selfdriveState.as_reader()
car_control = messaging.new_message('carControl')
car_control.carControl.enabled = True
services['carControl'] = car_control.carControl.as_reader()
model = messaging.new_message('modelV2')
model.modelV2.orientationRate.z = [0.01] * 33 # nonzero: a straight path divides by zero in SCC vision
model.modelV2.velocity.x = [V_EGO] * 33
model.modelV2.position.x = [float(i) for i in range(33)]
model.modelV2.action.desiredAcceleration = E2E_ACCEL
services['modelV2'] = model.modelV2.as_reader()
return MockSubMaster(services)
def build_planner(dec_active: bool, dec_mode: str) -> LongitudinalPlanner:
CP = structs.CarParams()
CP.steerRatio = 15.0
CP.wheelbase = 2.7
CP.longitudinalActuatorDelay = 0.2
CP_SP = custom.CarParamsSP.new_message().as_reader()
planner = LongitudinalPlanner(CP, CP_SP, init_v=V_EGO)
planner.dec = cast(DynamicExperimentalController, MockDec(dec_active, dec_mode))
return planner
class TestDecPlannerGate(OpenpilotTestCase):
"""The e2e candidate must be gated on is_e2e(), not raw experimentalMode."""
def _source(self, experimental_mode: bool, dec_active: bool, dec_mode: str) -> LongitudinalPlanSource:
planner = build_planner(dec_active, dec_mode)
planner.update(build_sm(experimental_mode))
return planner.mpc.source
def test_no_e2e_when_experimental_mode_off(self):
assert self._source(False, False, 'acc') != LongitudinalPlanSource.e2e
def test_e2e_when_dec_inactive(self):
# DEC off: behavior must match upstream
assert self._source(True, False, 'acc') == LongitudinalPlanSource.e2e
def test_e2e_when_dec_blended(self):
assert self._source(True, True, 'blended') == LongitudinalPlanSource.e2e
def test_no_e2e_when_dec_holds_acc(self):
# the regression
assert self._source(True, True, 'acc') != LongitudinalPlanSource.e2e
@@ -1,7 +1,5 @@
from openpilot.common.realtime import DT_MDL
from openpilot.common.test import OpenpilotTestCase
from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController, ModelAccelTransition
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
class MockLeadOne:
def __init__(self, present=0.0):
@@ -91,56 +89,3 @@ class TestDynamicExperimentalController(OpenpilotTestCase):
controller.update(default_sm)
assert controller.mode() == "blended"
class TestModelAccelTransition(OpenpilotTestCase):
def test_blended_entry_is_rate_bounded(self):
transition = ModelAccelTransition()
previous = 0.30
outputs = []
for _ in range(10):
previous = transition.update(0.50, -0.88, previous, blended=True)
outputs.append(previous)
max_step = WMACConstants.MODEL_ACCEL_TRANSITION_RATE * DT_MDL
self.assertAlmostEqual(outputs[0], 0.15)
assert min(b - a for a, b in zip([0.30, *outputs[:-1]], outputs, strict=True)) >= -max_step - 1e-9
self.assertAlmostEqual(outputs[-1], -0.88)
def test_harder_mpc_braking_is_immediate(self):
transition = ModelAccelTransition()
self.assertAlmostEqual(transition.update(-2.0, -0.88, 0.30, blended=True), -2.0)
def test_urgent_model_braking_is_immediate(self):
transition = ModelAccelTransition()
self.assertAlmostEqual(transition.update(0.0, -2.0, 0.30, blended=True, urgent=True), -2.0)
self.assertAlmostEqual(transition.update(0.0, 0.0, -2.0, blended=True), -1.85)
def test_harder_mpc_release_is_rate_bounded(self):
transition = ModelAccelTransition()
self.assertAlmostEqual(transition.update(-2.0, -0.5, 0.30, blended=True), -2.0)
self.assertAlmostEqual(transition.update(0.0, -0.5, -2.0, blended=True), -1.85)
def test_entry_and_exit_are_rate_bounded(self):
transition = ModelAccelTransition()
output = 0.30
for _ in range(20):
output = transition.update(0.0, -0.88, output, blended=True)
if output <= -0.88:
break
else:
self.fail("transition did not converge")
output = transition.update(0.0, -1.50, output, blended=True)
self.assertAlmostEqual(output, -1.50)
self.assertAlmostEqual(transition.update(0.0, -0.20, output, blended=False), -1.35)
def test_harder_mpc_braking_bypasses_exit_ramp(self):
transition = ModelAccelTransition()
self.assertAlmostEqual(transition.update(2.0, 0.76, 0.76, blended=True), 0.76)
self.assertAlmostEqual(transition.update(-2.0, 0.76, 0.76, blended=False), -2.0)
def test_urgent_release_remains_rate_bounded(self):
transition = ModelAccelTransition()
self.assertAlmostEqual(transition.update(-1.0, -1.0, -1.0, blended=True), -1.0)
self.assertAlmostEqual(transition.update(1.0, -1.0, -1.0, blended=False, urgent=True), -0.85)
@@ -1,53 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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
from typing import cast
STOPPING_DISTANCE = 0.75
STOPPING_TIME = 2.5
STOPPING_ACCEL_TOLERANCE = 0.1
STOPPING_SPEED_TOLERANCE = 0.05
STOPPING_SETTLE_FRAMES = 30
class LongControlSP:
def __init__(self):
self._stopping_settle_frames: int | None = None
def update_state(self, stopping: bool) -> None:
if not stopping:
self._stopping_settle_frames = None
def stopping_decel_rate(self, CS, a_target: float) -> float:
if not all(math.isfinite(value) for value in (self.last_output_accel, a_target, CS.vEgo, CS.aEgo)):
return 1.0
can_hold = self.last_output_accel <= 0.0 and a_target >= self.last_output_accel
terminal_speed = (0.0 <= CS.vEgo <= STOPPING_SPEED_TOLERANCE
or CS.standstill and abs(CS.vEgo) <= STOPPING_SPEED_TOLERANCE)
if self.last_output_accel > 0.0 or CS.vEgo < 0.0 and not terminal_speed:
return 1.0
if terminal_speed and self._stopping_settle_frames is None:
if not can_hold or self.last_output_accel > -STOPPING_ACCEL_TOLERANCE or CS.aEgo >= -STOPPING_ACCEL_TOLERANCE:
return 1.0
self._stopping_settle_frames = 0
time_decel = 0.0 if self._stopping_settle_frames is not None else CS.vEgo / STOPPING_TIME
required_decel = max(time_decel, CS.vEgo ** 2 / (2.0 * STOPPING_DISTANCE), 1e-3)
adequacy = min(max(-CS.aEgo / required_decel, 0.0), 1.0)
if not terminal_speed and self._stopping_settle_frames is None and can_hold and adequacy >= 1.0:
self._stopping_settle_frames = 0
motion_need = 1.0 - adequacy ** 2
planner_need = min(max((self.last_output_accel - a_target) / max(required_decel, STOPPING_ACCEL_TOLERANCE), 0.0), 1.0)
terminal_need = 0.0
if terminal_speed or self._stopping_settle_frames not in (None, 0):
settle_frames = cast(int, self._stopping_settle_frames)
self._stopping_settle_frames = min(settle_frames + 1, STOPPING_SETTLE_FRAMES)
terminal_need = (self._stopping_settle_frames / STOPPING_SETTLE_FRAMES) ** 2
return max(motion_need, planner_need, terminal_need)
@@ -8,11 +8,8 @@ See the LICENSE.md file in the root directory for more details.
from openpilot.cereal import messaging, custom
from opendbc.car import structs
from openpilot.common.constants import CV
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX, V_CRUISE_UNSET
from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalPlanSource as MpcSource
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelController
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController, ModelAccelTransition
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
from openpilot.sunnypilot.selfdrive.controls.lib.e2e_alerts_helper import E2EAlertsHelper
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.smart_cruise_control import SmartCruiseControl
from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_assist import SpeedLimitAssist
@@ -26,23 +23,18 @@ LongitudinalPlanSource = custom.LongitudinalPlanSP.LongitudinalPlanSource
class LongitudinalPlannerSP:
def __init__(self, CP: structs.CarParams, CP_SP: structs.CarParamsSP, mpc):
self.accel_controller = AccelController(CP, dt=mpc.dt)
self.events_sp = EventsSP()
self.resolver = SpeedLimitResolver()
self.dec = DynamicExperimentalController(CP, mpc)
self.model_accel_transition = ModelAccelTransition(mpc.dt)
self.scc = SmartCruiseControl()
self.resolver = SpeedLimitResolver()
self.sla = SpeedLimitAssist(CP, CP_SP)
self.generation = int(model_bundle.generation) if (model_bundle := get_active_bundle()) else None
self.source = LongitudinalPlanSource.cruise
self.e2e_alerts_helper = E2EAlertsHelper()
self._radar_log_mono_time = None
self._radar_fresh_this_cycle = True
self._radar_healthy_this_cycle = True
self.output_v_target = 0.
self.output_a_target = 0.
self.previous_plan_accel = 0.
def is_e2e(self, sm: messaging.SubMaster) -> bool:
experimental_mode = sm['selfdriveState'].experimentalMode
@@ -51,59 +43,6 @@ class LongitudinalPlannerSP:
return experimental_mode and self.dec.mode() == "blended"
def select_model_accel(self, mpc_accel: float, model_accel: float, *, blended: bool,
should_stop: bool, fcw: bool, reset: bool) -> float:
return self.model_accel_transition.update(
mpc_accel, model_accel, self.previous_plan_accel, blended=blended, urgent=should_stop or fcw, reset=reset or not self.dec.active(),
)
def update_accel_controller(self, sm: messaging.SubMaster, candidates):
cruise_index = next((i for i, candidate in enumerate(candidates) if candidate[1] == MpcSource.cruise), -1)
if cruise_index < 0:
return candidates
CS = sm['carState']
long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
reset_state = ((long_control_off if self.accel_controller.available else not sm['selfdriveState'].enabled)
or CS.vCruise == V_CRUISE_UNSET)
cruise_accel = candidates[cruise_index][0]
acc_selected = not self.is_e2e(sm)
decision = self.accel_controller.update(
sm['radarState'], v_ego=CS.vEgo, a_ego=CS.aEgo, v_cruise=self.output_v_target,
follow_personality=sm['selfdriveState'].personality, engaged=not reset_state,
cruise_initialized=CS.vCruise != V_CRUISE_UNSET, acc_selected=acc_selected,
stock_accel_max=max(cruise_accel, 0.0), radar_fresh=self._radar_fresh_this_cycle,
radar_healthy=self._radar_healthy_this_cycle,
force_decel=sm['controlsState'].forceDecel, previous_plan_accel=self.previous_plan_accel,
)
if self.accel_controller.is_enabled and acc_selected and reset_state:
# Do not carry an unactuated cruise ramp into engagement.
self.a_cruise = 0.0
if cruise_accel > 0.0:
candidates = list(candidates)
_, source, stop = candidates[cruise_index]
candidates[cruise_index] = (0.0, source, stop)
return candidates
if decision.cruise_accel_max is None and decision.early_decel is None:
return candidates
candidates = list(candidates)
if decision.cruise_accel_max is not None:
_, source, stop = candidates[cruise_index]
candidates[cruise_index] = (min(cruise_accel, decision.cruise_accel_max), source, stop)
if decision.early_decel is not None:
candidates.append((decision.early_decel, MpcSource.cruise, False))
return candidates
def _update_radar_freshness(self, sm: messaging.SubMaster) -> bool:
radar_log_mono_time = sm.logMonoTime['radarState']
radar_healthy = sm.valid['radarState'] and sm.alive['radarState']
self._radar_healthy_this_cycle = radar_healthy
radar_advanced = self._radar_log_mono_time is None or radar_log_mono_time > self._radar_log_mono_time
if radar_advanced:
self._radar_log_mono_time = radar_log_mono_time
return radar_healthy and radar_advanced
def update_targets(self, sm: messaging.SubMaster, v_ego: float, a_ego: float, v_cruise: float) -> tuple[float, float]:
CS = sm['carState']
v_cruise_cluster_kph = min(CS.vCruiseCluster, V_CRUISE_MAX)
@@ -135,8 +74,6 @@ class LongitudinalPlannerSP:
return self.output_v_target, self.output_a_target
def update(self, sm: messaging.SubMaster) -> None:
self._radar_fresh_this_cycle = self._update_radar_freshness(sm)
self.accel_controller.update_params()
self.events_sp.clear()
self.dec.update(sm)
self.e2e_alerts_helper.update(sm, self.events_sp)
@@ -158,12 +95,6 @@ class LongitudinalPlannerSP:
dec.enabled = self.dec.enabled()
dec.active = self.dec.active()
accel_controller = longitudinalPlanSP.accelController
accel_controller.enabled = self.accel_controller.is_enabled
accel_controller.active = self.accel_controller.is_active
accel_controller.profile = self.accel_controller.profile
accel_controller.state = self.accel_controller.state
# Smart Cruise Control
smartCruiseControl = longitudinalPlanSP.smartCruiseControl
# Vision Control
@@ -4,8 +4,6 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from types import SimpleNamespace
from typing import Any
import numpy as np
@@ -17,23 +15,8 @@ from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP, LongitudinalPlanSource
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control import MIN_V
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import (
_A_LAT_REG_MAX,
_BELOW_EGO_TARGET_RELEASE_RATE,
_ENTERING_PRED_LAT_ACC_TH,
_MIN_ACTIVATION_SPEED,
_RELIEF_CONFIRMATION_FRAMES,
_TARGET_RELEASE_CONFIRMATION_FRAMES,
_TARGET_RELEASE_RATE,
_TARGET_TIGHTEN_CONFIRMATION_FRAMES,
_TARGET_TIGHTEN_RATE,
_TURNING_LAT_ACC_TH,
_URGENT_PRED_LAT_ACC_TH,
SmartCruiseControlVision,
)
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import SmartCruiseControlVision, _ENTERING_PRED_LAT_ACC_TH
from openpilot.common.test import OpenpilotTestCase
VisionState = custom.LongitudinalPlanSP.SmartCruiseControl.VisionState
@@ -124,6 +107,7 @@ def generate_controlsState():
class TestSmartCruiseControlVision(OpenpilotTestCase):
def setup_method(self):
self.params = Params()
self.reset_params()
@@ -137,377 +121,36 @@ class TestSmartCruiseControlVision(OpenpilotTestCase):
def reset_params(self):
self.params.put_bool("SmartCruiseControlVision", True, block=True)
def assert_approx(self, actual, expected):
self.assertAlmostEqual(actual, expected, delta=max(1e-12, abs(expected) * 1e-6))
def set_lat_accels(self, current: float, predicted: float, v_ego: float = 20.0, model_speed: float = 20.0) -> None:
self.sm['controlsState'].curvature = current / v_ego**2
self.sm['modelV2'].velocity.x = [model_speed] * len(ModelConstants.T_IDXS)
self.sm['modelV2'].orientationRate.z = [predicted / model_speed] * len(ModelConstants.T_IDXS)
def update_lat_accels(
self, current: float, predicted: float, cruise: float = 30.0, a_ego: float = 0.0, v_ego: float = 20.0, model_speed: float = 20.0
) -> None:
self.set_lat_accels(current, predicted, v_ego, model_speed)
self.scc_v.update(self.sm, True, False, v_ego, a_ego, cruise)
def enter_curve(self, predicted: float = 2.2) -> None:
self.update_lat_accels(0.5, predicted)
self.update_lat_accels(0.5, predicted)
assert self.scc_v.state == VisionState.entering
def test_initial_state(self):
assert self.scc_v.state == VisionState.disabled
assert not self.scc_v.is_active
assert self.scc_v.output_v_target == V_CRUISE_UNSET
assert self.scc_v.output_a_target == 0.0
assert self.scc_v.output_a_target == 0.
