remove realized frame

models: remove tg_occupancy_opt
modeld_v2: one dev warp and enqueue (#1990 )
2026-09-06 01:13:42 +08:00 · 2026-09-05 09:53:04 -07:00 · 2026-09-05 07:28:37 -07:00 · 2026-09-04 21:15:00 -07:00 · 2026-09-05 10:50:12 +08:00 · 2026-09-04 16:52:09 -07:00
199 changed files with 2884 additions and 6472 deletions
@@ -9,7 +9,6 @@
 *.ttf filter=lfs diff=lfs merge=lfs -text
 *.otf filter=lfs diff=lfs merge=lfs -text
 *.wav filter=lfs diff=lfs merge=lfs -text
-openpilot/selfdrive/assets/sounds/milestone.wav -filter -diff -merge -text

 openpilot/selfdrive/car/tests/test_models_segs.txt filter=lfs diff=lfs merge=lfs -text
 openpilot/common/hardware/comma/updater filter=lfs diff=lfs merge=lfs -text
@@ -1,11 +0,0 @@
-*       @sunnypilot/dev-internal
-/.github/ @devtekve @sunnyhaibin
-/release/ci/ @devtekve @sunnyhaibin
-/tinygrad_repo @devtekve @Discountchubbs
-/tinygrad/ @devtekve @Discountchubbs
-/selfdrive/controls/lib/longitudinal_planner.py @devtekve @Discountchubbs
-/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py @devtekve @Discountchubbs
-/selfdrive/modeld/ @devtekve @Discountchubbs
-/sunnypilot/model* @devtekve @Discountchubbs
-/sunnypilot/sunnylink/ @devtekve
-/system/athena/ @devtekve
@@ -78,6 +78,7 @@ jobs:
      - name: Get next recompiled dir number
        id: create-recompiled-dir
        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
          HF_REPO: ${{ github.event.inputs.hf_repo }}
        run: |
          pip install huggingface_hub
@@ -30,6 +30,7 @@ jobs:
    runs-on: ubuntu-24.04
    outputs:
      model_name: ${{ steps.resolve.outputs.model_name }}
+      safe_model_name: ${{ steps.resolve.outputs.safe_model_name }}
      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
@@ -64,7 +65,9 @@ jobs:
            exit 1
          fi

+          SAFE_NAME="${NAME// /-}"
          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
+          echo "safe_model_name=${SAFE_NAME}" >> $GITHUB_OUTPUT
          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
@@ -135,7 +138,7 @@ jobs:

      - name: Prepare output
        env:
-          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
        run: |
          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
          export PYTHONPATH=${{ github.workspace }}
@@ -158,13 +161,13 @@ jobs:
      - name: Upload small model artifact
        uses: actions/upload-artifact@v4
        with:
-          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
          path: ${{ github.workspace }}/small_output/

      - name: Upload artifact name file
        uses: actions/upload-artifact@v4
        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
          path: ${{ github.workspace }}/small_output/artifact_name.txt

      - name: Re-enable powersave
@@ -254,7 +257,7 @@ jobs:

      - name: Prepare output
        env:
-          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
        run: |
          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
          export PYTHONPATH=${{ github.workspace }}
@@ -277,13 +280,13 @@ jobs:
      - name: Upload big model artifact
        uses: actions/upload-artifact@v4
        with:
-          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
          path: ${{ github.workspace }}/big_output/

      - name: Upload artifact name file
        uses: actions/upload-artifact@v4
        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
          path: ${{ github.workspace }}/big_output/artifact_name.txt

      - name: Re-enable powersave
@@ -318,7 +321,7 @@ jobs:
        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
        uses: actions/download-artifact@v4
        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
          path: artifact_name

      - name: Read artifact name
@@ -338,7 +341,7 @@ jobs:
      - name: Upload model to HF
        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
        run: |
          rm -f output/artifact_name.txt
@@ -364,7 +367,7 @@ jobs:
      - name: Generate DM metadata and upload to HF
        if: ${{ inputs.target == 'dm' }}
        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
        run: |
          export PYTHONPATH=$(pwd)
          python3 -c "
@@ -481,11 +484,29 @@ jobs:
          print(f'Chunked {pkl} into {len(targets)} chunks')
          "

+      - name: Compile DM warp
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
+
+          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
+          MODEL_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld"
+          DM_SIZE=$(python3 -c "from openpilot.common.transformations.model import DM_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
+
+          for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
+            WARP_PKL="${MODEL_DIR}/models/dm_warp_${res}_tinygrad.pkl"
+            taskset -c 7 env ${TG_FLAGS} python3 ${MODEL_DIR}/compile_dm_warp.py \
+              --camera-resolution ${res} \
+              --warp-to ${DM_SIZE} \
+              --output ${WARP_PKL}
+          done
+
      - name: Prepare DM output
        run: |
          mkdir -p dm_output
          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
+          cp ${{ github.workspace }}/openpilot/selfdrive/modeld/models/dm_warp_* dm_output/

      - name: Upload DM artifact
        uses: actions/upload-artifact@v4
@@ -146,7 +146,7 @@ jobs:

      - name: Validate hf_repo and JSON version
        env:
-          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
        run: |
          if [ ! -f "$JSON_FILE" ]; then
            echo "JSON file $JSON_FILE does not exist!"
@@ -155,13 +155,8 @@ jobs:
          python3 -c "
          import sys
          from huggingface_hub import HfApi
-          try:
-              api = HfApi()
-              api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
-              print(f'Success: Repo {sys.argv[1]} exists.')
-          except Exception as e:
-              print('HF validation failed:', e)
-              sys.exit(1)
+          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
+          print(f'Success: Repo {sys.argv[1]} exists.')
          " "${{ inputs.hf_repo }}"

      - name: Download artifact name file
@@ -192,7 +187,7 @@ jobs:

      - name: Upload to Hugging Face
        env:
-          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
          ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
        run: |
          hf upload ${{ inputs.hf_repo }} \
@@ -46,6 +46,13 @@ runs:
            printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}.chunk${CHUNK_IDX}" >> "$DOWNLOAD_LIST"
          done < <(echo "$ARTIFACT" | jq -r '.chunks[].file_name')
          echo "$NUM_CHUNKS" > "${DEST_DIR}/${CANONICAL}.chunkmanifest"
+
+          if [ "$CANONICAL" = "dmonitoring_model_tinygrad.pkl" ]; then
+            for warp in dm_warp_1928x1208_tinygrad.pkl dm_warp_1344x760_tinygrad.pkl; do
+              ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${warp}', safe=':/'))")
+              printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${warp}" >> "$DOWNLOAD_LIST"
+            done
+          fi
        }

        echo "$MODELS_JSON" | jq -c '.[]' | while IFS= read -r model; do
@@ -188,7 +188,7 @@ jobs:
          if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
            echo "CHESTNUT build"
            export CHESTNUT=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
            OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
          else
            echo "QCOM build"
@@ -216,6 +216,9 @@ jobs:
    needs: [ prepare_strategy ]
    runs-on: ubuntu-24.04
    if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
+    concurrency:
+      group: prepare-chestnut
+      cancel-in-progress: false
    outputs:
      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
    env:
@@ -228,8 +231,10 @@ jobs:
        run: |
          REF="${{ github.head_ref || github.ref_name }}"