def test_system_disabled(self):
self.params.put_bool("SmartCruiseControlVision", False, block=True)
self.scc_v.enabled = self.params.get_bool("SmartCruiseControlVision")
for _ in range(int(10.0 / DT_MDL)):
self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
for _ in range(int(10. / DT_MDL)):
self.scc_v.update(self.sm, True, False, 0., 0., 0.)
assert self.scc_v.state == VisionState.disabled
assert not self.scc_v.is_active
def test_disabled(self):
for _ in range(int(10.0 / DT_MDL)):
self.scc_v.update(self.sm, False, False, 0.0, 0.0, 0.0)
for _ in range(int(10. / DT_MDL)):
self.scc_v.update(self.sm, False, False, 0., 0., 0.)
assert self.scc_v.state == VisionState.disabled
def test_transition_disabled_to_enabled(self):
for _ in range(int(10.0 / DT_MDL)):
self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
for _ in range(int(10. / DT_MDL)):
self.scc_v.update(self.sm, True, False, 0., 0., 0.)
assert self.scc_v.state == VisionState.enabled
def test_unconfirmed_release_holds_but_urgent_reentry_tightens(self):
self.enter_curve()
targets = [self.scc_v.output_v_target]
self.update_lat_accels(2.0, 2.2, a_ego=-0.8)
assert self.scc_v.state == VisionState.turning
assert self.scc_v.output_a_target == -0.8
turning_demand = self.scc_v._v_demand()
targets.append(self.scc_v.output_v_target)
self.update_lat_accels(1.2, 1.2, a_ego=0.3)
assert self.scc_v.state == VisionState.leaving
assert self.scc_v.output_a_target == 0.3
targets.append(self.scc_v.output_v_target)
self.update_lat_accels(1.0, 3.0, a_ego=-1.2)
assert self.scc_v.state == VisionState.entering
assert self.scc_v.output_a_target == -1.2
reentry_demand = self.scc_v._v_demand()
targets.append(self.scc_v.output_v_target)
entering, turning, leaving, reentering = targets
assert turning < entering
self.assert_approx(turning, turning_demand)
self.assert_approx(leaving, turning)
assert reentering < leaving
self.assert_approx(reentering, reentry_demand)
def test_new_curve_interrupts_confirmed_release_immediately(self):
self.enter_curve()
for _ in range(_RELIEF_CONFIRMATION_FRAMES + 1):
self.update_lat_accels(0.8, 0.8)
releasing_v_target = self.scc_v.output_v_target
assert self.scc_v.state == VisionState.leaving
self.update_lat_accels(0.8, 3.0, a_ego=-0.7)
assert self.scc_v.state == VisionState.entering
assert self.scc_v.output_v_target < releasing_v_target
assert self.scc_v.output_a_target == -0.7
@parameterized.expand([(-2.0,), (-0.5,), (0.0,), (0.8,)])
def test_planner_acceleration_passes_through_exactly(self, planner_accel):
self.enter_curve()
self.update_lat_accels(0.5, 2.2, a_ego=planner_accel)
assert self.scc_v.output_a_target == planner_accel
def test_planner_acceleration_passes_through_all_states(self):
cases = (
(False, False, 0.5, 2.2, -0.2, VisionState.disabled),
(True, False, 0.5, 0.8, 0.1, VisionState.enabled),
(True, False, 0.5, 2.2, -0.4, VisionState.entering),
(True, False, 2.0, 2.2, -0.8, VisionState.turning),
(True, False, 1.2, 1.2, 0.3, VisionState.leaving),
(True, True, 1.2, 1.2, 0.6, VisionState.overriding),
)
for long_enabled, override, current, predicted, planner_accel, state in cases:
self.set_lat_accels(current, predicted)
self.scc_v.update(self.sm, long_enabled, override, 20.0, planner_accel, 30.0)
assert self.scc_v.state == state
assert self.scc_v.output_a_target == planner_accel
def test_jitter_requires_confirmed_relief_then_releases_smoothly(self):
self.enter_curve()
previous_v_target = self.scc_v.output_v_target
for frame in range(_RELIEF_CONFIRMATION_FRAMES * 2):
self.update_lat_accels(1.0, 1.05 if frame % 2 == 0 else 1.15)
assert self.scc_v.state == VisionState.entering
assert self.scc_v.output_v_target >= previous_v_target
assert self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
previous_v_target = self.scc_v.output_v_target
for _ in range(_RELIEF_CONFIRMATION_FRAMES):
self.update_lat_accels(1.15, 0.8)
assert self.scc_v.state == VisionState.entering
assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
previous_v_target = self.scc_v.output_v_target
release_cruise = 30.0
for _ in range(_RELIEF_CONFIRMATION_FRAMES - 1):
self.update_lat_accels(0.8, 0.8, release_cruise)
assert self.scc_v.state == VisionState.entering
assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
previous_v_target = self.scc_v.output_v_target
active_v_targets = [previous_v_target]
for _ in range(int((release_cruise - previous_v_target) / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
self.update_lat_accels(0.8, 0.8, release_cruise)
if not self.scc_v.is_active:
break
assert self.scc_v.state == VisionState.leaving
assert self.scc_v.output_v_target != V_CRUISE_UNSET
active_v_targets.append(self.scc_v.output_v_target)
assert self.scc_v.state == VisionState.enabled
assert self.scc_v.output_v_target == V_CRUISE_UNSET
self.assert_approx(active_v_targets[-1], release_cruise)
assert np.all((np.diff(active_v_targets) >= 0.0) & (np.diff(active_v_targets) <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9))
def test_target_release_waits_for_relief_above_ego_speed(self):
self.enter_curve()
held_v_target = self.scc_v.output_v_target
self.assert_approx(held_v_target, self.scc_v.v_ego)
for _ in range(_RELIEF_CONFIRMATION_FRAMES + _TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
self.update_lat_accels(0.8, 0.8)
self.assert_approx(self.scc_v.output_v_target, held_v_target)
self.update_lat_accels(0.8, 0.8)
rise = self.scc_v.output_v_target - held_v_target
assert 0.0 < rise <= _TARGET_RELEASE_RATE * DT_MDL + 1e-9
def test_curve_target_is_independent_of_ego_speed(self):
model_speed = 24.0
predicted_yaw_rate = 0.12
predicted_lat_accel = model_speed * predicted_yaw_rate
expected_v_target = (_A_LAT_REG_MAX / (predicted_yaw_rate / model_speed)) ** 0.5
targets = []
for v_ego in (18.0, 28.0):
controller = SmartCruiseControlVision()
self.set_lat_accels(0.5, predicted_lat_accel, v_ego, model_speed)
controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
assert controller.state == VisionState.entering
targets.append(controller.v_target)
self.assert_approx(targets[0], expected_v_target)
self.assert_approx(targets[1], expected_v_target)
def test_curve_target_respects_minimum_speed_floor(self):
model_speed = 10.0
predicted_yaw_rate = 2.0
self.set_lat_accels(0.5, model_speed * predicted_yaw_rate, model_speed=model_speed)
self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
assert self.scc_v.state == VisionState.entering
assert self.scc_v.v_target < MIN_V
self.assert_approx(self.scc_v.output_v_target, MIN_V)
@parameterized.expand(
[([], []), ([np.nan] * len(ModelConstants.T_IDXS), [np.nan] * len(ModelConstants.T_IDXS)), ([20.0] * 5, [0.1] * 3)],
names=["velocities", "yaw_rates"],
)
def test_model_vector_edges_remain_finite(self, velocities, yaw_rates):
self.sm['modelV2'].velocity.x = velocities
self.sm['modelV2'].orientationRate.z = yaw_rates
self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
assert all(
np.isfinite(value)
for value in (
self.scc_v.current_lat_acc,
self.scc_v.max_pred_lat_acc,
self.scc_v.v_target,
self.scc_v.output_v_target,
self.scc_v.output_a_target,
)
)
@parameterized.expand([(5.75,), (9.9,), (_MIN_ACTIVATION_SPEED,)])
def test_vision_control_does_not_steal_launch(self, launch_speed):
self.set_lat_accels(0.5, 3.0, launch_speed)
self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
assert launch_speed <= _MIN_ACTIVATION_SPEED
assert self.scc_v.state == VisionState.enabled
assert not self.scc_v.is_active
assert self.scc_v.output_v_target == V_CRUISE_UNSET
def test_vision_control_can_activate_above_launch_range(self):
speed = _MIN_ACTIVATION_SPEED + 0.01
self.set_lat_accels(0.5, 3.0, speed)
self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
assert self.scc_v.state == VisionState.entering
assert self.scc_v.is_active
def test_nonurgent_activation_has_no_target_cliff(self):
v_ego = _MIN_ACTIVATION_SPEED + 0.01
model_speed = 8.0
self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
self.assert_approx(self.scc_v.v_target, 8.0)
self.assert_approx(self.scc_v.output_v_target, v_ego)
def test_nonurgent_tightening_is_confirmed_and_rate_limited(self):
self.enter_curve()
initial_v_target = self.scc_v.output_v_target
for _ in range(_TARGET_TIGHTEN_CONFIRMATION_FRAMES - 1):
self.update_lat_accels(0.5, 2.8)
self.assert_approx(self.scc_v.output_v_target, initial_v_target)
self.update_lat_accels(0.5, 2.8)
drop = initial_v_target - self.scc_v.output_v_target
assert 0.0 < drop <= _TARGET_TIGHTEN_RATE * DT_MDL + 1e-9
def test_one_frame_curve_prediction_does_not_pulse_target(self):
self.enter_curve()
for _ in range(10):
self.update_lat_accels(0.5, 2.2)
stable_v_target = self.scc_v.output_v_target
self.update_lat_accels(0.5, 2.8)
self.assert_approx(self.scc_v.output_v_target, stable_v_target)
self.update_lat_accels(0.5, 2.2)
self.assert_approx(self.scc_v.output_v_target, stable_v_target)
def test_one_frame_release_does_not_reverse_target(self):
self.enter_curve(_URGENT_PRED_LAT_ACC_TH)
stable_v_target = self.scc_v.output_v_target
self.update_lat_accels(0.5, 2.2)
self.assert_approx(self.scc_v.output_v_target, stable_v_target)
self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
self.assert_approx(self.scc_v.output_v_target, stable_v_target)
def test_urgent_predicted_curve_is_not_delayed(self):
self.enter_curve()
self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
def test_current_curve_is_not_delayed(self):
self.enter_curve()
self.update_lat_accels(_TURNING_LAT_ACC_TH, 2.8)
self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
def test_sequential_curve_confirms_release_and_tightens_urgently(self):
self.enter_curve(3.0)
for _ in range(20):
self.update_lat_accels(0.5, 3.0)
restrictive_v_target = self.scc_v.output_v_target
self.update_lat_accels(0.5, 1.4, a_ego=0.4)
assert self.scc_v.state == VisionState.entering
self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
assert self.scc_v.output_a_target == 0.4
for _ in range(_TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
self.update_lat_accels(0.5, 1.4)
self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
self.update_lat_accels(0.5, 1.4)
released_v_target = self.scc_v.output_v_target
assert 0.0 < released_v_target - restrictive_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
self.update_lat_accels(0.5, 3.0, a_ego=-0.6)
assert self.scc_v.state == VisionState.entering
self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
assert self.scc_v.output_a_target == -0.6
for _ in range(4):
self.update_lat_accels(0.5, 1.4)
self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
self.update_lat_accels(0.5, 3.0)
self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
def test_acceleration_is_continuous_through_planner_arbitration(self):
car_control = messaging.new_message('carControl')
car_control.carControl.enabled = True
car_control.carControl.cruiseControl.override = False
self.sm['carControl'] = car_control.carControl
self.sm['carState'].vCruiseCluster = 108.0
planner: Any = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
planner.scc = SimpleNamespace(
vision=self.scc_v,
map=SimpleNamespace(output_v_target=V_CRUISE_UNSET, output_a_target=0.0),
update=lambda sm, enabled, override, v_ego, a_ego, v_cruise: self.scc_v.update(sm, enabled, override, v_ego, a_ego, v_cruise),
)
planner.resolver = SimpleNamespace(
speed_limit_valid=False,
speed_limit_last_valid=False,
speed_limit=0.0,
speed_limit_final_last=0.0,
distance=0.0,
update=lambda _v_ego, _sm: None,
)
planner.sla = SimpleNamespace(
output_v_target=V_CRUISE_UNSET,
output_a_target=0.0,
update=lambda *_args: None,
)
planner.events_sp = SimpleNamespace()
self.set_lat_accels(0.5, 2.2)
planner.update_targets(self.sm, 20.0, -0.8, 30.0)
planner.update_targets(self.sm, 20.0, -0.8, 30.0)
assert planner.source == LongitudinalPlanSource.sccVision
assert planner.output_a_target == -0.8
for planner_accel in (-2.0, 0.5, -0.2):
planner.update_targets(self.sm, 20.0, planner_accel, 30.0)
assert planner.source == LongitudinalPlanSource.sccVision
assert planner.output_a_target == planner_accel
self.set_lat_accels(0.8, 0.8)
for _ in range(int(30.0 / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
planner.update_targets(self.sm, 20.0, 0.4, 30.0)
assert planner.output_a_target == 0.4
if planner.source == LongitudinalPlanSource.cruise:
break
else:
self.fail("SCC Vision did not release to cruise")
planner.update_targets(self.sm, 20.0, 0.4, 30.0)
assert self.scc_v.state == VisionState.enabled
assert planner.source == LongitudinalPlanSource.cruise
@parameterized.expand(
[
@parameterized.expand([
("p97_just_above_threshold", True),
("single_spike_filtered", False),
("persistent_high_values", True),
],
names=["case", "should_enter"],
)
], names=["case", "should_enter"])
def test_max_pred_lat_acc_uses_p97_and_threshold(self, case, should_enter):
n = len(ModelConstants.T_IDXS)
th = float(_ENTERING_PRED_LAT_ACC_TH)
@@ -1,110 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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 gc
from contextlib import ExitStack
from unittest import mock
import numpy as np
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanSource
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import _A_LAT_REG_MAX
def _run_constant_curve(*, scc_enabled: bool, cruise: float, duration: float = 70.0) -> dict[str, np.ndarray]:
gc.collect()
curvature = 0.005
plant = Plant(lead_relevancy=False, speed=30.0)
planner = plant.planner
planner.dec._enabled = False
planner.scc.map.enabled = False
planner.scc.vision.enabled = scc_enabled
solver_failures = 0
with ExitStack() as patches:
patches.enter_context(mock.patch.object(planner.dec, "_read_params", return_value=None))
patches.enter_context(mock.patch.object(planner.scc.map, "update_params", return_value=None))
patches.enter_context(mock.patch.object(planner.scc.vision, "_update_params", return_value=None))
original_mpc_reset = planner.mpc.reset
def record_mpc_reset(*args, **kwargs):
nonlocal solver_failures
solver_failures += int(planner.mpc.solution_status != 0)
return original_mpc_reset(*args, **kwargs)
patches.enter_context(mock.patch.object(planner.mpc, "reset", side_effect=record_mpc_reset))
if scc_enabled:
original_update_calculations = planner.scc.vision._update_calculations
def inject_constant_curvature(sm):
velocities = np.asarray(sm['modelV2'].velocity.x, dtype=float)
sm['modelV2'].orientationRate.z = (curvature * velocities).tolist()
sm['controlsState'].curvature = curvature
original_update_calculations(sm)
patches.enter_context(mock.patch.object(planner.scc.vision, "_update_calculations", side_effect=inject_constant_curvature))
original_update = planner.update
def enable_longitudinal(sm):
sm['carControl'].enabled = True
sm['carControl'].longActive = True
original_update(sm)
patches.enter_context(mock.patch.object(planner, "update", side_effect=enable_longitudinal))
rows = []
while plant.current_time < duration:
output = plant.step(v_cruise=cruise)
rows.append(
(
plant.current_time,
output['speed'],
output['should_stop'],
planner.scc.vision.is_active,
planner.source == LongitudinalPlanSource.sccVision,
planner.scc.vision.output_v_target,
)
)
data = np.asarray(rows, dtype=float)
gc.collect()
return {
'time': data[:, 0],
'speed': data[:, 1],
'should_stop': data[:, 2],
'active': data[:, 3],
'scc_source': data[:, 4],
'target': data[:, 5],
'solver_failures': np.asarray(solver_failures),
}
class TestVisionControllerClosedLoop(OpenpilotTestCase):
def test_constant_curve_recovers_like_stock_speed_cap(self):
target = (_A_LAT_REG_MAX / 0.005) ** 0.5
scc = _run_constant_curve(scc_enabled=True, cruise=30.0)
stock = _run_constant_curve(scc_enabled=False, cruise=target)
scc_final = scc['speed'][scc['time'] >= 60.0]
stock_final = stock['speed'][stock['time'] >= 60.0]