-          ONNX_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.sha')
+          ONNX_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
          echo "ONNX hash: $ONNX_HASH"
+          [ -n "$ONNX_HASH" ] || { echo "::error::Failed to extract ONNX hash"; exit 1; }
          echo "onnx_sha256=$ONNX_HASH" >> $GITHUB_OUTPUT

          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
@@ -238,7 +243,7 @@ jobs:
          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"

          check_defaults() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
            [ "$TINYGRAD_MATCH" = "true" ] || return 1
            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
@@ -252,18 +257,35 @@ jobs:

          echo "No matching model on HF — dispatching build"
          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
+          sleep 10

-          echo "Polling HF for big model availability..."
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
          for i in $(seq 1 90); do
            sleep 30
-            if check_defaults; then
-              echo "Big model available on HF after $((i * 30))s"
-              exit 0
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/90: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Big model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
            fi
-            echo "Poll $i/90: not yet available"
          done

-          echo "::error::Big model not available on HF after 45 minutes"
+          echo "::error::Build run did not complete within 45 minutes"
          exit 1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -277,6 +299,9 @@ jobs:
  prepare_small_model:
    needs: [ prepare_strategy ]
    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-small-model
+      cancel-in-progress: false
    outputs:
      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
    env:
@@ -289,8 +314,10 @@ jobs:
        run: |
          REF="${{ github.head_ref || github.ref_name }}"

-          DRIVING_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.sha')
+          DRIVING_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
          echo "Driving ONNX hash: $DRIVING_HASH"
+          [ -n "$DRIVING_HASH" ] || { echo "::error::Failed to extract driving ONNX hash"; exit 1; }
          echo "driving_onnx_sha256=$DRIVING_HASH" >> $GITHUB_OUTPUT

          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
@@ -299,7 +326,7 @@ jobs:
          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"

          check_defaults() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
            [ "$TINYGRAD_MATCH" = "true" ] || return 1
            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
@@ -313,18 +340,35 @@ jobs:

          echo "No matching model on HF — dispatching build"
          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
+          sleep 10

-          echo "Polling HF for model availability..."
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
          for i in $(seq 1 60); do
            sleep 30
-            if check_defaults; then
-              echo "Model available on HF after $((i * 30))s"
-              exit 0
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "Small model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
            fi
-            echo "Poll $i/60: not yet available"
          done

-          echo "::error::Small driving model not available on HF after 30 minutes"
+          echo "::error::Small model build did not complete within 30 minutes"
          exit 1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -338,6 +382,9 @@ jobs:
  prepare_dm_model:
    needs: [ prepare_strategy ]
    runs-on: ubuntu-24.04
+    concurrency:
+      group: prepare-dm-model
+      cancel-in-progress: false
    outputs:
      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
    env:
@@ -350,8 +397,10 @@ jobs:
        run: |
          REF="${{ github.head_ref || github.ref_name }}"

-          DM_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
+          BLOB_SHA=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.sha')
+          DM_HASH=$(gh api "repos/${GH_REPO}/git/blobs/${BLOB_SHA}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
          echo "DM ONNX hash: $DM_HASH"
+          [ -n "$DM_HASH" ] || { echo "::error::Failed to extract DM ONNX hash"; exit 1; }
          echo "dm_onnx_sha256=$DM_HASH" >> $GITHUB_OUTPUT

          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
@@ -360,7 +409,7 @@ jobs:
          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"

          check_defaults() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
            [ "$TINYGRAD_MATCH" = "true" ] || return 1
            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
@@ -374,18 +423,35 @@ jobs:

          echo "No matching DM model on HF — dispatching build"
          gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
+          sleep 10

-          echo "Polling HF for DM model availability..."
+          BUILD_RUN_ID=$(gh run list --workflow build-default-models.yaml --branch "$REF" --limit 1 --json databaseId --jq '.[0].databaseId')
+          echo "Dispatched build run: $BUILD_RUN_ID"
+
+          echo "Waiting for build run to complete..."
          for i in $(seq 1 60); do
            sleep 30
-            if check_defaults; then
-              echo "DM model available on HF after $((i * 30))s"
-              exit 0
+            STATUS=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.status')
+            CONCLUSION=$(gh api "repos/${GH_REPO}/actions/runs/${BUILD_RUN_ID}" --jq '.conclusion')
+            echo "Poll $i/60: status=$STATUS conclusion=$CONCLUSION"
+            if [ "$STATUS" = "completed" ]; then
+              if [ "$CONCLUSION" = "success" ]; then
+                echo "Build run succeeded, verifying HF..."
+                sleep 10
+                if check_defaults; then
+                  echo "DM model verified on HF"
+                  exit 0
+                fi
+                echo "::error::Build succeeded but DM model not found on HF"
+                exit 1
+              else
+                echo "::error::Build run failed with conclusion=$CONCLUSION"
+                exit 1
+              fi
            fi
-            echo "Poll $i/60: not yet available"
          done

-          echo "::error::DM model not available on HF after 30 minutes"
+          echo "::error::DM model build did not complete within 30 minutes"
          exit 1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -1,181 +0,0 @@
-# Ford C2-free path tracking with measured feedback
-
-Hypothesis `curvature-c0-c1-feedback-v5` retains v4's absolute desired-curvature
-C0/C1 requests and adds a bounded yaw-error integral to C1. Persistent measured
-shortfall can increase the request without requiring the planner to keep
-increasing curvature; excess turning can reduce it. C0 and its centering
-input are unchanged. C2/C3 remain zero.
-
-This is an experimental outer feedback loop around the multivariable PSCM.
-It is not an angle servo or a calibrated C0/C1-to-wheel mapping. Its feedback
-scale and response interval are not road-validated.
-
-## Evidence and scope
-
-Route80 ran v3 (`98662df40`) and contains both sustained under-response and
-over-response. Representative eligible windows had median CAN response/request
-ratios of 0.78, 1.77 and 0.69 with a declared 0.2-second comparison interval.
-These are descriptive ratios, not gains or percentages of a maneuver completed.
-Wheel-model curvature agrees on the directions of these discrepancies.
-
-V4 (`0ace0b051`) replaced separate model-heading C1 with the selected curvature
-reference and reduced C1 in several large maneuvers. The user then reported
-steering repeatedly stopping near 85 degrees. No recording of that new symptom
-was available during implementation. Older logs contain much larger wheel
-angles. The inspected host path has no fixed 85-degree wheel stop, but an
-upstream speed-dependent curvature limit remains.
-
-Restoring larger C1 everywhere also restores excess demand in known
-overshoot cases and barely changes some sustained shortfalls. V5 tests whether
-measured correction can distinguish them. Replaying old motion verifies
-command construction, not the truck's counterfactual response or a fix for
-the unrecorded plateau.
-
-Route83 had the sunnylink toggle on, but its current CarParams omitted the
-EPS firmware responses. The former firmware eligibility check therefore
-selected the default `FordPathController`; replay reproduced its recorded
-C0/C1/C2 requests. Those favorable driving results do not validate v5. The
-toggle now selects this experiment on the supported Lightning platform
-without depending on firmware-query results.
-
-## Base request and feedback
-
-controlsd uses valid `lateralManeuverPlan.desiredCurvature`, otherwise
-`modelV2.action.desiredCurvature`, after the existing curvature limiter:
-
-```text
-L0 = max(8 m, speed × 1 s)
-L1 = max(7 m, speed × 1 s)
-C0_target = clip(0.5 × desired_curvature × L0², ±5.11 m)
-C1_base = clip(desired_curvature × L1, ±0.5 rad)
-
-past_request = selected curvature held at or before (measurement_time − delay)
-yaw_error = measured_speed × past_request − measured_yaw_rate
-bias_trial = released_bias + feedback_gain × yaw_error × measurement_dt
-C1_target = clip(C1_base + accepted_bias, ±0.5 rad)
-```
-
-Measured yaw is negated Ford CAN yaw rate, matching the control sign convention.
-The historical request uses zero-order hold, never interpolation toward a
-command published later. Nominal delay is `CP.steerActuatorDelay` (0.2 s on
-the source vehicle). This delays only the error comparison; it does not
-advance the already delay-aware current action again.
-
-The integration scale is **1.0**. Integrating compatible rad/s and rad units
-does not make it gain-free or establish stability. Preview distances are also
-effective gains. No adaptive wheel-response gain is identified.
-
-| Quantity | Value |
-|---|---:|
-| C0 / C1 bounds | ±5.11 m / ±0.5 rad |
-| Independent C0 / C1 slew | 4 m/s / 0.5 rad/s |
-| New feedback scale | 1.0 |
-| Feedback minimum speed | 2 m/s |
-| Maximum PSCM status age | 150 ms |
-| Allowed timestamp lead | 5 ms |
-| Release comparison tolerance | one C1 wire quantum, 0.0005 rad |
-
-Zero yaw error retains the acquired bias and absolute base. Reaching the target
-does not remove the additional demand that may be sustaining the turn.
-
-## Release and limits
-
-When the clipped base magnitude decreases, bias decreases in the same ratio.
-Using the clipped base avoids increasing total C1 by shrinking a negative bias
-while the base stays saturated. Zero request or reversal clears bias and
-requires fresh reference history. Existing output slew still applies.
-
-Integration is inhibited if the delayed request has the old sign or exceeds
-the current request by more than one heading quantum after multiplying the
-curvature difference by L1. This prevents old demand from rebuilding correction
-during release while tolerating sub-quantum planner changes.
-
-Host anti-windup considers both field and slew limits on the combined base
-and trial bias. It admits only reachable correction in the intended increment
-direction when an outward update hits a host limit, and permits inward
-unwinding. A large error must not stall correction merely because its entire
-increment cannot fit within one tick. Retained bias is bounded by available
-C1 field headroom. No overflow goes into C0; no safety limit is raised.
-
-Actual PSCM LimitReached freezes all new integration while base-driven
-release continues. C1 sign is not interpreted as motor-effort direction.
-Host bounds and generic status cannot identify internal PSCM dynamics or
-guarantee prevention of downstream windup.
-
-## PSCM status and driver handling
-
-card publishes the existing Ford parser's `Lane_Assist_Data3_FD1` status in
-`carStateSP.fordPscmStatus`, using its original CAN receipt timestamp.
-Republishing carStateSP or receiving unrelated CAN frames cannot refresh it.
-The opendbc submodule is unchanged.
-
-Feedback requires valid fresh status, InProgress lateral state (2), capability
-LimitedModeAvailable or ExtendedModeAvailable (1 or 2), and no denial.
-Missing, malformed, stale, backward-timestamped, denied or unavailable status
-clears feedback bias/history. Base control keeps its existing validity rules.
-LimitReached (2) freezes integration; LimitWithDriverActive (3) clears feedback.
-
-`steeringPressed`, raw torque above the existing Ford driver allowance, or
-nonfinite torque also clear feedback immediately. The baseline request retains
-its existing PSCM driver-arbitration behavior while lateral control remains
-authorized. An unset override flag cannot exclude subthreshold driver influence.
-A fresh reference interval is required after override.
-
-Below 2 m/s feedback clears; base C0/C1 keep their original speed gates.
-The correction does not learn a persistent zero-request bias. It is not a
-complete zero-yaw or lane-centering servo; centering intent continues to enter
-through selected desired curvature and C0.
-
-## Existing gates and selection
-
-Core model/action/car-state freshness, finite-value, clock and speed checks
-are unchanged. Invalid core inputs reset both commands and clear latActive.
-Model geometry remains for diagnostics and its existing validity gate; its
-filtered heading does not command C1.
-
-Vehicle → Ford → **C2-Free Path Tracking (Experimental)** retains the existing
-`FordVirtualAngleController` key and default-off setting. An already-enabled
-setting selects v5 after updating and restarting controlsd. The toggle
-controls selection on Ford CAN FD `FORD_F_150_LIGHTNING_MK1`: missing or
-different EPS firmware-query results no longer cause a fallback. Other
-platforms retain their existing controller. V5 takes priority over PSCM
-Coefficient Observer while selected. Turning it off and cycling offroad/onroad
-restores the previous controller selection; changes are not applied live onroad.
-
-Controller selection does not bypass lateral engagement, input-validity,
-driver-override or fresh-PSCM-status requirements. The feedback eligibility
-rules above still apply, and all C0/C1 bounds and C2/C3 behavior are unchanged.
-The analyzed firmware remains `RL38-14D003-AA`; removing the selection check
-does not establish validation on other firmware. No live device setting is
-changed by this commit.
-
-## Diagnostics and verification
-
-The 5 Hz `Ford C2-free path tracking` event identifies v5 and records the
-selected reference, measured curvature/yaw, base and corrected C1 targets,
-bias, integration status, historical request/time, yaw error, raw torque and
-PSCM freshness/status. `angleState.saturated` is not an EPS-limit substitute:
-it describes tracking error on this path.
-
-Checks cover deficit/excess response, retained turn demand, release/reversal,
-driver/status resets, delayed history, repeated measurements, host/PSCM limits,
-unchanged C0, C2/C3 zero, telemetry timestamps, CAN packing and recorded
-maneuvers. Missing-status behavior preserves v4 commands. Replay holds recorded
-motion and planner outputs fixed and cannot establish physical improvement
-or closed-loop stability.
-
-The final v5 replay covered 52,273 route80 cycles with reconstructed causal
-PSCM status and raw driver torque. C0 and output-validity gates were unchanged;
-C2/C3 stayed zero and command bounds, slew and reference causality passed.
-Median eligible C1 magnitude changed from 0.144 to 0.178 rad in the 333–339 s
-shortfall and 0.190 to 0.267 rad in the 430–435 s shortfall. The 417–420 s
-over-response window stayed at 0.286 rad: 102 of its 105 eligible samples
-reported LimitReached, suppressing new integration. This is a known limitation
-of the guarded candidate, not a demonstrated overshoot improvement.
-The separate no-status replay preserved v4 C1 and old C0/gates exactly over
-246,961 cycles across all 43 supplied segments.
-
-The next enabled logs must show whether tracking error diminishes without
-oscillation, excess release overshoot or increased intervention. A shortfall
-when the selected reference or available commands are already limited remains
-a separate case. This feedback cannot create new physical authority.
@@ -16,7 +16,7 @@ export VECLIB_MAXIMUM_THREADS=1
 export QCOM_PRIORITY=12

 if [ -z "$AGNOS_VERSION" ]; then
-  export AGNOS_VERSION="19.6"
+  export AGNOS_VERSION="19.7"
 fi

 export STAGING_ROOT="/data/safe_staging"
@@ -383,7 +383,6 @@ struct CarControlSP @0xa5cd762cd951a455 {
  leadOne @2 :LeadData;
  leadTwo @3 :LeadData;
  intelligentCruiseButtonManagement @4 :IntelligentCruiseButtonManagement;
-  fordLateralPath @5 :FordLateralPath;

  struct Param {
    key @0 :Text;
@@ -404,14 +403,6 @@ struct CarControlSP @0xa5cd762cd951a455 {
  }
 }