# The generated solver can report platform-specific failures for the
# synthetic no-lead plant. The feature must not make that stock baseline
# worse; requiring an absolute zero would hide a harness difference as a
# controller regression.
assert scc['solver_failures'] <= stock['solver_failures']
assert not scc['should_stop'].any()
assert np.all(scc['active'][scc['time'] >= 60.0])
assert np.all(scc['scc_source'][scc['time'] >= 60.0])
assert np.allclose(scc['target'][scc['time'] >= 60.0], target)
assert scc_final.min() >= target - 1.0
assert abs(scc_final.mean() - stock_final.mean()) < 0.5
assert abs(scc_final.min() - stock_final.min()) < 1.0
assert abs(scc_final.max() - stock_final.max()) < 1.0
@@ -23,21 +23,25 @@ _ENTERING_PRED_LAT_ACC_TH = 1.3 # Predicted Lat Acc threshold to trigger enteri
_ABORT_ENTERING_PRED_LAT_ACC_TH = 1.1 # Predicted Lat Acc threshold to abort entering state if speed drops.
_TURNING_LAT_ACC_TH = 1.6 # Lat Acc threshold to trigger turning state.
_URGENT_PRED_LAT_ACC_TH = 3. # Predicted Lat Acc threshold that requires an immediate speed reduction.
_LEAVING_LAT_ACC_TH = 1.3 # Lat Acc threshold to trigger leaving turn state.
_FINISH_LAT_ACC_TH = 1.1 # Lat Acc threshold to trigger the end of the turn cycle.
_A_LAT_REG_MAX = 2. # Maximum lateral acceleration
_RELIEF_CONFIRMATION_FRAMES = max(1, int(round(0.5 / DT_MDL)))
_TARGET_TIGHTEN_CONFIRMATION_FRAMES = max(1, int(round(0.1 / DT_MDL)))
_TARGET_RELEASE_CONFIRMATION_FRAMES = max(1, int(round(0.15 / DT_MDL)))
_TARGET_TIGHTEN_RATE = 5. # m/s^2
_TARGET_RELEASE_RATE = 1. # m/s^2
_BELOW_EGO_TARGET_RELEASE_RATE = 3. # m/s^2
_MIN_PRED_SPEED = 1. # m/s
_MIN_ACTIVATION_SPEED = 10. # m/s
_NO_OVERSHOOT_TIME_HORIZON = 4. # s. Time to use for velocity desired based on a_target when not overshooting.
# Lookup table for the minimum smooth deceleration during the ENTERING state
# depending on the actual maximum absolute lateral acceleration predicted on the turn ahead.
_ENTERING_SMOOTH_DECEL_V = [-0.2, -1.] # min decel value allowed on ENTERING state
_ENTERING_SMOOTH_DECEL_BP = [1.3, 3.] # absolute value of lat acc ahead
# Lookup table for the acceleration for the TURNING state
# depending on the current lateral acceleration of the vehicle.
_TURNING_ACC_V = [0.5, 0., -0.4] # acc value
_TURNING_ACC_BP = [1.5, 2.3, 3.] # absolute value of current lat acc
_LEAVING_ACC = 0.5 # Conformable acceleration to regain speed while leaving a turn.
class SmartCruiseControlVision:
@@ -61,62 +65,14 @@ class SmartCruiseControlVision:
self.state = VisionState.disabled
self.current_lat_acc = 0.
self.max_pred_lat_acc = 0.
self.relief_frames = 0
self.tighten_frames = 0
self.release_frames = 0
def _v_demand(self) -> float:
return max(MIN_V, min(self.v_target, self.v_cruise_setpoint))
def _curve_is_urgent(self) -> bool:
return self.current_lat_acc >= _TURNING_LAT_ACC_TH or self.max_pred_lat_acc >= _URGENT_PRED_LAT_ACC_TH
def _filtered_v_target(self) -> float:
demand = self._v_demand()
if self.output_v_target == V_CRUISE_UNSET:
self.tighten_frames = 0
self.release_frames = 0
if self._curve_is_urgent():
return demand
return max(demand, min(self.v_ego, self.v_cruise_setpoint))
if demand < self.output_v_target:
self.release_frames = 0
if self._curve_is_urgent():
self.tighten_frames = 0
return demand
self.tighten_frames += 1
if self.tighten_frames < _TARGET_TIGHTEN_CONFIRMATION_FRAMES:
return self.output_v_target
return max(demand, self.output_v_target - _TARGET_TIGHTEN_RATE * DT_MDL)
self.tighten_frames = 0
releasing_brake = self.output_v_target < min(self.v_ego, demand)
if not releasing_brake and self.relief_frames < _RELIEF_CONFIRMATION_FRAMES:
self.release_frames = 0
return self.output_v_target
if demand > self.output_v_target:
self.release_frames += 1
if self.release_frames < _TARGET_RELEASE_CONFIRMATION_FRAMES:
return self.output_v_target
else:
self.release_frames = 0
release_rate = _BELOW_EGO_TARGET_RELEASE_RATE if releasing_brake else _TARGET_RELEASE_RATE
return min(demand, self.output_v_target + release_rate * DT_MDL)
def get_a_target_from_control(self) -> float:
return self.a_ego
return self.a_target
def get_v_target_from_control(self) -> float:
if self.is_active:
return self._filtered_v_target()
return max(self.v_target, MIN_V) + self.a_target * _NO_OVERSHOOT_TIME_HORIZON
self.tighten_frames = 0
self.release_frames = 0
return V_CRUISE_UNSET
def _update_params(self) -> None:
@@ -126,27 +82,25 @@ class SmartCruiseControlVision:
def _update_calculations(self, sm: messaging.SubMaster) -> None:
if not self.long_enabled:
return
else:
rate_plan = np.array(np.abs(sm['modelV2'].orientationRate.z))
vel_plan = np.array(sm['modelV2'].velocity.x)
rate_plan = np.asarray(np.abs(sm['modelV2'].orientationRate.z), dtype=float)
vel_plan = np.asarray(sm['modelV2'].velocity.x, dtype=float)
size = min(len(rate_plan), len(vel_plan))
rate_plan, vel_plan = rate_plan[:size], vel_plan[:size]
valid = np.isfinite(rate_plan) & np.isfinite(vel_plan) & (vel_plan >= _MIN_PRED_SPEED)
self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
self.max_pred_lat_acc = 0.
self.v_target = V_CRUISE_UNSET
if np.any(valid):
self.max_pred_lat_acc = float(np.percentile(rate_plan[valid] * vel_plan[valid], 97))
max_pred_curvature = float(np.percentile(rate_plan[valid] / vel_plan[valid], 97))
if max_pred_curvature > 0.:
self.v_target = min(float((_A_LAT_REG_MAX / max_pred_curvature) ** 0.5), V_CRUISE_UNSET)
# get the maximum lat accel from the model
predicted_lat_accels = rate_plan * vel_plan
self.max_pred_lat_acc = np.percentile(predicted_lat_accels, 97)
# get the maximum curve based on the current velocity
v_ego = max(self.v_ego, 0.1) # ensure a value greater than 0 for calculations
max_curve = self.max_pred_lat_acc / (v_ego**2)
# Get the target velocity for the maximum curve
self.v_target = (_A_LAT_REG_MAX / max_curve) ** 0.5
def _update_state_machine(self) -> tuple[bool, bool]:
# ENABLED, ENTERING, TURNING, LEAVING, OVERRIDING
relief = self.current_lat_acc < _FINISH_LAT_ACC_TH and self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH
self.relief_frames = self.relief_frames + 1 if self.state in ACTIVE_STATES and relief else 0
if self.state != VisionState.disabled:
# longitudinal and feature disable always have priority in a non-disabled state
if not self.long_enabled or not self.enabled:
@@ -158,7 +112,7 @@ class SmartCruiseControlVision:
# ENABLED
if self.state == VisionState.enabled:
# Do not enter a turn control cycle if the speed is low.
if self.v_ego <= _MIN_ACTIVATION_SPEED:
if self.v_ego <= MIN_V:
pass
# If significant lateral acceleration is predicted ahead, then move to Entering turn state.
elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
@@ -174,26 +128,23 @@ class SmartCruiseControlVision:
# Transition to Turning if current lateral acceleration is over the threshold.
if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
self.state = VisionState.turning
# Begin releasing only after both current and predicted lateral acceleration stay clear.
elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES:
self.state = VisionState.leaving
# Abort if the predicted lateral acceleration drops
elif self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH:
self.state = VisionState.enabled
# TURNING
elif self.state == VisionState.turning:
# Transition out of Turning if current lateral acceleration drops below a threshold.
# Transition to Leaving if current lateral acceleration drops below a threshold.
if self.current_lat_acc <= _LEAVING_LAT_ACC_TH:
self.state = VisionState.entering if self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH else VisionState.leaving
self.state = VisionState.leaving
# LEAVING
elif self.state == VisionState.leaving:
# Transition back to Turning if current lateral acceleration goes back over the threshold.
if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
self.state = VisionState.turning
# Start a new turn cycle immediately if another curve is predicted.
elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
self.state = VisionState.entering
# Finish after confirmed relief and a gradual release to the cruise setpoint.
elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES and self.output_v_target >= self.v_cruise_setpoint:
# Finish if current lateral acceleration goes below a threshold.
elif self.current_lat_acc < _FINISH_LAT_ACC_TH:
self.state = VisionState.enabled
# DISABLED
@@ -206,11 +157,32 @@ class SmartCruiseControlVision:
enabled = self.state in ENABLED_STATES
active = self.state in ACTIVE_STATES
if not active:
self.relief_frames = 0
return enabled, active
def _update_solution(self) -> float:
# DISABLED, ENABLED, OVERRIDING
if self.state not in ACTIVE_STATES:
# when not overshooting, calculate v_turn as the speed at the prediction horizon when following
# the smooth deceleration.
a_target = self.a_ego
# ENTERING
elif self.state == VisionState.entering:
# when not overshooting, target a smooth deceleration in preparation for a sharp turn to come.
a_target = np.interp(self.max_pred_lat_acc, _ENTERING_SMOOTH_DECEL_BP, _ENTERING_SMOOTH_DECEL_V)
# TURNING
elif self.state == VisionState.turning:
# When turning, we provide a target acceleration that is comfortable for the lateral acceleration felt.
a_target = np.interp(self.current_lat_acc, _TURNING_ACC_BP, _TURNING_ACC_V)
# LEAVING
elif self.state == VisionState.leaving:
# When leaving, we provide a comfortable acceleration to regain speed.
a_target = _LEAVING_ACC
else:
raise NotImplementedError(f"SCC-V state not supported: {self.state}")
return a_target
def update(self, sm: messaging.SubMaster, long_enabled: bool, long_override: bool, v_ego: float, a_ego: float,
v_cruise_setpoint: float) -> None:
self.long_enabled = long_enabled
@@ -223,7 +195,7 @@ class SmartCruiseControlVision:
self._update_calculations(sm)
self.is_enabled, self.is_active = self._update_state_machine()
self.a_target = self.a_ego
self.a_target = self._update_solution()
self.output_v_target = self.get_v_target_from_control()
self.output_a_target = self.get_a_target_from_control()
@@ -1,216 +0,0 @@
import inspect
from typing import Any
from unittest import mock
import numpy as np
from opendbc.car.interfaces import ACCEL_MAX, ACCEL_MIN
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import N, LongitudinalMpc, LongitudinalPlanSource
from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.constants import AccelProfile
from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP as Plant
def configure(plant, *, enabled=True, profile=AccelProfile.normal):
controller: Any = plant.planner.accel_controller
controller.enabled = enabled
controller.profile = profile
controller.update_params = lambda: None
dec: Any = plant.planner.dec
dec._enabled = False
dec._read_params = lambda: None
def record_candidates(plant):
snapshots = []
planner: Any = plant.planner
original = planner.update_accel_controller
def wrapper(sm, candidates):
before = tuple(candidates)
after = original(sm, candidates)
snapshots.append((before, tuple(after)))
return after
planner.update_accel_controller = wrapper
return snapshots
class TestAccelControllerPlannerIntegration(OpenpilotTestCase):
def test_one_stock_mpc_solve_with_unmodified_bounds_and_api(self):
plant = Plant(enabled=True, lead_relevancy=True, speed=20.0, distance_lead=70.0)
configure(plant, profile=AccelProfile.eco)
mpc: Any = plant.planner.mpc
original_run = mpc.run
run_calls = []
params_at_solve = []
def count_run():
run_calls.append(None)
params_at_solve.append(mpc.params.copy())
return original_run()
mpc.run = count_run
result = plant.step(v_lead=14.0, v_cruise=25.0)
self.assertEqual(len(run_calls), 1)
self.assertTrue(np.isfinite(result["a_target"]))
self.assertEqual(LongitudinalMpc.__bases__, (object,))
self.assertEqual(tuple(inspect.signature(LongitudinalMpc.update).parameters), ("self", "radarstate", "personality"))
self.assertFalse(hasattr(mpc, "set_jerk_cost_multiplier"))
self.assertFalse(hasattr(mpc, "cruise_accel_max"))
self.assertEqual(params_at_solve[0].shape, (N + 1, 6))
np.testing.assert_array_equal(params_at_solve[0][:, 0], ACCEL_MIN)
np.testing.assert_array_equal(params_at_solve[0][:, 1], ACCEL_MAX)
def test_stock_lead_mpc_braking_remains_authoritative(self):
plant = Plant(enabled=True, lead_relevancy=True, speed=20.0, distance_lead=30.0)
configure(plant, profile=AccelProfile.eco)
snapshots = record_candidates(plant)
stock_mpc_won = False
for _ in range(20):
result = plant.step(v_lead=5.0, v_cruise=30.0)
stock, augmented = snapshots[-1]
mpc_candidate = stock[0]
selected = min(augmented, key=lambda candidate: candidate[0])
self.assertAlmostEqual(result["a_target"], selected[0])
if mpc_candidate[0] < 0.0 and selected == mpc_candidate:
stock_mpc_won = True
assert mpc_candidate[1] in (LongitudinalPlanSource.lead0, LongitudinalPlanSource.lead1)
break
self.assertTrue(stock_mpc_won, "the hook must never mask stock lead braking")
def test_stock_should_stop_survives_controller_candidates(self):
plant = Plant(enabled=True, lead_relevancy=True, speed=0.2, distance_lead=3.0)
configure(plant, profile=AccelProfile.normal)
snapshots = record_candidates(plant)
result = plant.step(v_lead=0.0, v_cruise=8.0)
stock, augmented = snapshots[-1]
self.assertTrue(any(candidate[2] for candidate in stock))
self.assertTrue(any(candidate[2] for candidate in augmented))
self.assertTrue(result["should_stop"])
self.assertAlmostEqual(result["a_target"], min(augmented, key=lambda candidate: candidate[0])[0])
def test_dec_blended_entry_limits_the_first_model_brake_step(self):
class DecStub:
mode_name = "acc"
def update(self, _sm):
pass
def active(self):
return True
def mode(self):
return self.mode_name
plant = Plant(
enabled=True, e2e=True, speed=22.0,
model_action_fn=lambda _current_time, _v_ego, _a_ego: (-2.0, False),
actuator_delay=0.15, actuator_lag=0.20,
)
configure(plant)
dec = DecStub()
planner: Any = plant.planner
planner.dec = dec
outputs = []
for frame in range(20):
if frame == 10:
dec.mode_name = "blended"
result = plant.step(v_lead=0.0, v_cruise=22.0)
outputs.append(result["a_target"])
self.assertGreaterEqual(outputs[10] - outputs[9], -0.15 - 1e-9)
self.assertFalse(result["fcw"])
def test_model_endpoint_urgency_does_not_bypass_entry_ramp(self):
plant = Plant(enabled=True, e2e=True, speed=21.0)
planner: Any = plant.planner
planner.dec._active = True
planner.dec._has_slow_down = True
planner.dec._urgency = 1.0
planner.previous_plan_accel = -0.136
first = planner.select_model_accel(0.0, -1.140, blended=True, should_stop=False, fcw=False, reset=False)
second = planner.select_model_accel(0.0, -1.140, blended=True, should_stop=False, fcw=False, reset=False)
self.assertAlmostEqual(first, -0.286)
self.assertAlmostEqual(second, -0.436)
def test_dec_exit_limits_positive_acceleration_step(self):
plant = Plant(enabled=True, e2e=True, speed=6.0)
planner: Any = plant.planner
planner.dec._active = True
planner.previous_plan_accel = 0.76
self.assertAlmostEqual(planner.select_model_accel(1.94, 0.76, blended=True, should_stop=False, fcw=False, reset=False), 0.76)
first = planner.select_model_accel(1.94, 0.76, blended=False, should_stop=False, fcw=False, reset=False)
second = planner.select_model_accel(1.94, 0.76, blended=False, should_stop=False, fcw=False, reset=False)
self.assertAlmostEqual(first, 0.91)
self.assertAlmostEqual(second, 1.06)
def test_dec_exit_transition_reaches_the_final_candidate_list(self):
class DecStub:
mode_name = "blended"
def update(self, _sm):
pass
def active(self):
return True
def mode(self):
return self.mode_name
plant = Plant(
enabled=True, e2e=True, speed=22.0,
model_action_fn=lambda _current_time, _v_ego, _a_ego: (0.20, False),
)
configure(plant, enabled=False)
dec = DecStub()
planner: Any = plant.planner
planner.dec = dec
def update_mpc(_radar_state, personality):
plant.planner.mpc.source = LongitudinalPlanSource.cruise
plant.planner.mpc.crash_cnt = 0
# Exercise final candidate arbitration without depending on the local ACADOS build.
with (
mock.patch.object(plant.planner.mpc, "update", side_effect=update_mpc),
mock.patch("openpilot.selfdrive.controls.lib.longitudinal_planner.get_accel_from_plan", return_value=1.94),
mock.patch("openpilot.selfdrive.controls.lib.longitudinal_planner.get_cruise_accel", return_value=1.94),
):
outputs = [plant.step(v_lead=0.0, v_cruise=30.0)["a_target"] for _ in range(4)]
self.assertAlmostEqual(outputs[-1], 0.20)
dec.mode_name = "acc"
first = plant.step(v_lead=0.0, v_cruise=30.0)["a_target"]
second = plant.step(v_lead=0.0, v_cruise=30.0)["a_target"]
self.assertLessEqual(first - outputs[-1], 0.15 + 1e-9)
self.assertLessEqual(second - first, 0.15 + 1e-9)
self.assertEqual(plant.planner.mpc.source, LongitudinalPlanSource.cruise)
def test_disengaged_cruise_state_cannot_leak_into_first_sport_accel(self):
plant = Plant(enabled=False, speed=10.0)
configure(plant, profile=AccelProfile.sport)
with (
mock.patch.object(plant.planner.mpc, "update", return_value=None),
mock.patch("openpilot.selfdrive.controls.lib.longitudinal_planner.get_accel_from_plan", return_value=1.30),
):
for _ in range(12):
self.assertAlmostEqual(plant.step(v_lead=0.0, v_cruise=30.0)["a_target"], 0.0)
self.assertAlmostEqual(plant.planner.a_cruise, 0.0)
plant.enabled = True
first = plant.step(v_lead=0.0, v_cruise=30.0)["a_target"]
self.assertGreater(first, 0.0)
self.assertLessEqual(first, 0.10)
@@ -1,392 +0,0 @@
import numpy as np
from unittest import mock
from opendbc.car import DT_CTRL, gen_empty_fingerprint, structs
from openpilot.common.parameterized import parameterized
from openpilot.common.test import OpenpilotTestCase
from opendbc.car.car_helpers import interfaces
from opendbc.car.gm.values import CAR as GM
from opendbc.car.honda.values import CAR as HONDA
from opendbc.car.hyundai.values import CAR as HYUNDAI
from opendbc.car.rivian.values import CAR as RIVIAN
from opendbc.car.toyota.values import CAR as TOYOTA
from opendbc.car.volkswagen.values import CAR as VOLKSWAGEN
from openpilot.selfdrive.controls.lib.drive_helpers import should_stop
from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState
from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import STOPPING_SETTLE_FRAMES, STOPPING_SPEED_TOLERANCE
from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PRIUS_TSS2_ROUTE_MODEL, PlantSP
STOP_ACCEL_VEHICLES = (TOYOTA.TOYOTA_RAV4_TSS2, HONDA.HONDA_CIVIC_2022, VOLKSWAGEN.VOLKSWAGEN_ARTEON_MK1, RIVIAN.RIVIAN_R1)
SETTLE_VEHICLES = (TOYOTA.TOYOTA_RAV4_TSS2, HONDA.HONDA_CIVIC_2022, VOLKSWAGEN.VOLKSWAGEN_ARTEON_MK1)
ROUTE_STOP_ONSETS = (
(0.280, -0.290, -0.220, -0.220),
(0.290, -0.497, -0.270, -0.302),
(0.464, -0.223, -0.264, -0.292),
(0.467, -0.582, -0.316, -0.359),
(0.530, -0.311, -0.309, -0.333),
(0.581, -0.467, -0.312, -0.352),
(0.398, -0.557, -0.311, -0.348),
(0.517, -0.290, -0.301, -0.327),
(0.312, -0.420, -0.271, -0.304),
(0.474, -0.509, -0.303, -0.347),
(0.241, -0.554, -0.573, -0.617),
(0.292, -0.154, -0.302, -0.326),
)
def get_car_params(candidate):
fingerprint = gen_empty_fingerprint()
interface = interfaces[candidate]
CP = interface.get_params(candidate, fingerprint, [], True, False, False)
return CP, interface.get_params_sp(CP, candidate, fingerprint, [], True, False, False)
def make_car_state(v_ego=0.2, a_ego=0.0, standstill=False) -> structs.CarState:
state = structs.CarState(vEgo=float(v_ego), aEgo=float(a_ego), standstill=standstill)
state.cruiseState.standstill = standstill
return state
def make_control(candidate, initial_accel=-0.33):
CP, CP_SP = get_car_params(candidate)
control = LongControl(CP, CP_SP)
control.long_control_state = LongCtrlState.pid
control.last_output_accel = initial_accel
return CP, control
def stock_stopping_output(output_accel, stop_accel):
return min(output_accel, 0.0) - DT_CTRL if output_accel > stop_accel else output_accel
class TestLongControlSP(OpenpilotTestCase):
def test_stop_threshold_matches_the_shared_helper(self):
assert should_stop(0.29, 0.0)
assert not should_stop(0.3, 0.0)
assert not should_stop(0.29, 0.1)
@parameterized.expand(ROUTE_STOP_ONSETS, names=("v_ego", "a_ego", "a_target", "initial_accel"))
def test_logged_stop_onsets_hold_the_existing_brake(self, v_ego, a_ego, a_target, initial_accel):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, initial_accel)
output = control.update(True, make_car_state(v_ego, a_ego), a_target, True, (-3.5, 2.0))
assert control.long_control_state == LongCtrlState.stopping
self.assertAlmostEqual(output, initial_accel)
def test_glide_hold_survives_a_soft_deceleration_sample(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -0.166)
samples = ((0.388, -0.201, -0.164), (0.330, -0.120, -0.140), (0.283, -0.0675, -0.120))
outputs = [control.update(True, make_car_state(v_ego, a_ego), a_target, True, (-3.5, 2.0)) for v_ego, a_ego, a_target in samples]
np.testing.assert_allclose(outputs, [-0.166] * len(samples), rtol=1e-6, atol=1e-12)
def test_glide_response_reaches_the_stock_rate_when_deceleration_stops(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -0.166)
control.update(True, make_car_state(0.388, -0.201), -0.164, True, (-3.5, 2.0))
output = control.update(True, make_car_state(0.330, -0.01), -0.140, True, (-3.5, 2.0))
assert -0.176 < output < -0.175
def test_glide_response_increases_with_stopping_distance_error(self):
_, nominal = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -0.166)
_, distance_error = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -0.166)
for control in (nominal, distance_error):
control.update(True, make_car_state(0.388, -0.201), -0.164, True, (-3.5, 2.0))
nominal_output = nominal.update(True, make_car_state(0.330, -0.050), -0.140, True, (-3.5, 2.0))
distance_error_output = distance_error.update(True, make_car_state(0.400, -0.050), -0.140, True, (-3.5, 2.0))
assert -0.176 < distance_error_output < nominal_output
@parameterized.expand(((1.0, 0.0), (0.75, 0.4375), (0.5, 0.75), (0.0, 1.0)), names=("decel_fraction", "expected_rate"))
def test_stopping_rate_scales_with_realized_deceleration(self, decel_fraction, expected_rate):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
output = control.update(True, make_car_state(0.3, -0.12 * decel_fraction), 0.0, True, (-3.5, 2.0))
self.assertAlmostEqual((-0.33 - output) / DT_CTRL, expected_rate, delta=1e-6)
def test_stopping_rate_scales_with_planner_demand(self):
_, gentle = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
_, urgent = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
gentle_output = gentle.update(True, make_car_state(0.3, -0.12), -0.34, True, (-3.5, 2.0))
urgent_output = urgent.update(True, make_car_state(0.3, -0.12), -1.0, True, (-3.5, 2.0))
assert -0.331 < gentle_output < -0.33
self.assertAlmostEqual(urgent_output, -0.34)
def test_glide_hold_yields_to_stronger_planner_braking(self):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -0.166)
control.update(True, make_car_state(0.388, -0.201), -0.164, True, (-3.5, 2.0))
output = control.update(True, make_car_state(0.330, -0.120), -1.0, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(-0.166, CP.stopAccel))
@parameterized.expand(STOP_ACCEL_VEHICLES, names=("candidate",))
def test_urgent_braking_matches_the_stock_ramp(self, candidate):
CP, control = make_control(candidate)
CS = make_car_state(0.8, -0.1)
output = control.last_output_accel
for _ in range(round(1.0 / DT_CTRL)):
output = control.update(True, CS, -3.0, True, (-3.5, 2.0))
expected = -0.33
for _ in range(round(1.0 / DT_CTRL)):
expected = stock_stopping_output(expected, CP.stopAccel)
self.assertAlmostEqual(output, expected)
@parameterized.expand(STOP_ACCEL_VEHICLES, names=("candidate",))
def test_stronger_planner_brake_matches_the_stock_ramp(self, candidate):
CP, control = make_control(candidate)
outputs = [control.update(True, make_car_state(0.3, -0.3), -1.0, True, (-3.5, 2.0)) for _ in range(10)]
expected = []
output = -0.33
for _ in range(10):
output = stock_stopping_output(output, CP.stopAccel)
expected.append(output)
np.testing.assert_allclose(outputs, expected, rtol=1e-6, atol=1e-12)
@parameterized.expand(STOP_ACCEL_VEHICLES, names=("candidate",))
def test_insufficient_deceleration_uses_most_of_the_stock_ramp(self, candidate):
CP, control = make_control(candidate)
output = control.update(True, make_car_state(0.6, -0.1), -0.1, True, (-3.5, 2.0))
if -0.33 > CP.stopAccel:
assert -0.34 < output < -0.338
else:
self.assertAlmostEqual(output, -0.33)
def test_deceleration_noise_cannot_release_the_brake(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
outputs = [control.update(True, make_car_state(0.3, -0.3 if frame % 2 else 0.0), -0.1, True, (-3.5, 2.0)) for frame in range(40)]
assert all(current <= previous for previous, current in zip(outputs[:-1], outputs[1:], strict=True))
def test_planner_noise_cannot_release_the_brake(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
outputs = [control.update(True, make_car_state(0.3, -0.3), -1.0 if frame % 2 else -0.1, True, (-3.5, 2.0)) for frame in range(40)]
assert all(current <= previous for previous, current in zip(outputs[:-1], outputs[1:], strict=True))
@parameterized.expand(
(
(float("nan"), -0.3, -0.1),
(0.3, float("nan"), -0.1),
(0.3, -0.3, float("nan")),
(float("inf"), -0.3, -0.1),
(0.3, -float("inf"), -0.1),
(0.3, -0.3, float("inf")),
),
names=("v_ego", "a_ego", "a_target"),
)
def test_invalid_state_uses_the_stock_ramp(self, v_ego, a_ego, a_target):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
output = control.update(True, make_car_state(v_ego, a_ego), a_target, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(-0.33, CP.stopAccel))
@parameterized.expand(
(
(0.24, 0.0, -0.49, 0.15, 0.0),
(0.53, -0.31, -0.49, 0.35, 0.1),
(0.24, 0.0, 0.0, 0.15, 0.0),
(0.464, -0.223, 0.0, 0.25, 0.05),
(0.53, -0.31, 0.0, 0.35, 0.1),
(0.24, 0.0, 0.49, 0.15, 0.0),
(0.53, -0.31, 0.49, 0.25, 0.05),
(0.6, -0.3, 0.49, 0.35, 0.1),
(0.6, -0.3, 0.49, 0.5, 0.1),
),
names=("speed", "initial_accel", "grade_accel", "actuator_lag", "actuator_delay"),
)
def test_smooth_stop_distance_is_bounded(self, speed, initial_accel, grade_accel, actuator_lag, actuator_delay):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, initial_accel)
applied_accel = initial_accel
delay = [initial_accel] * round(actuator_delay / DT_CTRL)
distance = 0.0
outputs = []
for _ in range(round(4.0 / DT_CTRL)):
command = control.update(True, make_car_state(speed, applied_accel), -0.1, True, (-3.5, 2.0))
outputs.append(command)
delayed_command = command
if delay:
delay.append(command)
delayed_command = delay.pop(0)
applied_accel += DT_CTRL / actuator_lag * (delayed_command + grade_accel - applied_accel)
speed = max(0.0, speed + applied_accel * DT_CTRL)
distance += speed * DT_CTRL
if speed == 0.0:
break
assert speed == 0.0
assert distance < 1.0
assert all(current <= previous for previous, current in zip(outputs[:-1], outputs[1:], strict=True))
@parameterized.expand(STOP_ACCEL_VEHICLES, names=("candidate",))
def test_standstill_uses_the_stock_ramp(self, candidate):
CP, control = make_control(candidate)
control.long_control_state = LongCtrlState.off
CS = make_car_state(0.0, 0.0, standstill=True)
outputs = [control.update(True, CS, 0.0, False, (-3.5, 2.0)) for _ in range(round(2.0 / DT_CTRL))]
expected = -0.33
for _ in range(round(2.0 / DT_CTRL)):
expected = stock_stopping_output(expected, CP.stopAccel)
self.assertAlmostEqual(outputs[0], stock_stopping_output(-0.33, CP.stopAccel))
self.assertAlmostEqual(outputs[-1], expected)
@parameterized.expand(SETTLE_VEHICLES, names=("candidate",))
def test_final_stop_builds_brake_smoothly_while_vehicle_settles(self, candidate):
_, control = make_control(candidate)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
outputs = [control.update(True, make_car_state(0.0006, a_ego, standstill=True), -0.032, True, (-3.5, 2.0)) for a_ego in (-1.098, -0.950, -0.609, -0.286)]
changes = -np.diff([-0.33, *outputs])
assert np.all(changes > 0.0)
assert np.all(np.diff(changes) > 0.0)
assert changes[-1] < 0.001
@parameterized.expand((-0.09, 0.0, 0.1), names=("a_ego",))
def test_settled_vehicle_uses_the_stock_hold_ramp(self, a_ego):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
output = control.update(True, make_car_state(0.0, a_ego, standstill=True), -0.1, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(-0.33, CP.stopAccel))
@parameterized.expand(SETTLE_VEHICLES, names=("candidate",))
def test_direct_terminal_entry_builds_brake_smoothly(self, candidate):
_, control = make_control(candidate)
CS = make_car_state(0.0006, -0.3, standstill=True)
outputs = [control.update(True, CS, -0.1, True, (-3.5, 2.0)) for _ in range(4)]
rates = -np.diff([-0.33, *outputs]) / DT_CTRL
np.testing.assert_allclose(rates, [(frame / STOPPING_SETTLE_FRAMES) ** 2 for frame in range(1, 5)], rtol=1e-6, atol=1e-12)
def test_direct_terminal_entry_keeps_urgent_stock_braking(self):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
output = control.update(True, make_car_state(0.0006, -0.3, standstill=True), -1.0, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(-0.33, CP.stopAccel))
@parameterized.expand((0.0, -0.05), names=("initial_accel",))
def test_direct_terminal_entry_first_builds_meaningful_brake(self, initial_accel):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, initial_accel)
output = control.update(True, make_car_state(0.0006, -0.3, standstill=True), 0.0, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(initial_accel, CP.stopAccel))
@parameterized.expand(SETTLE_VEHICLES, names=("candidate",))
def test_final_settling_ramp_is_bounded(self, candidate):
_, control = make_control(candidate)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
CS = make_car_state(0.0, -0.3, standstill=True)
outputs = [control.update(True, CS, -0.1, True, (-3.5, 2.0)) for _ in range(STOPPING_SETTLE_FRAMES + 1)]
rates = -np.diff([-0.33, *outputs]) / DT_CTRL
expected = [(frame / STOPPING_SETTLE_FRAMES) ** 2 for frame in range(1, STOPPING_SETTLE_FRAMES + 1)] + [1.0]
np.testing.assert_allclose(rates, expected, rtol=1e-6, atol=1e-12)
@parameterized.expand(((0.6, -0.1, False), (0.0, 0.0, True)), names=("v_ego", "a_ego", "standstill"))
def test_stopping_never_releases_a_stronger_command(self, v_ego, a_ego, standstill):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -3.0)
output = control.update(True, make_car_state(v_ego, a_ego, standstill), 0.0, True, (-3.5, 2.0))
self.assertAlmostEqual(output, -3.0)
def test_reported_standstill_while_moving_can_hold_the_brake(self):
_, control = make_control(GM.CHEVROLET_BOLT_EUV)
control.long_control_state = LongCtrlState.off
output = control.update(True, make_car_state(0.3, -0.3, standstill=True), -0.1, False, (-3.5, 2.0))
self.assertAlmostEqual(output, -0.33)
def test_stopping_removes_positive_acceleration_immediately(self):
_, control = make_control(HYUNDAI.HYUNDAI_SONATA, 0.2)
output = control.update(True, make_car_state(0.2, -0.2), -0.1, True, (-3.5, 2.0))
self.assertAlmostEqual(output, -DT_CTRL)
def test_rollback_uses_the_stock_ramp(self):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
output = control.update(True, make_car_state(-0.1, 0.1), -0.1, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(-0.33, CP.stopAccel))
def test_rollback_after_settling_arms_uses_the_stock_ramp(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
control.update(True, make_car_state(0.01, -0.3), -0.1, True, (-3.5, 2.0))
previous = control.last_output_accel
output = control.update(True, make_car_state(-0.04, -0.3), -0.1, True, (-3.5, 2.0))
self.assertAlmostEqual(output, previous - DT_CTRL)
def test_small_velocity_noise_does_not_trigger_the_stock_rate(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
output = control.update(True, make_car_state(-0.04, -0.3, standstill=True), -0.1, True, (-3.5, 2.0))
assert -0.331 < output < -0.33
def test_terminal_speed_chatter_cannot_extend_settling_ramp(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
outputs = [
control.update(True, make_car_state(0.049 if frame % 2 == 0 else 0.051, -0.3), -0.1, True, (-3.5, 2.0)) for frame in range(STOPPING_SETTLE_FRAMES + 2)
]
rates = -np.diff([-0.33, *outputs]) / DT_CTRL
np.testing.assert_allclose(
rates[:STOPPING_SETTLE_FRAMES], [(frame / STOPPING_SETTLE_FRAMES) ** 2 for frame in range(1, STOPPING_SETTLE_FRAMES + 1)], rtol=1e-6, atol=1e-12
)
np.testing.assert_allclose(rates[-2:], [1.0, 1.0], rtol=1e-6, atol=1e-12)
def test_terminal_speed_plateau_cannot_extend_settling_ramp(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
CS = make_car_state(0.03, -0.3)
outputs = [control.update(True, CS, -0.1, True, (-3.5, 2.0)) for _ in range(STOPPING_SETTLE_FRAMES + 1)]
rates = -np.diff([-0.33, *outputs]) / DT_CTRL
np.testing.assert_allclose(rates[-2:], [1.0, 1.0], rtol=1e-6, atol=1e-12)
def test_interrupted_stop_cannot_reuse_settling_hold(self):
CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.update(True, make_car_state(0.28, -0.29), -0.22, True, (-3.5, 2.0))
control.update(False, make_car_state(0.0, 0.0, standstill=True), 0.0, False, (-3.5, 2.0))
output = control.update(True, make_car_state(0.0, -0.3, standstill=True), -0.1, True, (-3.5, 2.0))
self.assertAlmostEqual(output, stock_stopping_output(0.0, CP.stopAccel))
def test_departure_uses_the_stock_pid_path(self):
_, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
control.long_control_state = LongCtrlState.stopping
output = control.update(True, make_car_state(0.0), 0.6, False, (-3.5, 2.0))
assert control.long_control_state == LongCtrlState.pid
assert output > 0.0
def test_planner_mpc_and_longcontrol_complete_a_smooth_stop(self):
plant = PlantSP(
lead_relevancy=True,
speed=0.6,
distance_lead=3.6,
run_long_control=True,
actuator_model=PRIUS_TSS2_ROUTE_MODEL,
)
plant.planner.accel_controller.enabled = True
plant.planner.accel_controller.profile = 1
plant.planner.dec._enabled = False
commands = []
speeds = []
states = []
solver_statuses = []
with (
mock.patch.object(plant.planner.accel_controller, "update_params", return_value=None),
mock.patch.object(plant.planner.dec, "_read_params", return_value=None),
):
while plant.current_time < 5.0:
result = plant.step(v_lead=0.0, v_cruise=8.0)
commands.append(result["actuator_command"])
speeds.append(result["speed"])
states.append(result["long_control_state"])
solver_statuses.append(plant.planner.mpc.solution_status)
stopping = states.index(LongCtrlState.stopping)
moving_stop_commands = [
command for command, state, speed in zip(commands, states, speeds, strict=True) if state == LongCtrlState.stopping and speed > STOPPING_SPEED_TOLERANCE
]
assert all(current <= previous + 1e-9 for previous, current in zip(commands[stopping:-1], commands[stopping + 1 :], strict=True))
assert len(moving_stop_commands) > 1 and max(moving_stop_commands) - min(moving_stop_commands) < 1e-9
assert plant.speed == 0.0 and plant.distance < 1.0
assert plant.distance_lead - plant.distance > 3.0
assert all(status == 0 for status in solver_statuses)
@@ -1,397 +0,0 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
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.
"""
from collections import deque
from collections.abc import Callable
from dataclasses import dataclass
import math
import time
from typing import Any
import numpy as np
from openpilot.cereal import log, messaging
from opendbc.car.interfaces import ACCEL_MAX, ACCEL_MIN
from openpilot.common.realtime import DT_CTRL, DT_MDL, Ratekeeper
from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState
from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanner
from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant, PlannerSM
LeadObservation = dict[str, Any]
LeadObservationFn = Callable[[float, str, LeadObservation], LeadObservation | None]
ModelActionFn = Callable[[float, float, float], tuple[float, bool]]
EgoObservationFn = Callable[[float, float, float], tuple[float, float]]
@dataclass(frozen=True)
class ActuatorModel:
planner_delay: float
transport_delay: float
actuator_lag: float
command_rate_limit: float
stopping_acceleration: float
standstill_breakaway_acceleration: float
standstill_breakaway_time: float
def __post_init__(self):
nonnegative_fields = {
"planner_delay": self.planner_delay,
"transport_delay": self.transport_delay,
"actuator_lag": self.actuator_lag,
"standstill_breakaway_acceleration": self.standstill_breakaway_acceleration,
"standstill_breakaway_time": self.standstill_breakaway_time,
}
if any(not math.isfinite(value) or value < 0.0 for value in nonnegative_fields.values()):
raise ValueError(f"ActuatorModel fields must be finite and non-negative: {nonnegative_fields}")
if not math.isfinite(self.command_rate_limit) or self.command_rate_limit <= 0.0:
raise ValueError("command_rate_limit must be finite and positive")
if not math.isfinite(self.stopping_acceleration) or self.stopping_acceleration > 0.0:
raise ValueError("stopping_acceleration must be finite and non-positive")
# Conservative Prius TSS2 actuator model.
PRIUS_TSS2_ROUTE_MODEL = ActuatorModel(
planner_delay=0.05,
transport_delay=0.0,
actuator_lag=0.20,
command_rate_limit=4.0,
stopping_acceleration=-2.0,
standstill_breakaway_acceleration=1.0,
standstill_breakaway_time=0.05,
)
class PlantSP(Plant):
"""Closed-loop plant with configurable observations and actuator response."""