-struct FordLateralPath {
-  pathOffset @0 :Float32;     # c0 [m]
-  pathAngle @1 :Float32;      # c1 [rad]
-  curvature @2 :Float32;      # c2 [1/m]
-  curvatureRate @3 :Float32;  # c3 [1/m^2]
-  valid @4 :Bool;
-}
-
 struct BackupManagerSP @0xf98d843bfd7004a3 {
  backupStatus @0 :Status;
  restoreStatus @1 :Status;
@@ -456,16 +447,6 @@ struct BackupManagerSP @0xf98d843bfd7004a3 {

 struct CarStateSP @0xb86e6369214c01c8 {
  speedLimit @0 :Float32;
-  fordPscmStatus @1 :FordPscmStatus;
-
-  struct FordPscmStatus {
-    valid @0 :Bool;
-    canMonoTime @1 :UInt64;  # Last accepted Lane_Assist_Data3_FD1 CAN receipt, not carStateSP publication time.
-    lateralState @2 :UInt8;  # LatCtlSte_D_Stat
-    limit @3 :UInt8;  # LatCtlLim_D_Stat: generic lateral limit, not a torque/rate diagnosis.
-    capability @4 :UInt8;  # LatCtlCpblty_D_Stat
-    denied @5 :Bool;  # LaActDeny_B_Actl
-  }
 }

 struct LiveMapDataSP @0xf416ec09499d9d19 {
@@ -489,30 +470,7 @@ struct ModelDataV2SP @0xa1680744031fdb2d {
  }
 }

-struct AssistedDrivingMilestoneState @0xcb9fd56c7057593a {
-  enabled @0 :Bool;
-  madsDistanceMeters @1 :Float64;
-  fullAssistDistanceMeters @2 :Float64;
-  event @3 :Event;
-
-  struct Event {
-    id @0 :UInt64;
-    category @1 :Category;
-    distanceMeters @2 :Float64;
-    previousDistanceMeters @3 :Float64;
-    unit @4 :Unit;
-  }
-
-  enum Category {
-    none @0;
-    mads @1;
-    fullAssist @2;
-  }
-
-  enum Unit {
-    imperial @0;
-    metric @1;
-  }
+struct CustomReserved10 @0xcb9fd56c7057593a {
 }

 struct CustomReserved11 @0xc2243c65e0340384 {
@@ -725,6 +725,7 @@ struct ChestnutState {
  pcieLtssm @7 :UInt8;
  supplyVoltage @8 :UInt16;  # mV
  supplyCurrent @9 :Int16;  # mA
+  supplyFault @10 :Bool;
 }

 struct RadarState @0x9a185389d6fdd05f {
@@ -1004,6 +1005,7 @@ struct DrivingModelData {
  frameIdExtra @1 :UInt32;
  frameDropPerc @6 :Float32;
  modelExecutionTime @7 :Float32;
+  big @8 :Bool;

  action @2 :ModelDataV2.Action;

@@ -2640,7 +2642,7 @@ struct Event {
    carStateSP @114 :Custom.CarStateSP;
    liveMapDataSP @115 :Custom.LiveMapDataSP;
    modelDataV2SP @116 :Custom.ModelDataV2SP;
-    assistedDrivingMilestoneState @136 :Custom.AssistedDrivingMilestoneState;
+    customReserved10 @136 :Custom.CustomReserved10;
    customReserved11 @137 :Custom.CustomReserved11;
    customReserved12 @138 :Custom.CustomReserved12;
    customReserved13 @139 :Custom.CustomReserved13;
@@ -90,7 +90,6 @@ _services: dict[str, tuple] = {
  "carParamsSP": (True, 0.02, 1),
  "carControlSP": (True, 100., 10),
  "carStateSP": (True, 100., 10),
-  "assistedDrivingMilestoneState": (True, 10., 1),
  "liveMapDataSP": (True, 1., 1),
  "modelDataV2SP": (True, 20., None, QueueSize.BIG),
  "liveLocationKalman": (True, 20.),
@@ -56,29 +56,29 @@
  },
  {
    "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd.img.xz",
-    "hash": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
-    "hash_raw": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
+    "url": "https://commadist.azureedge.net/agnosupdate/boot-6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d.img.xz",
+    "hash": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
+    "hash_raw": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
    "size": 46897152,
    "sparse": false,
    "full_check": true,
    "has_ab": true,
-    "ondevice_hash": "6650e4c46df99ae6dfd6ee895a34b8a2a3cc490a8ce18e16cc3c451c3f822b6e"
+    "ondevice_hash": "d12e1e5b9455b62a1464558716493b33e470d7a7e88da1c4105a3b21d0961808"
  },
  {
    "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img.xz",
-    "hash": "b134fd04e9da27fa1d359ea0f2742c216fa21a08b5c47e9be22ab3b0563d9b9b",
-    "hash_raw": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img.xz",
+    "hash": "74ffc9c551e1f29cda897ace8a69080fe644f8039977c6885f2b48362e39b744",
+    "hash_raw": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
    "size": 4718592000,
    "sparse": true,
    "full_check": false,
    "has_ab": true,
-    "ondevice_hash": "91242772af771ae96fe2eebc105f2b80a7e1dbaaf6003c2574b62d51b806f468",
+    "ondevice_hash": "6a992680183685eea9db99d915219a37935f45989330d9b619e880450257f448",
    "alt": {
-      "hash": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img",
+      "hash": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img",
      "size": 4718592000
    }
  }
-]
+]
@@ -5,6 +5,7 @@ import logging
 import os
 import select
 import signal
+import string
 import struct
 import subprocess
 import tempfile
@@ -354,7 +355,7 @@ class Modem:
      imei = ""

    iccid = (self._atv("AT+QCCID", "+QCCID:") or "").rstrip("F")
-    if not iccid.isdigit():
+    if not all(c in string.hexdigits for c in iccid):
      iccid = ""

    imsi = first_line("AT+CIMI")
@@ -4,11 +4,17 @@ from pathlib import Path
 CHESTNUT_FW_VERSION = "ed4e39b7"
 CHESTNUT_USB_IDS = ((0xADD1, 0x0001), (0x3801, 0x0001))
 CHESTNUT_ROM_USB_IDS = ((0x174C, 0x2464), (0x174C, 0x2463))
+CHESTNUT_USB_PRODUCT = f"custom {CHESTNUT_FW_VERSION}-CLEAN"
 USB_DEVICES_PATH = Path("/sys/bus/usb/devices")
 TYPEC_CC_ORIENTATION_PATH = Path("/sys/class/power_supply/usb/typec_cc_orientation")
 PRIMARY_USB_CONTROLLER = "a600000.ssusb"


+def is_chestnut_usb_id(vendor_id: int, product_id: int, include_bootloader: bool = False) -> bool:
+  ids = CHESTNUT_USB_IDS + CHESTNUT_ROM_USB_IDS if include_bootloader else CHESTNUT_USB_IDS
+  return (vendor_id, product_id) in ids
+
+
 def get_usb_topology() -> set[str]:
  try:
    return set(os.listdir(USB_DEVICES_PATH))
@@ -81,7 +87,7 @@ def set_usb_state(device_state, devices: list[dict]) -> None:
    entry.linkErrorCount = device["linkErrorCount"]
    entry.usb3Lane = device.get("usb3Lane", "unknown")

-    if (entry.vendorId, entry.productId) in CHESTNUT_USB_IDS:
+    if is_chestnut_usb_id(entry.vendorId, entry.productId):
      chestnut_present = True

  device_state.chestnutPresent = chestnut_present
@@ -97,10 +97,6 @@ Params::Params(const std::string &path) {
 }

 Params::~Params() {
-  flushNonBlockingWrites();
-}
-
-void Params::flushNonBlockingWrites() {
  if (future.valid()) {
    future.wait();
  }
@@ -75,7 +75,6 @@ public:
    return put(key.c_str(), val ? "1" : "0", 1);
  }
  void putNonBlocking(const std::string &key, const std::string &val);
-  void flushNonBlockingWrites();
  inline void putBoolNonBlocking(const std::string &key, bool val) {
    putNonBlocking(key, val ? "1" : "0");
  }
@@ -73,7 +73,6 @@ params_get = _bind("params_get", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool],
 params_get_bool = _bind("params_get_bool", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool], ctypes.c_bool)
 params_put = _bind("params_put", [ParamsHandle, ctypes.c_char_p, ctypes.c_char_p, ctypes.c_size_t, ctypes.c_bool], ctypes.c_int)
 params_put_bool = _bind("params_put_bool", [ParamsHandle, ctypes.c_char_p, ctypes.c_bool, ctypes.c_bool], ctypes.c_int)
-params_flush = _bind("params_flush", [ParamsHandle])
 params_remove = _bind("params_remove", [ParamsHandle, ctypes.c_char_p], ctypes.c_int)
 params_get_path = _bind("params_get_path", [ParamsHandle, ctypes.c_char_p, ctypes.c_size_t], ParamsBuffer)
 params_keys_size = _bind("params_keys_size", [ParamsHandle], ctypes.c_size_t)
@@ -179,10 +178,6 @@ class Params:
  def put_bool(self, key, val, block=False):
    params_put_bool(self.p, self.check_key(key), val, block)

-  def flush(self):
-    """Wait for all prior nonblocking writes from this Params instance."""
-    params_flush(self.p)
-
  def remove(self, key):
    params_remove(self.p, self.check_key(key))

@@ -133,12 +133,6 @@ int params_put_bool(ParamsHandle *handle, const char *key, bool value, bool bloc
  });
 }

-void params_flush(ParamsHandle *handle) noexcept {
-  translate_exceptions([&]() {
-    handle->params.flushNonBlockingWrites();
-  });
-}
-
 int params_remove(ParamsHandle *handle, const char *key) noexcept {
  return translate_exceptions(-1, [&]() {
    return handle->params.remove(key);
@@ -92,6 +92,12 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"ObdMultiplexingEnabled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, BOOL}},
    {"Offroad_CarUnrecognized", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
    {"Offroad_ChestnutBranch", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutNotDetected", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutOverheated", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutPcieUnavailable", {CLEAR_ON_MANAGER_START, JSON}},
+    {"Offroad_ChestnutUncompiled", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUpdateFailed", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
+    {"Offroad_ChestnutUsbSlow", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, JSON}},
    {"Offroad_ConnectivityNeeded", {CLEAR_ON_MANAGER_START, JSON}},
    {"Offroad_ConnectivityNeededPrompt", {CLEAR_ON_MANAGER_START, JSON}},
    {"Offroad_ExcessiveActuation", {PERSISTENT, JSON}},
@@ -132,12 +138,11 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"UptimeOnroad", {PERSISTENT, FLOAT, "0.0"}},
    {"ChestnutActive", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
    {"ChestnutLoading", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
+    {"ChestnutModelError", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION | CLEAR_ON_IGNITION_ON, BOOL}},
    {"Version", {PERSISTENT, STRING}},

    // --- sunnypilot params --- //
    {"ApiCache_DriveStats", {PERSISTENT, JSON}},
-    {"AssistedDrivingMilestonesEnabled", {PERSISTENT | BACKUP, BOOL, "1"}},
-    {"AssistedDrivingMilestoneState", {PERSISTENT, JSON, "{}"}},
    {"AutoLaneChangeBsmDelay", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"AutoLaneChangeTimer", {PERSISTENT | BACKUP, INT, "0"}},
    {"BlinkerLateralReengageDelay", {PERSISTENT | BACKUP, INT, "0"}},  // seconds
@@ -158,7 +163,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"DevUIInfo", {PERSISTENT | BACKUP, INT, "0"}},
    {"EnableCopyparty", {PERSISTENT | BACKUP, BOOL}},
    {"EnableGithubRunner", {PERSISTENT | BACKUP, BOOL}},
-    {"FullAssistDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
    {"GreenLightAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"GithubRunnerSufficientVoltage", {CLEAR_ON_MANAGER_START , BOOL}},
    {"HasAcceptedTermsSP", {PERSISTENT, STRING, "0"}},
@@ -168,9 +172,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"IsDevelopmentBranch", {CLEAR_ON_MANAGER_START, BOOL}},
    {"IsReleaseSpBranch", {CLEAR_ON_MANAGER_START, BOOL}},
    {"LastGPSPositionLLK", {PERSISTENT, STRING}},
-    {"LastDriveAssistedDrivingSummary", {PERSISTENT, JSON, "{}"}},
    {"LeadDepartAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"MadsDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
    {"MaxTimeOffroad", {PERSISTENT | BACKUP, INT, "1800"}},
    {"ModelRunnerTypeCache", {CLEAR_ON_ONROAD_TRANSITION, INT}},
    {"OffroadMode", {CLEAR_ON_MANAGER_START, BOOL}},
@@ -230,8 +232,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
    {"BackupManager_RestoreVersion", {PERSISTENT, STRING}},

    // sunnypilot car specific params
-    {"FordPscmObserver", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"FordVirtualAngleController", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"HyundaiLongitudinalTuning", {PERSISTENT | BACKUP, INT, "0"}},
    {"SubaruStopAndGo", {PERSISTENT | BACKUP, BOOL, "0"}},
    {"SubaruStopAndGoManualParkingBrake", {PERSISTENT | BACKUP, BOOL, "0"}},
@@ -27,14 +27,14 @@ public:
    auto param_path = Params().getParamPath();
    if (util::file_exists(param_path)) {
      std::string real_path = util::readlink(param_path);
-      util::check_system(util::string_format("rm %s -rf", real_path.c_str()));
+      util::check_system(util::string_format("rm -rf %s", real_path.c_str()));
      unlink(param_path.c_str());
    }
    if (getenv("COMMA_CACHE") == nullptr) {
-      util::check_system(util::string_format("rm %s -rf", Path::download_cache_root().c_str()));
+      util::check_system(util::string_format("rm -rf %s", Path::download_cache_root().c_str()));
    }
-    util::check_system(util::string_format("rm %s -rf", Path::comma_home().c_str()));
-    util::check_system(util::string_format("rm %s -rf", msgq_path.c_str()));
+    util::check_system(util::string_format("rm -rf %s", Path::comma_home().c_str()));
+    util::check_system(util::string_format("rm -rf %s", msgq_path.c_str()));
    unsetenv("OPENPILOT_PREFIX");
  }