def __init__(
self,
lead_relevancy=False,
speed=0.0,
distance_lead=2.0,
enabled=True,
only_lead2=False,
only_radar=False,
e2e=False,
personality=0,
force_decel=False,
lead_observation_fn: LeadObservationFn | None = None,
model_action_fn: ModelActionFn | None = None,
ego_observation_fn: EgoObservationFn | None = None,
actuator_delay: float | None = None,
actuator_lag: float = 0.0,
actuator_model: ActuatorModel | None = None,
run_long_control: bool = False,
):
if actuator_delay is not None and (not math.isfinite(actuator_delay) or actuator_delay < 0.0):
raise ValueError("actuator_delay must be finite and non-negative")
if not math.isfinite(actuator_lag) or actuator_lag < 0.0:
raise ValueError("actuator_lag must be finite and non-negative")
self.rate = 1.0 / DT_MDL
if not Plant.messaging_initialized:
Plant.radar = messaging.pub_sock('radarState')
Plant.controls_state = messaging.pub_sock('controlsState')
Plant.selfdrive_state = messaging.pub_sock('selfdriveState')
Plant.car_state = messaging.pub_sock('carState')
Plant.plan = messaging.sub_sock('longitudinalPlan')
Plant.messaging_initialized = True
self.v_lead_prev = 0.0
self.distance = 0.0
self.speed = speed
self.should_stop = False
self.acceleration = 0.0
self.a_target = 0.0
self.actuator_command = 0.0
self.applied_actuator_command = 0.0
self.breakaway_confirmed = False
self._breakaway_timer = 0.0
# lead car
self.lead_relevancy = lead_relevancy
self.distance_lead = distance_lead
self.enabled = enabled
self.only_lead2 = only_lead2
self.only_radar = only_radar
self.e2e = e2e
self.personality = personality
self.force_decel = force_decel
self.lead_observation_fn = lead_observation_fn
self.model_action_fn = model_action_fn
self.ego_observation_fn = ego_observation_fn
self.actuator_model = actuator_model
self.actuator_delay = actuator_model.planner_delay if actuator_model is not None else actuator_delay
self.transport_delay = actuator_model.transport_delay if actuator_model is not None else actuator_delay
self.actuator_lag = actuator_model.actuator_lag if actuator_model is not None else actuator_lag
self.publish_realized_a_ego = any((lead_observation_fn is not None, model_action_fn is not None, ego_observation_fn is not None,
actuator_delay is not None, actuator_lag > 0.0, actuator_model is not None, run_long_control))
self.rk = Ratekeeper(self.rate, print_delay_threshold=100.0)
self.ts = 1.0 / self.rate
time.sleep(0.1)
self.sm = messaging.SubMaster(['longitudinalPlan'])
from opendbc.car.honda.values import CAR
from opendbc.car.honda.interface import CarInterface
CP = CarInterface.get_non_essential_params(CAR.HONDA_CIVIC)
if self.actuator_delay is not None:
CP.longitudinalActuatorDelay = self.actuator_delay
CP_SP = CarInterface.get_non_essential_params_sp(CP, CAR.HONDA_CIVIC)
self.planner = LongitudinalPlanner(CP, CP_SP, init_v=self.speed)
self.long_control = LongControl(CP, CP_SP) if run_long_control else None
if self.actuator_model is not None and self.speed >= 0.01:
self.breakaway_confirmed = True
self.integration_dt = DT_CTRL if run_long_control else self.ts
delay_steps = 0 if self.transport_delay is None else round(self.transport_delay / self.integration_dt)
self._actuator_delay_queue = deque([self.acceleration] * delay_steps)
@staticmethod
def _lead_message(observation: LeadObservation):
lead = log.RadarState.LeadData.new_message()
for field, value in observation.items():
setattr(lead, field, value)
return lead
def _observe_lead(self, lead_name: str, truth: LeadObservation, present_by_default: bool) -> LeadObservation | None:
if self.lead_observation_fn is None:
return dict(truth) if present_by_default else None
observed = self.lead_observation_fn(self.current_time, lead_name, dict(truth))
if observed is None:
return None
complete_observation = dict(truth)
complete_observation.update(observed)
return complete_observation
def _update_actuator(self, command: float) -> tuple[float, float]:
if self._actuator_delay_queue:
self._actuator_delay_queue.append(command)
delayed_command = self._actuator_delay_queue.popleft()
else:
delayed_command = command
if self.actuator_model is not None:
max_command_delta = self.actuator_model.command_rate_limit * self.integration_dt
self.applied_actuator_command = float(np.clip(delayed_command,
self.applied_actuator_command - max_command_delta,
self.applied_actuator_command + max_command_delta))
if self.speed < 0.01:
if self.applied_actuator_command <= 0.0:
self.breakaway_confirmed = False
self._breakaway_timer = 0.0
elif not self.breakaway_confirmed:
breakaway_ready = self.applied_actuator_command + 1e-9 >= self.actuator_model.standstill_breakaway_acceleration
if breakaway_ready:
self._breakaway_timer += self.integration_dt
else:
self._breakaway_timer = 0.0
self.breakaway_confirmed = breakaway_ready and self._breakaway_timer + 1e-9 >= self.actuator_model.standstill_breakaway_time
if not self.breakaway_confirmed:
self.acceleration = 0.0
return delayed_command, self.acceleration
else:
self.breakaway_confirmed = True
response_command = self.applied_actuator_command
else:
self.applied_actuator_command = delayed_command
response_command = delayed_command
if self.actuator_lag > 0.0:
alpha = 1.0 - math.exp(-self.integration_dt / self.actuator_lag)
self.acceleration += alpha * (response_command - self.acceleration)
else:
self.acceleration = response_command
return delayed_command, self.acceleration
def _integrate_ego(self, dt: float, stop_at_standstill: bool = False) -> None:
self.speed += self.acceleration * dt
if self.speed <= 0.0 or stop_at_standstill and self.speed < 0.01 and self.actuator_command <= 0.0:
self.speed = self.acceleration = 0.0
self.distance += self.speed * dt
def step(self, v_lead=0.0, prob_lead=1.0, v_cruise=50.0, pitch=0.0, prob_throttle=1.0):
# ******** publish a fake model going straight and fake calibration ********
# note that this is worst case for MPC, since model will delay long mpc by one time step
radar = messaging.new_message('radarState')
control = messaging.new_message('controlsState')
ss = messaging.new_message('selfdriveState')
car_state = messaging.new_message('carState')
vehicle_parameters = messaging.new_message('vehicleParameters')
car_control = messaging.new_message('carControl')
model = messaging.new_message('modelV2')
car_state_sp = messaging.new_message('carStateSP')
live_map_data_sp = messaging.new_message('liveMapDataSP')
gps_data = messaging.new_message('gpsLocation')
a_lead = (v_lead - self.v_lead_prev) / self.ts
self.v_lead_prev = v_lead
if self.lead_relevancy:
d_rel = np.maximum(0.0, self.distance_lead - self.distance)
v_rel = v_lead - self.speed
if self.only_radar:
status = True
elif prob_lead > 0.5:
status = True
else:
status = False
else:
d_rel = 200.0
v_rel = 0.0
prob_lead = 0.0
status = False
truth_lead: LeadObservation = {
"dRel": float(d_rel),
"yRel": 0.0,
"vRel": float(v_rel),
"vLead": float(v_lead),
"vLeadK": float(v_lead),
"aLeadK": float(a_lead),
"present": bool(status),
# TODO use real radard logic for this
"aLeadTau": float(_LEAD_ACCEL_TAU),
"modelProb": float(prob_lead),
"radar": bool(self.only_radar),
"radarTrackId": -1,
}
lead_one_observation = self._observe_lead("leadOne", truth_lead, not self.only_lead2)
lead_two_observation = self._observe_lead("leadTwo", truth_lead, True)
if lead_one_observation is not None:
radar.radarState.leadOne = self._lead_message(lead_one_observation)
if lead_two_observation is not None:
radar.radarState.leadTwo = self._lead_message(lead_two_observation)
# Simulate model predicting slightly faster speed
# this is to ensure lead policy is effective when model
# does not predict slowdown in e2e mode
position = log.XYZTData.new_message()
position.x = [float(x) for x in (self.speed + 0.5) * np.array(ModelConstants.T_IDXS)]
model.modelV2.position = position
if self.model_action_fn is None:
model_acceleration, model_should_stop = self.acceleration + 0.5, False
else:
model_acceleration, model_should_stop = self.model_action_fn(self.current_time, self.speed, self.acceleration)
model.modelV2.action.desiredAcceleration = float(model_acceleration)
model.modelV2.action.shouldStop = bool(model_should_stop)
velocity = log.XYZTData.new_message()
velocity.x = [float(x) for x in (self.speed + 0.5) * np.ones_like(ModelConstants.T_IDXS)]
velocity.x[0] = float(self.speed) # always start at current speed
model.modelV2.velocity = velocity
acceleration = log.XYZTData.new_message()
acceleration.x = [float(x) for x in np.zeros_like(ModelConstants.T_IDXS)]
model.modelV2.acceleration = acceleration
model.modelV2.meta.disengagePredictions.gasPressProbs = [float(prob_throttle) for _ in range(6)]
control.controlsState.longControlState = self.long_control.long_control_state if self.long_control is not None else (
LongCtrlState.pid if self.enabled else LongCtrlState.off)
ss.selfdriveState.experimentalMode = self.e2e
ss.selfdriveState.personality = self.personality
control.controlsState.forceDecel = self.force_decel
true_v_ego = self.speed
true_a_ego = self.acceleration
published_v_ego = true_v_ego
published_a_ego = true_a_ego if self.publish_realized_a_ego else 0.0
if self.ego_observation_fn is not None:
published_v_ego, published_a_ego = self.ego_observation_fn(self.current_time, true_v_ego, true_a_ego)
car_state.carState.vEgo = float(published_v_ego)
car_state.carState.aEgo = float(published_a_ego)
car_state.carState.standstill = bool(self.speed < 0.01)
car_state.carState.vCruise = float(v_cruise * 3.6)
car_control.carControl.orientationNED = [0.0, float(pitch), 0.0]
# ******** get controlsState messages for plotting ***
sm = PlannerSM(self.rk.frame, {
'radarState': radar.radarState,
'carState': car_state.carState,
'carControl': car_control.carControl,
'controlsState': control.controlsState,
'selfdriveState': ss.selfdriveState,
'vehicleParameters': vehicle_parameters.vehicleParameters,
'modelV2': model.modelV2,
'carStateSP': car_state_sp.carStateSP,
'liveMapDataSP': live_map_data_sp.liveMapDataSP,
'gpsLocation': gps_data.gpsLocation,
})
self.planner.update(sm)
self.a_target = self.planner.output_a_target
if self.long_control is None:
self.actuator_command = self.a_target
if self.planner.output_should_stop:
stopping_acceleration = -0.5 if self.actuator_model is None else self.actuator_model.stopping_acceleration
self.actuator_command = min(stopping_acceleration, self.actuator_command)
self._update_actuator(self.actuator_command)
self._integrate_ego(self.ts)
else:
for _ in range(round(self.ts / DT_CTRL)):
car_state.carState.vEgo = self.speed
car_state.carState.aEgo = self.acceleration
car_state.carState.standstill = self.speed < 0.01
self.actuator_command = self.long_control.update(
self.enabled, car_state.carState, self.a_target, self.planner.output_should_stop, (ACCEL_MIN, ACCEL_MAX),
)
self._update_actuator(self.actuator_command)
self._integrate_ego(DT_CTRL, stop_at_standstill=True)
self.should_stop = self.planner.output_should_stop
fcw = self.planner.fcw
self.distance_lead = self.distance_lead + v_lead * self.ts
# *** radar model ***
if self.lead_relevancy:
d_rel = np.maximum(0.0, self.distance_lead - self.distance)
v_rel = v_lead - self.speed
else:
d_rel = 200.0
v_rel = 0.0
# print at 5hz
# if (self.rk.frame % (self.rate // 5)) == 0:
# print("%2.2f sec %6.2f m %6.2f m/s %6.2f m/s2 lead_rel: %6.2f m %6.2f m/s"
# % (self.current_time, self.distance, self.speed, self.acceleration, d_rel, v_rel))
# ******** update prevs ********
self.rk.monitor_time()
accel_controller = self.planner.accel_controller
return {
"distance": self.distance,
"speed": self.speed,
"acceleration": self.acceleration,
"realized_acceleration": self.acceleration,
"a_target": self.a_target,
"actuator_command": self.actuator_command,
"published_a_ego": published_a_ego,
"published_v_ego": published_v_ego,
"should_stop": self.should_stop,
"long_control_state": (int(self.long_control.long_control_state) if self.long_control is not None
else control.controlsState.longControlState.raw),
"distance_lead": self.distance_lead,
"fcw": fcw,
"mpc_source": self.planner.mpc.source,
"dec_mode": self.planner.dec.mode(),
"controller_active": accel_controller.is_active,
"controller_accel_max": accel_controller.cruise_accel_max,
"controller_early_decel": accel_controller.early_decel,
"model_action": {
"desiredAcceleration": float(model_acceleration),
"shouldStop": bool(model_should_stop),
},
"truth_lead": dict(truth_lead),
"lead_one_observation": None if lead_one_observation is None else dict(lead_one_observation),
"lead_two_observation": None if lead_two_observation is None else dict(lead_two_observation),
}
@@ -1,166 +0,0 @@
from collections.abc import Callable
import math
from typing import cast
from openpilot.common.parameterized import parameterized
from openpilot.common.realtime import DT_MDL
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP
STOCK_STEP_KEYS = ("distance", "speed", "acceleration", "should_stop", "distance_lead", "fcw")
def departing_lead(current_time: float) -> float:
return 0.0 if current_time < 1.0 else min(2.0, 2.0 * (current_time - 1.0))
def stopped_lead(_current_time: float) -> float:
return 0.0
PARITY_SCENARIOS = {
"approach_stopped_lead": {"lead_relevancy": True, "speed": 15.0, "distance_lead": 60.0, "v_cruise": 20.0, "v_lead": stopped_lead, "steps": 80},
"stop_then_depart": {"lead_relevancy": True, "speed": 0.0, "distance_lead": 6.0, "v_cruise": 8.0, "v_lead": departing_lead, "steps": 120},
}
def _drive(cls, *, v_cruise: float, v_lead: Callable[[float], float], steps: int, **kwargs):
plant = cls(**kwargs)
plant.v_lead_prev = v_lead(0.0)
solver_failures = 0
original_reset = plant.planner.mpc.reset
def counting_reset(*args, **kw):
nonlocal solver_failures
if plant.planner.mpc.solution_status != 0:
solver_failures += 1
return original_reset(*args, **kw)
plant.planner.mpc.reset = counting_reset
results = []
for _ in range(steps):
lead_speed = v_lead(plant.current_time)
result = plant.step(v_lead=lead_speed, v_cruise=v_cruise)
results.append((result, plant.planner.mpc.source, plant.planner.output_a_target))
return results, solver_failures
class TestPlantSP(OpenpilotTestCase):
@parameterized.expand(PARITY_SCENARIOS, names=("scenario",), ids=lambda scenario: scenario)
def test_plant_sp_matches_stock_plant_on_shared_kwargs(self, scenario: str):
kwargs = dict(PARITY_SCENARIOS[scenario])
v_cruise = cast(float, kwargs.pop("v_cruise"))
v_lead = cast(Callable[[float], float], kwargs.pop("v_lead"))
steps = cast(int, kwargs.pop("steps"))
stock_results, stock_failures = _drive(Plant, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
sp_results, sp_failures = _drive(PlantSP, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
assert stock_failures == 0, f"stock Plant solver failed {stock_failures} times in {scenario!r}"
assert sp_failures == 0, f"PlantSP solver failed {sp_failures} times in {scenario!r}"
for frame, ((stock_result, stock_source, stock_a_target), (sp_result, sp_source, sp_a_target)) in enumerate(
zip(stock_results, sp_results, strict=True),
):
for key in STOCK_STEP_KEYS:
if isinstance(stock_result[key], float):
self.assertAlmostEqual(sp_result[key], stock_result[key], msg=f"{scenario} frame {frame} key {key}")
else:
assert sp_result[key] == stock_result[key], f"{scenario} frame {frame} key {key}"
assert sp_source == stock_source, f"{scenario} frame {frame} mpc.source"
self.assertAlmostEqual(sp_a_target, stock_a_target, msg=f"{scenario} frame {frame} output_a_target")
if scenario == "stop_then_depart":
departure_frame = round(1.0 / DT_MDL)
for results in (stock_results, sp_results):
assert all(result["speed"] < 0.01 for result, _, _ in results[:departure_frame])
assert results[departure_frame - 1][0]["should_stop"]
assert any(not result["should_stop"] for result, _, _ in results[departure_frame:])
assert any(result["speed"] > 0.05 for result, _, _ in results[departure_frame:])
stock_release = next(frame for frame, (result, _, _) in enumerate(stock_results)
if frame >= departure_frame and not result["should_stop"])
sp_release = next(frame for frame, (result, _, _) in enumerate(sp_results)
if frame >= departure_frame and not result["should_stop"])
stock_motion = next(frame for frame, (result, _, _) in enumerate(stock_results)
if frame >= departure_frame and result["speed"] > 0.05)
sp_motion = next(frame for frame, (result, _, _) in enumerate(sp_results)
if frame >= departure_frame and result["speed"] > 0.05)
assert sp_release == stock_release
assert sp_motion == stock_motion
def test_full_lead_observation_is_independent_from_truth(self):
callback_inputs = []
def observe_lead(current_time, lead_name, truth):
callback_inputs.append((current_time, lead_name, truth))
if lead_name == "leadOne":
return {
"dRel": 12.5,
"vRel": -4.0,
"vLead": 6.0,
"vLeadK": 5.5,
"aLeadK": -1.25,
"aLeadTau": 0.7,
"present": True,
"modelProb": 0.9,
"radarTrackId": 42,
}
return None
plant = PlantSP(lead_relevancy=True, speed=10.0, distance_lead=50.0, lead_observation_fn=observe_lead)
result = plant.step(v_lead=8.0)
assert [entry[1] for entry in callback_inputs] == ["leadOne", "leadTwo"]
self.assertAlmostEqual(callback_inputs[0][2]["dRel"], 50.0)
self.assertAlmostEqual(result["truth_lead"]["dRel"], 50.0)
self.assertAlmostEqual(result["lead_one_observation"]["dRel"], 12.5)
assert result["lead_one_observation"]["radarTrackId"] == 42
assert result["lead_two_observation"] is None
self.assertAlmostEqual(result["distance_lead"], 50.0 + 8.0 * DT_MDL)
def test_model_action_realized_acceleration_and_source_logging(self):
def model_action(current_time, v_ego, a_ego):
return -1.25, True
plant = PlantSP(speed=10.0, e2e=True, force_decel=True, model_action_fn=model_action, actuator_lag=0.5)
first = plant.step()
second = plant.step()
assert first["model_action"] == {"desiredAcceleration": -1.25, "shouldStop": True}
self.assertAlmostEqual(first["published_a_ego"], 0.0)
self.assertAlmostEqual(second["published_a_ego"], first["realized_acceleration"])
assert first["acceleration"] == first["realized_acceleration"]
assert abs(first["realized_acceleration"]) < abs(first["actuator_command"])
assert first["mpc_source"] is not None
assert first["dec_mode"] in ("acc", "blended")
assert "controller_active" in first
assert "controller_accel_max" in first
assert "controller_early_decel" in first
assert first["lead_one_observation"] is not None
assert first["truth_lead"] == first["lead_one_observation"]
def test_default_model_action_matches_stock_plant(self):
result = PlantSP(speed=10.0).step()
self.assertAlmostEqual(result["model_action"]["desiredAcceleration"], 0.5)
assert not result["model_action"]["shouldStop"]
def test_configurable_transport_delay_and_first_order_lag(self):
plant = PlantSP(speed=10.0, actuator_delay=2 * DT_MDL, actuator_lag=0.2)
self.assertAlmostEqual(plant.planner.CP.longitudinalActuatorDelay, 2 * DT_MDL)
delayed_commands = [plant._update_actuator(-1.0) for _ in range(3)]
assert [command for command, _ in delayed_commands[:2]] == [0.0, 0.0]
expected_acceleration = -(1.0 - math.exp(-DT_MDL / 0.2))
assert delayed_commands[2][0] == -1.0
self.assertAlmostEqual(delayed_commands[2][1], expected_acceleration)
@parameterized.expand(
[(-0.1, 0.0), (float("nan"), 0.0), (float("inf"), 0.0), (None, -0.1), (None, float("nan")), (None, float("inf"))],
names=("delay", "lag"),
)
def test_invalid_actuator_dynamics(self, delay, lag):
with self.assertRaises(ValueError):
PlantSP(actuator_delay=delay, actuator_lag=lag)
@@ -11,7 +11,6 @@ from opendbc.car.structs import car
from opendbc.car.hyundai.values import CAR as HYUNDAI_CAR, UNSUPPORTED_LONGITUDINAL_CAR
from opendbc.car.subaru.values import CAR as SUBARU_CAR, SubaruFlags
from opendbc.sunnypilot.car.tesla.values import TeslaFlagsSP
from opendbc.sunnypilot.car.toyota.values import ToyotaFlagsSP, VIRTUAL_CRUISE_SPEED_CAR