@@ -106,13 +106,6 @@ class TestParams(OpenpilotTestCase):
    assert q.get("CarParams") is None
    assert q.get("CarParams", True) == b"1"

-  def test_flush_non_blocking_writes(self):
-    self.params.put("DongleId", "first")
-    self.params.put("DongleId", "last")
-    self.params.flush()
-
-    assert self.params.get("DongleId") == "last"
-
  def test_params_all_keys(self):
    keys = Params().all_keys()

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07bda2fe5d6be0b2854044053c384fe002e96406da119863a443b9344258b500
+size 1544
@@ -21,7 +21,6 @@ from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.helpers import convert_carControlSP, convert_to_capnp
-from openpilot.selfdrive.car.ford_pscm_status import populate_ford_pscm_status

 from openpilot.sunnypilot.mads.helpers import set_alternative_experience, set_car_specific_params
 from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
@@ -199,7 +198,6 @@ class Car:
    # Update carState from CAN
    CS, CS_SP = self.CI.update(can_list)
    CS_SP = convert_to_capnp(CS_SP)
-    populate_ford_pscm_status(self.CP, self.CI.can_parsers, CS_SP, CS.canValid)

    # Update radar tracks from CAN
    RD: structs.RadarDataT | None = self.RI.update(can_list)
@@ -1,36 +0,0 @@
-"""Publish the Ford PSCM's actual CAN status without changing opendbc structs."""
-import math
-
-from opendbc.car import Bus
-from opendbc.car.ford.values import FordFlags
-
-
-MESSAGE = 'Lane_Assist_Data3_FD1'
-SIGNALS = ('LatCtlSte_D_Stat', 'LatCtlLim_D_Stat', 'LatCtlCpblty_D_Stat', 'LaActDeny_B_Actl')
-
-
-def populate_ford_pscm_status(CP, can_parsers, CS_SP, can_valid):
-  if CP.brand != 'ford' or not CP.flags & FordFlags.CANFD:
-    return
-  status = CS_SP.init('fordPscmStatus')
-  parser = can_parsers.get(Bus.pt)
-  if parser is None:
-    return
-  values = parser.vl.get(MESSAGE, {})
-  timestamps = parser.ts_nanos.get(MESSAGE, {})
-  if any(signal not in values or signal not in timestamps for signal in SIGNALS):
-    return
-  received = timestamps[SIGNALS[0]]
-  if received <= 0 or any(timestamps[signal] != received for signal in SIGNALS):
-    return
-  decoded = [values[signal] for signal in SIGNALS]
-  if any(not math.isfinite(value) or int(value) != value or not 0 <= value <= maximum
-         for value, maximum in zip(decoded, (7, 3, 3, 1), strict=True)):
-    return
-  status.canMonoTime = received
-  status.lateralState, status.limit, status.capability = map(int, decoded[:3])
-  status.denied = bool(decoded[3])
-  # CI.update already checked all parser validity. Reading can_valid again here
-  # would advance the parser's invalid-message counter a second time per tick.
-  # Age is evaluated by the feedback consumer using this original CAN timestamp.
-  status.valid = bool(can_valid)
@@ -63,6 +63,5 @@ def convert_carControlSP(struct: capnp.lib.capnp._DynamicStructReader) -> struct
  struct_dataclass.intelligentCruiseButtonManagement = structs.IntelligentCruiseButtonManagement(
    **remove_deprecated(struct_dict.get('intelligentCruiseButtonManagement', {}))
  )
-  struct_dataclass.fordLateralPath = structs.FordLateralPath(**remove_deprecated(struct_dict.get('fordLateralPath', {})))

  return struct_dataclass
@@ -1,109 +0,0 @@
-import ast
-from pathlib import Path
-from types import SimpleNamespace
-import unittest
-
-from openpilot.cereal import custom
-from openpilot.selfdrive.car.ford_pscm_status import MESSAGE, SIGNALS, populate_ford_pscm_status
-from openpilot.selfdrive.car.helpers import convert_to_capnp
-from opendbc.can import CANPacker, CANParser
-from opendbc.car import Bus, structs
-from opendbc.car.ford.values import FordFlags
-
-
-class TestFordPscmStatus(unittest.TestCase):
-  def setUp(self):
-    self.cp = SimpleNamespace(brand='ford', flags=FordFlags.CANFD)
-    self.packer = CANPacker('ford_lincoln_base_pt')
-    self.parser = CANParser('ford_lincoln_base_pt', [(MESSAGE, 33), ('Yaw_Data_FD1', 100)], 0)
-
-  def update_status(self, timestamp, *, lateral_state=2, limit=0, capability=2, denied=False):
-    status = self.packer.make_can_msg(MESSAGE, 0, dict(zip(SIGNALS, (lateral_state, limit, capability, denied), strict=True)))
-    yaw = self.packer.make_can_msg('Yaw_Data_FD1', 0, {'VehYaw_W_Actl': 0.1})
-    self.parser.update([(timestamp, [status, yaw])])
-
-  def publish(self, *, can_valid=True):
-    state_sp = convert_to_capnp(structs.CarStateSP(speedLimit=13.5))
-    populate_ford_pscm_status(self.cp, {Bus.pt: self.parser}, state_sp, can_valid)
-    return state_sp
-
-  def test_decodes_status_and_preserves_receipt_time_across_other_can_messages(self):
-    self.update_status(1_000_000_000, limit=2, capability=1, denied=True)
-    original = self.publish()
-    self.assertEqual(original.speedLimit, 13.5)
-    status = original.fordPscmStatus
-    self.assertTrue(status.valid)
-    self.assertEqual(status.canMonoTime, 1_000_000_000)
-    self.assertEqual((status.lateralState, status.limit, status.capability, status.denied), (2, 2, 1, True))
-
-    # carStateSP may publish at 100 Hz while this 33 Hz message is absent. New
-    # unrelated CAN must not freshen the timestamp of an old PSCM status.
-    yaw = self.packer.make_can_msg('Yaw_Data_FD1', 0, {'VehYaw_W_Actl': .2})
-    self.parser.update([(1_080_000_000, [yaw])])
-    copied = self.publish().fordPscmStatus
-    self.assertEqual(copied.canMonoTime, 1_000_000_000)
-    self.assertEqual((copied.limit, copied.capability, copied.denied), (2, 1, True))
-
-    self.update_status(1_090_000_000, lateral_state=3, limit=3, capability=2)
-    next_state = self.publish()
-    with custom.CarStateSP.from_bytes(next_state.to_bytes()) as decoded:
-      latest = decoded.fordPscmStatus
-      self.assertTrue(latest.valid)
-      self.assertEqual(latest.canMonoTime, 1_090_000_000)
-      self.assertEqual((latest.lateralState, latest.limit, latest.capability, latest.denied), (3, 3, 2, False))
-
-  def test_absent_parser_unseen_message_and_invalid_can_do_not_claim_valid_status(self):
-    state = custom.CarStateSP.new_message()
-    populate_ford_pscm_status(self.cp, {}, state, True)
-    self.assertFalse(state.fordPscmStatus.valid)
-    self.assertEqual(state.fordPscmStatus.canMonoTime, 0)
-    self.assertFalse(self.publish().fordPscmStatus.valid)
-    self.update_status(1_000_000_000)
-    invalid = self.publish(can_valid=False).fordPscmStatus
-    self.assertFalse(invalid.valid)
-    self.assertEqual(invalid.canMonoTime, 1_000_000_000)
-
-  def test_mixed_timestamps_or_malformed_status_cannot_enable_feedback(self):
-    self.update_status(1_000_000_000)
-    self.parser.ts_nanos[MESSAGE][SIGNALS[-1]] = 990_000_000
-    self.assertFalse(self.publish().fordPscmStatus.valid)
-    self.parser.ts_nanos[MESSAGE][SIGNALS[-1]] = 1_000_000_000
-    for value in (float('nan'), -1, 1.5, 4):
-      self.parser.vl[MESSAGE]['LatCtlLim_D_Stat'] = value
-      self.assertFalse(self.publish().fordPscmStatus.valid)
-
-  def test_other_vehicles_and_legacy_messages_default_to_unavailable(self):
-    for cp in (SimpleNamespace(brand='toyota'), SimpleNamespace(brand='ford', flags=0)):
-      state = custom.CarStateSP.new_message(speedLimit=10.)
-      populate_ford_pscm_status(cp, {}, state, True)
-      self.assertFalse(state.fordPscmStatus.valid)
-      self.assertEqual(state.fordPscmStatus.canMonoTime, 0)
-      self.assertEqual(state.speedLimit, 10.)
-    # Old recordings/readers have no appended status pointer; defaults must
-    # remain unavailable rather than interpreting zeroed enums as fresh data.
-    self.assertFalse(custom.CarStateSP.new_message().fordPscmStatus.valid)
-
-  def test_actual_card_update_populates_status_after_dataclass_conversion(self):
-    self.update_status(1_000_000_000, limit=1)
-    source_path = Path(__file__).resolve().parents[1] / 'card.py'
-    source = ast.parse(source_path.read_text())
-    car_class = next(n for n in source.body if isinstance(n, ast.ClassDef) and n.name == 'Car')
-    method = next(n for n in car_class.body if isinstance(n, ast.FunctionDef) and n.name == 'state_update')
-    statements = method.body
-    first = next(i for i, n in enumerate(statements) if isinstance(n, ast.Assign) and ast.unparse(n.value) == 'self.CI.update(can_list)')
-    last = next(i for i, n in enumerate(statements) if isinstance(n, ast.Expr) and isinstance(n.value, ast.Call)
-                and isinstance(n.value.func, ast.Name) and n.value.func.id == 'populate_ford_pscm_status')
-    self.assertGreater(last, first)
-    code = compile(ast.Module(body=statements[first:last + 1], type_ignores=[]), str(source_path), 'exec')
-    ci = SimpleNamespace(update=lambda _: (SimpleNamespace(canValid=True), structs.CarStateSP(speedLimit=11.)),
-                         can_parsers={Bus.pt: self.parser})
-    environment = {'self': SimpleNamespace(CP=self.cp, CI=ci), 'can_list': [], 'convert_to_capnp': convert_to_capnp,
-                   'populate_ford_pscm_status': populate_ford_pscm_status}
-    exec(code, environment)
-    self.assertTrue(environment['CS_SP'].fordPscmStatus.valid)
-    self.assertEqual(environment['CS_SP'].fordPscmStatus.canMonoTime, 1_000_000_000)
-    self.assertEqual(environment['CS_SP'].fordPscmStatus.limit, 1)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
 import math
-import time
 from numbers import Number

 from openpilot.cereal import log
@@ -12,11 +11,8 @@ from openpilot.common.realtime import config_realtime_process, DT_CTRL, Priority
 from openpilot.common.swaglog import cloudlog

 from opendbc.car.car_helpers import interfaces
-from opendbc.car.ford.values import FordFlags
 from opendbc.car.vehicle_model import VehicleModel
 from openpilot.selfdrive.controls.lib.drive_helpers import clip_curvature
-from openpilot.selfdrive.controls.lib.ford_path import FordPath, FordPathController, FordPscmObserverPathController
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController, PscmStatus, select_virtual_angle_controller
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl
 from openpilot.selfdrive.controls.lib.latcontrol_pid import LatControlPID
 from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle, STEER_ANGLE_SATURATION_THRESHOLD
@@ -48,7 +44,7 @@ class Controls(ControlsExt):
    self.CI = interfaces[self.CP.carFingerprint](self.CP, self.CP_SP)

    self.sm = messaging.SubMaster(['lateralDelay', 'vehicleParameters', 'lateralTorqueParameters', 'modelV2', 'selfdriveState',
-                                   'extrinsicsCalibration', 'deviceMotion', 'longitudinalPlan', 'lateralManeuverPlan', 'carState', 'carStateSP', 'carOutput',
+                                   'extrinsicsCalibration', 'deviceMotion', 'longitudinalPlan', 'lateralManeuverPlan', 'carState', 'carOutput',
                                   'driverMonitoringState', 'onroadEvents', 'driverAssistance'] + self.sm_services_ext,
                                  poll='selfdriveState')
    self.pm = messaging.PubMaster(['carControl', 'controlsState'] + self.pm_services_ext)
@@ -56,15 +52,6 @@ class Controls(ControlsExt):
    self.steer_limited_by_safety = False
    self.curvature = 0.0
    self.desired_curvature = 0.0
-    self.ford_pscm_observer = (self.CP.brand == "ford" and self.CP.flags & FordFlags.CANFD and
-                               self.params.get_bool("FordPscmObserver"))
-    self.ford_path_controller = FordPscmObserverPathController() if self.ford_pscm_observer else FordPathController()
-    self.ford_path_controller = select_virtual_angle_controller(self.CP, self.params.get_bool("FordVirtualAngleController"),
-                                                               self.ford_path_controller)
-    self.ford_virtual_angle = isinstance(self.ford_path_controller, FordVirtualAngleController)
-    if self.CP.brand == "ford":
-      cloudlog.event("Ford path controller selected", controller=type(self.ford_path_controller).__name__)
-    self.ford_path = FordPath()