from openpilot.common.params import Params
from openpilot.common.swaglog import cloudlog
from openpilot.common.hardware import HARDWARE
@@ -20,7 +19,6 @@ from openpilot.common.hardware import HARDWARE
# Wire-protocol version for the capabilities payload. Bump on breaking changes
# only; additive fields are backward-compatible and do not require a bump.
PROTOCOL_VERSION = 1
TOYOTA_VIRTUAL_CRUISE_SPEED_PLATFORMS = {str(platform) for platform in VIRTUAL_CRUISE_SPEED_CAR}
# All capability fields that rules may reference.
# Non-boolean fields must have defaults in CAPABILITY_DEFAULTS.
@@ -44,7 +42,6 @@ CAPABILITY_FIELDS = (
"device_type",
"subaru_has_sng",
"hyundai_alpha_long_available",
"toyota_virtual_cruise_speed_available",
)
CAPABILITY_LABELS: dict[str, str] = {
@@ -67,7 +64,6 @@ CAPABILITY_LABELS: dict[str, str] = {
"device_type": "Device type",
"subaru_has_sng": "Subaru Stop-and-Go available",
"hyundai_alpha_long_available": "Hyundai Alpha Longitudinal available",
"toyota_virtual_cruise_speed_available": "Toyota Virtual Cruise Speed available",
}
# Explicit defaults for non-boolean capability fields
@@ -114,12 +110,6 @@ def _resolve_brand_capabilities(caps: dict, bundle_platform: str, CP) -> None:
caps["subaru_has_sng"] = not bool(CP.flags & (SubaruFlags.GLOBAL_GEN2 | SubaruFlags.HYBRID))
caps["has_stop_and_go"] = caps["subaru_has_sng"]
elif brand == "toyota":
if bundle_platform:
caps["toyota_virtual_cruise_speed_available"] = bundle_platform in TOYOTA_VIRTUAL_CRUISE_SPEED_PLATFORMS
elif CP is not None:
caps["toyota_virtual_cruise_speed_available"] = str(CP.carFingerprint) in TOYOTA_VIRTUAL_CRUISE_SPEED_PLATFORMS
def generate_capabilities(params: Params | None = None) -> dict:
"""Generate a SettingsCapabilities dict from CarParams + boolean params.
@@ -184,8 +174,6 @@ def generate_capabilities(params: Params | None = None) -> dict:
caps["icbm_available"] = bool(CP_SP.intelligentCruiseButtonManagementAvailable)
caps["has_icbm"] = bool(CP_SP.intelligentCruiseButtonManagementAvailable) and params.get_bool("IntelligentCruiseButtonManagement")
caps["tesla_has_vehicle_bus"] = bool(CP_SP.flags & TeslaFlagsSP.HAS_VEHICLE_BUS)
if caps["brand"] == "toyota":
caps["toyota_virtual_cruise_speed_available"] = bool(CP_SP.flags & ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE)
except Exception:
cloudlog.exception("capabilities: failed to deserialize CarParamsSPPersistent")
@@ -652,58 +652,6 @@
}
]
},
{
"key": "AccelPersonalityEnabled",
"widget": "toggle",
"title": "Enable Accel Controller",
"description": "Begin slowing early and smoothly behind lead vehicles. Stock longitudinal control retains braking and stopping authority.",
"visibility": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
}
],
"enablement": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
}
]
},
{
"key": "AccelPersonality",
"widget": "multiple_button",
"title": "Acceleration Profile",
"description": "Eco slows earliest and recovers gently, Normal balances comfort and response, and Sport reacts and recovers more quickly.",
"options": [
{
"value": 0,
"label": "Eco"
},
{
"value": 1,
"label": "Normal"
},
{
"value": 2,
"label": "Sport"
}
],
"enablement": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
},
{
"type": "param",
"key": "AccelPersonalityEnabled",
"equals": true
}
]
},
{
"key": "IntelligentCruiseButtonManagement",
"widget": "toggle",
@@ -764,21 +712,6 @@
"type": "capability",
"field": "has_icbm",
"equals": true
},
{
"type": "all",
"conditions": [
{
"type": "capability",
"field": "toyota_virtual_cruise_speed_available",
"equals": true
},
{
"type": "param",
"key": "ToyotaVirtualCruiseSpeed",
"equals": true
}
]
}
]
}
@@ -817,21 +750,6 @@
"type": "capability",
"field": "has_icbm",
"equals": true
},
{
"type": "all",
"conditions": [
{
"type": "capability",
"field": "toyota_virtual_cruise_speed_available",
"equals": true
},
{
"type": "param",
"key": "ToyotaVirtualCruiseSpeed",
"equals": true
}
]
}
]
}
@@ -2176,22 +2094,6 @@
"equals": true
}
]
},
{
"key": "PlanplusControl",
"widget": "option",
"title": "Plan Plus Controls",
"description": "Adjust planplus model recentering strength. The higher this number the more aggressively the model will recover to lane center; too high and it will ping-pong.",
"min": 0.0,
"max": 2.0,
"step": 0.1,
"enablement": [
{
"type": "param",
"key": "ShowAdvancedControls",
"equals": true
}
]
}
]
},
@@ -2400,50 +2302,6 @@
"title": "Toyota / Lexus Settings",
"description": "",
"items": [
{
"key": "ToyotaAutoHold",
"widget": "toggle",
"needs_onroad_cycle": true,
"title": "Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS",
"enablement": [
{
"type": "not_engaged"
}
]
},
{
"key": "ToyotaEnhancedBsm",
"widget": "toggle",
"needs_onroad_cycle": true,
"title": "Toyota: Prius TSS2 BSM and some tssp",
"enablement": [
{
"type": "not_engaged"
}
]
},
{
"key": "ToyotaTSS2Long",
"widget": "toggle",
"needs_onroad_cycle": true,
"title": "Toyota: custom longitudinal for TSS2",
"enablement": [
{
"type": "not_engaged"
}
]
},
{
"key": "ToyotaDriveMode",
"widget": "toggle",
"needs_onroad_cycle": true,
"title": "Enable drive mode btn link",
"enablement": [
{
"type": "not_engaged"
}
]
},
{
"key": "ToyotaEnforceStockLongitudinal",
"widget": "toggle",
@@ -2453,40 +2311,6 @@
"enablement": [
{
"type": "not_engaged"
},
{
"type": "param",
"key": "ToyotaVirtualCruiseSpeed",
"equals": false
}
]
},
{
"key": "ToyotaVirtualCruiseSpeed",
"widget": "toggle",
"needs_onroad_cycle": true,
"title": "Toyota: Virtual Cruise Speed (Alpha)",
"description": "Uses a sunnypilot-owned cruise target with the Toyota RES/SET buttons and unlocks Custom ACC Speed Intervals. Set the short interval to 5 for next-5-unit tap behavior. The Toyota cluster continues to show the factory target and may differ from sunnypilot. The direct button signals are route-validated on Corolla Cross and Prius TSS2, but held-button timing differs by platform. Validate acceleration above the factory target in a controlled setting.",
"visibility": [
{
"type": "capability",
"field": "toyota_virtual_cruise_speed_available",
"equals": true
}
],
"enablement": [
{
"type": "not_engaged"
},
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
},
{
"type": "param",
"key": "ToyotaEnforceStockLongitudinal",
"equals": false
}
]
},
@@ -43,32 +43,6 @@ sections:
label: Relaxed
enablement:
- $ref: '#/macros/longitudinal'
- key: AccelPersonalityEnabled
widget: toggle
title: Enable Accel Controller
description: Begin slowing early and smoothly behind lead vehicles. Stock longitudinal control retains braking
and stopping authority.
visibility:
- $ref: '#/macros/longitudinal'
enablement:
- $ref: '#/macros/longitudinal'
- key: AccelPersonality
widget: multiple_button
title: Acceleration Profile
description: Eco slows earliest and recovers gently, Normal balances comfort and response, and Sport reacts
and recovers more quickly.
options:
- value: 0
label: Eco
- value: 1
label: Normal
- value: 2
label: Sport
enablement:
- $ref: '#/macros/longitudinal'
- type: param
key: AccelPersonalityEnabled
equals: true
- key: IntelligentCruiseButtonManagement
widget: toggle
title: Intelligent Cruise Button Management (ICBM) (Alpha)
@@ -103,14 +77,6 @@ sections:
- type: capability
field: has_icbm
equals: true
- type: all
conditions:
- type: capability
field: toyota_virtual_cruise_speed_available
equals: true
- type: param
key: ToyotaVirtualCruiseSpeed
equals: true
items:
- key: CustomAccIncrementsEnabled
widget: toggle
@@ -132,14 +98,6 @@ sections:
- type: capability
field: has_icbm
equals: true
- type: all
conditions:
- type: capability
field: toyota_virtual_cruise_speed_available
equals: true
- type: param
key: ToyotaVirtualCruiseSpeed
equals: true
sub_panels:
- id: custom_acc_intervals
label: Custom ACC Speed Intervals Settings
@@ -51,16 +51,6 @@ sections:
key: LagdToggle
equals: true
- $ref: '#/macros/advanced_only'
- key: PlanplusControl
widget: option
title: Plan Plus Controls
description: Adjust planplus model recentering strength. The higher this number the more aggressively the model will recover
to lane center; too high and it will ping-pong.
min: 0.0
max: 2.0
step: 0.1
enablement:
- $ref: '#/macros/advanced_only'
- id: lateral_control
title: Lateral Control
description: Neural network lateral control for supported models
@@ -82,30 +82,6 @@ sections:
title: Toyota / Lexus Settings
description: ''
items:
- key: ToyotaAutoHold
widget: toggle
needs_onroad_cycle: true
title: 'Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS'
enablement:
- $ref: '#/macros/not_engaged'
- key: ToyotaEnhancedBsm
widget: toggle
needs_onroad_cycle: true
title: 'Toyota: Prius TSS2 BSM and some tssp'
enablement:
- $ref: '#/macros/not_engaged'
- key: ToyotaTSS2Long
widget: toggle
needs_onroad_cycle: true
title: 'Toyota: custom longitudinal for TSS2'
enablement:
- $ref: '#/macros/not_engaged'
- key: ToyotaDriveMode
widget: toggle
needs_onroad_cycle: true
title: Enable drive mode btn link
enablement:
- $ref: '#/macros/not_engaged'
- key: ToyotaEnforceStockLongitudinal
widget: toggle
needs_onroad_cycle: true
@@ -113,28 +89,6 @@ sections:
description: sunnypilot will not take over control of gas and brakes. Factory Toyota longitudinal control will be used.
enablement:
- $ref: '#/macros/not_engaged'
- type: param
key: ToyotaVirtualCruiseSpeed
equals: false
- key: ToyotaVirtualCruiseSpeed
widget: toggle
needs_onroad_cycle: true
title: 'Toyota: Virtual Cruise Speed (Alpha)'
description: Uses a sunnypilot-owned cruise target with the Toyota RES/SET buttons and unlocks Custom ACC Speed
Intervals. Set the short interval to 5 for next-5-unit tap behavior. The Toyota cluster continues to show the
factory target and may differ from sunnypilot. The direct button signals are route-validated on Corolla Cross
and Prius TSS2, but held-button timing differs by platform. Validate acceleration above the factory target in a
controlled setting.
visibility:
- type: capability
field: toyota_virtual_cruise_speed_available
equals: true
enablement:
- $ref: '#/macros/not_engaged'
- $ref: '#/macros/longitudinal'
- type: param
key: ToyotaEnforceStockLongitudinal
equals: false
- key: ToyotaStopAndGoHack
widget: toggle
needs_onroad_cycle: true
@@ -10,18 +10,9 @@ change and must be intentional. KNOWN_PROTOCOL_VERSIONS pins the set we
explicitly support when the constant is bumped, this list must be edited in
the same commit so the bump shows up in code review.
"""
from __future__ import annotations
from typing import cast
from openpilot.cereal import custom
from openpilot.common.params import Params
from openpilot.common.parameterized import parameterized
from openpilot.common.test import OpenpilotTestCase
from opendbc.car.structs import car
from opendbc.car.toyota.values import CAR as TOYOTA_CAR
from opendbc.sunnypilot.car.toyota.values import ToyotaFlagsSP
from openpilot.sunnypilot.sunnylink.capabilities import (
CAPABILITY_DEFAULTS,
CAPABILITY_FIELDS,
@@ -29,41 +20,13 @@ from openpilot.sunnypilot.sunnylink.capabilities import (
PROTOCOL_VERSION,
generate_capabilities,
)
from openpilot.common.test import OpenpilotTestCase
KNOWN_PROTOCOL_VERSIONS = (1,)
LATEST_KNOWN = max(KNOWN_PROTOCOL_VERSIONS)
class FakeParams:
def __init__(self, values=None):
self.values = values or {}
def get(self, key, *args, **kwargs):
return self.values.get(key)
def get_bool(self, key):
return bool(self.values.get(key, False))
def build_persistent_toyota_params(platform, *, sp_flags=0) -> Params:
CP = car.CarParams.new_message()
CP.brand = "toyota"
CP.carFingerprint = str(platform)
CP.pcmCruise = True
CP.openpilotLongitudinalControl = True
CP_SP = custom.CarParamsSP.new_message()
CP_SP.flags = int(sp_flags)
return cast(Params, FakeParams(
{
"CarParamsPersistent": CP.to_bytes(),
"CarParamsSPPersistent": CP_SP.to_bytes(),
}
))
def caps():
return generate_capabilities()
@@ -89,12 +52,14 @@ class TestProtocolVersion(OpenpilotTestCase):
def test_protocol_version_is_known(self):
"""Sentinel against accidental bumps. Edit KNOWN_PROTOCOL_VERSIONS if intentional."""
assert PROTOCOL_VERSION in KNOWN_PROTOCOL_VERSIONS, (
f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. "
+ "If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. " +
"If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
)
def test_protocol_version_matches_latest_known(self):
assert PROTOCOL_VERSION == LATEST_KNOWN, "Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
assert PROTOCOL_VERSION == LATEST_KNOWN, (
"Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
)
class TestOpaquePerBrandFlags(OpenpilotTestCase):
@@ -111,66 +76,6 @@ class TestOpaquePerBrandFlags(OpenpilotTestCase):
assert caps["hyundai_alpha_long_available"] is False
class TestToyotaVirtualCruiseSpeedCapability(OpenpilotTestCase):
def test_field_present_and_labeled(self):
assert "toyota_virtual_cruise_speed_available" in CAPABILITY_FIELDS
assert "toyota_virtual_cruise_speed_available" in CAPABILITY_LABELS
def test_default_false(self):
caps = generate_capabilities(cast(Params, FakeParams()))
assert caps["toyota_virtual_cruise_speed_available"] is False
@parameterized.expand(
(
(TOYOTA_CAR.TOYOTA_COROLLA_TSS2, True),
(TOYOTA_CAR.TOYOTA_PRIUS_TSS2, True),
(TOYOTA_CAR.TOYOTA_RAV4_TSS2, False),
)
)
def test_bundle_platform_gating(self, platform, expected):
params = FakeParams(
{
"CarPlatformBundle": {
"brand": "toyota",
"platform": str(platform),
},
}
)
caps = generate_capabilities(cast(Params, params))
assert caps["toyota_virtual_cruise_speed_available"] is expected
@parameterized.expand(
(
(TOYOTA_CAR.TOYOTA_COROLLA_TSS2, ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE, True),
(TOYOTA_CAR.TOYOTA_COROLLA_TSS2, 0, True),
(TOYOTA_CAR.TOYOTA_PRIUS_TSS2, ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE, True),
(TOYOTA_CAR.TOYOTA_PRIUS_TSS2, 0, True),
(TOYOTA_CAR.TOYOTA_RAV4_TSS2, ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE, False),
)
)
def test_persistent_car_params_platform_gating(self, platform, sp_flags, expected):
caps = generate_capabilities(build_persistent_toyota_params(platform, sp_flags=sp_flags))
assert caps["toyota_virtual_cruise_speed_available"] is expected
@parameterized.expand(
(
(TOYOTA_CAR.TOYOTA_COROLLA_TSS2, TOYOTA_CAR.TOYOTA_RAV4_TSS2, True),
(TOYOTA_CAR.TOYOTA_PRIUS_TSS2, TOYOTA_CAR.TOYOTA_RAV4_TSS2, True),
(TOYOTA_CAR.TOYOTA_RAV4_TSS2, TOYOTA_CAR.TOYOTA_COROLLA_TSS2, False),
(TOYOTA_CAR.TOYOTA_RAV4_TSS2, TOYOTA_CAR.TOYOTA_PRIUS_TSS2, False),
)
)
def test_bundle_platform_takes_precedence_over_stale_persistent_params(self, bundle_platform, persistent_platform, expected):
params = build_persistent_toyota_params(persistent_platform, sp_flags=ToyotaFlagsSP.VIRTUAL_CRUISE_SPEED_AVAILABLE)
params.values["CarPlatformBundle"] = {
"brand": "toyota",
"platform": str(bundle_platform),
}
caps = generate_capabilities(params)
assert caps["toyota_virtual_cruise_speed_available"] is expected
class TestCapabilitiesShape(OpenpilotTestCase):
def test_all_fields_present(self, caps):
for field in CAPABILITY_FIELDS:
@@ -9,7 +9,6 @@ isolates one of the gating bugs that the design-overhaul branch fixes so a
future regression is loud and obvious. These tests are intentionally narrow
and additive they do not replace the broader test_settings_schema.py.
"""
from __future__ import annotations
import json
@@ -25,13 +24,14 @@ from openpilot.sunnypilot.sunnylink.tools.generate_settings_schema import (
_load_torque_versions,
generate_schema,
)
from openpilot.sunnypilot.sunnylink.tools.validate_settings_ui import validate as validate_settings_ui
from openpilot.common.test import OpenpilotTestCase
SCHEMA_VALIDATOR_PATH = os.path.join(os.path.dirname(DEFINITION_PATH), "settings_ui.schema.json")
def _walk_items(schema: dict[str, Any]):
"""Yield every item dict from the schema."""
def _yield(item: dict[str, Any]):
yield item
for sub in item.get("sub_items", []):
@@ -106,26 +106,6 @@ def _references_capability_field(rules: list[dict[str, Any]] | None, field: str)
return found
def _has_toyota_virtual_cruise_gate(rules: list[dict[str, Any]] | None) -> bool:
def _walk(rule: dict[str, Any]) -> bool:
if rule.get("type") == "all":
conditions = rule.get("conditions", [])
has_capability = any(
c.get("type") == "capability" and c.get("field") == "toyota_virtual_cruise_speed_available" and c.get("equals") is True for c in conditions
)
has_param = any(c.get("type") == "param" and c.get("key") == "ToyotaVirtualCruiseSpeed" and c.get("equals") is True for c in conditions)
if has_capability and has_param:
return True
if rule.get("type") == "not" and "condition" in rule:
return _walk(rule["condition"])
if rule.get("type") in ("any", "all"):
return any(_walk(c) for c in rule.get("conditions", []))
return False
return any(_walk(rule) for rule in rules or [])
def schema():
return generate_schema()
@@ -169,13 +149,22 @@ class TestTestManeuversSection(OpenpilotTestCase):
assert "is_sp_release" in vis_refs
enablement = section.get("enablement") or []
enable_refs = json.dumps(enablement)
assert "ShowAdvancedControls" in enable_refs, "test_maneuvers must gate ShowAdvancedControls via enablement"
assert "ShowAdvancedControls" in enable_refs, \
"test_maneuvers must gate ShowAdvancedControls via enablement"
class TestValidator(OpenpilotTestCase):
def test_validator_accepts_real_json(self):
"""settings_ui.json passes the repository's production schema validator."""
self.assertTrue(validate_settings_ui(DEFINITION_PATH))
"""settings_ui.json validates against settings_ui.schema.json."""
try:
import jsonschema
except ImportError:
self.skipTest("jsonschema not installed")
with open(DEFINITION_PATH) as f:
data = json.load(f)
with open(SCHEMA_VALIDATOR_PATH) as f:
validator = json.load(f)
jsonschema.validate(instance=data, schema=validator)
class TestTorqueOptionGeneration(OpenpilotTestCase):
@@ -188,17 +177,16 @@ class TestTorqueOptionGeneration(OpenpilotTestCase):
assert item.get("options") == expected
def test_torque_versions_path_resolves(self):
assert os.path.exists(TORQUE_VERSIONS_PATH), f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
assert os.path.exists(TORQUE_VERSIONS_PATH), (
f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
)
class TestReleaseBranchGates(OpenpilotTestCase):
@parameterized.expand(
[
"EnableGithubRunner",
"QuickBootToggle",
],
names=["key"],
)
@parameterized.expand([
"EnableGithubRunner",
"QuickBootToggle",
], names=["key"])
def test_sp_dev_items_gate_on_is_sp_release(self, schema, key):
"""sunnypilot dev items must hide on sunnypilot release branches (is_sp_release gate)."""
item = _find_item(schema, key)
@@ -220,14 +208,11 @@ class TestSpuriousOffroadGatesDropped(OpenpilotTestCase):
class TestNotEngagedReplacement(OpenpilotTestCase):
@parameterized.expand(
[
"AlphaLongitudinalEnabled",
"ToyotaEnforceStockLongitudinal",
"ToyotaStopAndGoHack",
],
names=["key"],
)
@parameterized.expand([
"AlphaLongitudinalEnabled",
"ToyotaEnforceStockLongitudinal",
"ToyotaStopAndGoHack",
], names=["key"])
def test_offroad_only_replaced_with_not_engaged(self, schema, key):
"""These items should use not_engaged, not offroad_only."""
item = _find_item(schema, key)
@@ -235,25 +220,3 @@ class TestNotEngagedReplacement(OpenpilotTestCase):
rule_types = _flatten_rule_types(item.get("enablement"))
assert "offroad_only" not in rule_types, f"{key} still uses offroad_only"
assert "not_engaged" in rule_types, f"{key} missing not_engaged"
class TestToyotaVirtualCruiseSpeed(OpenpilotTestCase):
def test_vehicle_toggle_contract(self, schema):
toyota = schema["vehicle_settings"]["toyota"]
item = next((item for item in toyota["items"] if item.get("key") == "ToyotaVirtualCruiseSpeed"), None)
assert item is not None
assert item["widget"] == "toggle"
assert item.get("needs_onroad_cycle") is True
assert _references_capability_field(item.get("visibility"), "toyota_virtual_cruise_speed_available")
assert _references_capability_field(item.get("enablement"), "has_longitudinal_control")
assert "not_engaged" in _flatten_rule_types(item.get("enablement"))
def test_custom_acc_section_links_virtual_cruise_opt_in(self, schema):
section = _find_section(schema, "cruise", "custom_acc_increments")
assert section is not None
assert _has_toyota_virtual_cruise_gate(section.get("enablement"))
item = _find_item(schema, "CustomAccIncrementsEnabled")
assert item is not None
assert _has_toyota_virtual_cruise_gate(item.get("enablement"))
@@ -276,33 +276,16 @@ class TestKnownPanels(OpenpilotTestCase):
enhanced_enable_keys = {r.get("key") for r in enhanced.get("enablement", []) if r.get("type") == "param"}
assert "NeuralNetworkLateralControl" in enhanced_enable_keys
def test_accel_controller_profile_mapping_and_enablement(self, schema):
cruise = next(p for p in schema["panels"] if p["id"] == "cruise")
items = {item["key"]: item for item in _iter_panel_items(cruise)}
assert items["AccelPersonalityEnabled"]["widget"] == "toggle"
assert items["AccelPersonality"]["options"] == [
{"value": 0, "label": "Eco"},
{"value": 1, "label": "Normal"},
{"value": 2, "label": "Sport"},
]
assert {
"type": "param",
"key": "AccelPersonalityEnabled",
"equals": True,
} in items["AccelPersonality"]["enablement"]
class TestKnownVehicleSettings(OpenpilotTestCase):
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
def test_toyota_has_enforce_stock_stop_go_and_virtual_cruise(self, schema):
def test_toyota_has_enforce_stock_and_stop_go(self, schema):
keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("toyota"))}
assert "ToyotaEnforceStockLongitudinal" in keys
assert "ToyotaStopAndGoHack" in keys
assert "ToyotaVirtualCruiseSpeed" in keys
def test_tesla_has_coop_steering(self, schema):
keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("tesla"))}
+1 -18
View File
@@ -45,9 +45,8 @@ class ScrollState(Enum):
class GuiScrollPanel2:
def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
def __init__(self, horizontal: bool = True) -> None:
self._horizontal = horizontal
self._handle_out_of_bounds = handle_out_of_bounds
self._state = ScrollState.STEADY
self._offset: rl.Vector2 = rl.Vector2(0, 0)
self._initial_click_event: MouseEvent | None = None
@@ -86,20 +85,6 @@ class GuiScrollPanel2:
"""Returns (max_offset, min_offset) for the given bounds and content size."""
return 0.0, min(0.0, bounds_size - content_size)
def _clamp_offset(self, bounds_size: float, content_size: float) -> None:
if self._handle_out_of_bounds:
return
max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
offset = self.get_offset()
clamped_offset = max(min_offset, min(max_offset, offset))
if clamped_offset == offset:
return
self.set_offset(clamped_offset)
if (clamped_offset == max_offset and self._velocity > 0) or (clamped_offset == min_offset and self._velocity < 0):
self._velocity = 0.0
def _update_state(self, bounds_size: float, content_size: float, snap_target: float | None) -> None:
"""Runs per render frame, independent of mouse events. Updates auto-scrolling state and velocity."""
max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
@@ -153,8 +138,6 @@ class GuiScrollPanel2:
factor = 1.0 - math.exp(-SNAP_RATE * dt)
self.set_offset(self.get_offset() + dist * factor)
self._clamp_offset(bounds_size, content_size)
def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
content_size: float) -> None:
max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
+3 -10
View File
@@ -75,6 +75,7 @@ class _Scroller(Widget):
self._items: list[Widget] = []
self._horizontal = horizontal
self._snap_items = snap_items
assert not self._snap_items or self._horizontal, "Snapping is only supported for horizontal scrolling"
self._spacing = spacing
self._pad = pad
@@ -190,20 +191,12 @@ class _Scroller(Widget):
snap_target: float | None = None
if self._snap_items and visible_items and self._scrolling_to[0] is None:
# TODO: this doesn't handle two small buttons at the edges well
center_pos = (self._rect.x + self._rect.width / 2) if self._horizontal else (self._rect.y + self._rect.height / 2)
closest_delta_pos = min(
(self._item_center_pos(item) - center_pos for item in visible_items),
key=abs,
)
center_pos = self._rect.x + self._rect.width / 2
closest_delta_pos = min((((item.rect.x + item.rect.width / 2) - center_pos) for item in visible_items), key=abs)
snap_target = self.scroll_panel.get_offset() - closest_delta_pos
return self.scroll_panel.update(self._rect, content_size, snap_target=snap_target)
def _item_center_pos(self, item: Widget) -> float:
if self._horizontal:
return item.rect.x + item.rect.width / 2
return item.rect.y + item.rect.height / 2
@property
def moving_items(self) -> bool:
return len(self._move_animations) > 0 or len(self._move_lift) > 0
File diff suppressed because it is too large Load Diff
File diff suppressed because one or more lines are too long