    self.pose_calibrator = PoseCalibrator()
    self.calibrated_pose: Pose | None = None
@@ -168,39 +155,6 @@ class Controls(ControlsExt):
      actuators.curvature = float(lateral_output)
    else:
      actuators.steeringAngleDeg = float(lateral_output)
-    if self.CP.brand == "ford":
-      ford_model = model_v2 if self.sm.valid['modelV2'] else None
-      if self.ford_virtual_angle:
-        reference_service = 'lateralManeuverPlan' if self.sm.valid['lateralManeuverPlan'] else 'modelV2'
-        pscm = self.sm['carStateSP'].fordPscmStatus
-        pscm_status = PscmStatus(timestamp=pscm.canMonoTime * 1e-9, lateral_state=pscm.lateralState,
-                                 limit=pscm.limit, capability=pscm.capability, denied=pscm.denied,
-                                 valid=pscm.valid and self.sm.all_checks(['carStateSP']))
-        self.ford_path = self.ford_path_controller.update(
-          ford_model, self.desired_curvature, yaw_rate=-CS.yawRate, speed=CS.vEgo, now=time.monotonic(),
-          measurement_time=self.sm.logMonoTime['carState'] * 1e-9,
-          model_time=self.sm.logMonoTime['modelV2'] * 1e-9,
-          reference_time=self.sm.logMonoTime[reference_service] * 1e-9,
-          active=CC.latActive, valid=CS.canValid and self.sm.all_checks(['carState', 'vehicleParameters', 'modelV2', reference_service]),
-          steering_pressed=CS.steeringPressed, steering_torque=CS.steeringTorque, pscm_status=pscm_status,
-        )
-        if not self.ford_path.valid:
-          CC.latActive = False
-        if self.sm.frame % 20 == 0:
-          cloudlog.event("Ford C2-free path tracking", model_mono_time=self.sm.logMonoTime['modelV2'],
-                         measurement_mono_time=self.sm.logMonoTime['carState'],
-                         reference_service=reference_service, reference_mono_time=self.sm.logMonoTime[reference_service],
-                         measured_curvature=self.curvature,
-                         **self.ford_path_controller.diagnostics)
-      elif self.ford_pscm_observer:
-        self.ford_path = self.ford_path_controller.update(ford_model, self.desired_curvature,
-                                                          current_curvature=self.curvature, v_ego=CS.vEgo,
-                                                          v_ego_raw=CS.vEgoRaw, active=CC.latActive)
-      else:
-        self.ford_path = self.ford_path_controller.update(ford_model, self.desired_curvature,
-                                                          current_curvature=self.curvature, v_ego=CS.vEgo,
-                                                          active=CC.latActive)
-      actuators.curvature = float(self.ford_path.curvature)
    # Ensure no NaNs/Infs
    for p in ACTUATOR_FIELDS:
      attr = getattr(actuators, p)
@@ -1,348 +0,0 @@
-from collections import deque
-from dataclasses import dataclass
-import math
-
-import numpy as np
-
-from opendbc.car.ford.values import CarControllerParams
-
-
-DBC_OFFSET = (-5.12, 5.11)
-DBC_ANGLE = (-0.5, 0.5235)
-DBC_CURVATURE = (-0.02, 0.02)
-DBC_CURVATURE_RATE = (-0.001024, 0.001023)
-
-DBC_OFFSET_RESOLUTION = 0.01
-DBC_ANGLE_RESOLUTION = 0.0005
-DBC_CURVATURE_RESOLUTION = 0.00002
-DBC_CURVATURE_RATE_RESOLUTION = 0.000001
-_PATH_MIN_LOOKAHEAD = 7.0
-_POSE_PREDICTION_TIME = 0.1
-_POSE_BLEND_CURVATURE = (0.006, 0.012)
-_PATH_OFFSET_RATE = 4.0
-_PATH_ANGLE_RATE = 1.0
-
-_PSCM_DT = 0.004
-_PSCM_C0_RATE = 1.5
-_PSCM_C1_RATE = 0.100006103515625
-_PSCM_C2_RATE = 0.0030059814453125
-_PSCM_SPEED_KPH = (0.0, 15.0, 40.0, 70.0, 100.0, 150.0, 200.0, 250.0)
-_PSCM_SPEED_GAIN = (32.0, 32.0, 32.0, 30.0, 30.0, 24.0, 12.0, 0.0)
-_PSCM_C0_EFFECTIVE_LIMIT = 1.0
-_PSCM_C1_EFFECTIVE_LIMIT = 0.349609375 / 10.0
-
-
-@dataclass(frozen=True)
-class FordPath:
-  valid: bool = False
-  path_offset: float = 0.0
-  path_angle: float = 0.0
-  curvature: float = 0.0
-  curvature_rate: float = 0.0
-
-
-@dataclass(frozen=True)
-class FordPscmState:
-  path_offset: float = 0.0
-  path_angle: float = 0.0
-  curvature: float = 0.0
-
-
-def _finite(value: float) -> float:
-  return float(value) if math.isfinite(value) else 0.0
-
-
-def _sample(distance: float, distances: list[float], values: list[float]) -> float:
-  return float(np.interp(distance, distances, values))
-
-
-def _blend_share(demand: float) -> float:
-  lower, upper = _POSE_BLEND_CURVATURE
-  return float(np.clip((demand - lower) / (upper - lower), 0.0, 1.0))
-
-
-def _model_path(model) -> tuple[list[float], list[float], list[float], list[float]] | None:
-  try:
-    x = [float(value) for value in model.position.x]
-    y = [float(value) for value in model.position.y]
-    heading = [float(value) for value in model.orientation.z]
-  except (AttributeError, TypeError, ValueError):
-    return None
-  if len(x) < 2 or len(x) != len(y) or len(x) != len(heading):
-    return None
-  if not all(math.isfinite(value) for values in (x, y, heading) for value in values):
-    return None
-
-  distance = [0.0]
-  for i in range(1, len(x)):
-    distance.append(distance[-1] + math.hypot(x[i] - x[i - 1], y[i] - y[i - 1]))
-  if distance[-1] <= 0.0:
-    return None
-
-  unwrapped_heading = [heading[0]]
-  for value in heading[1:]:
-    delta = (value - unwrapped_heading[-1] + math.pi) % (2.0 * math.pi) - math.pi
-    unwrapped_heading.append(unwrapped_heading[-1] + delta)
-  return distance, x, y, unwrapped_heading
-
-
-def _predicted_pose(distance: float, current_curvature: float,
-                    curvature_delta: float) -> tuple[float, float, float]:
-  curvature = current_curvature + 0.5 * curvature_delta
-  heading = curvature * distance
-  if abs(curvature) < 1e-9:
-    return distance, 0.0, 0.0
-  return math.sin(heading) / curvature, (1.0 - math.cos(heading)) / curvature, heading
-
-
-def _relative_pose(target_distance: float, path: tuple[list[float], list[float], list[float], list[float]],
-                   vehicle_pose: tuple[float, float, float]) -> tuple[float, float]:
-  distance, x, y, heading = path
-  vehicle_x, vehicle_y, vehicle_heading = vehicle_pose
-  dx = _sample(target_distance, distance, x) - vehicle_x
-  dy = _sample(target_distance, distance, y) - vehicle_y
-  cosine = math.cos(vehicle_heading)
-  sine = math.sin(vehicle_heading)
-  offset = -sine * dx + cosine * dy
-  angle = math.atan2(math.sin(_sample(target_distance, distance, heading) - vehicle_heading),
-                     math.cos(_sample(target_distance, distance, heading) - vehicle_heading))
-  return offset, angle
-
-
-def _path_pose(target_distance: float,
-               path: tuple[list[float], list[float], list[float], list[float]]) -> tuple[float, float, float]:
-  distance, x, y, heading = path
-  return (_sample(target_distance, distance, x), _sample(target_distance, distance, y),
-          _sample(target_distance, distance, heading))
-
-
-def _bounded_feedback(feedforward: float, feedback: float, resolution: float, zero_path_limit: float) -> float:
-  quantization_threshold = 0.5 * resolution
-  limit = max(abs(feedforward) - resolution, 0.0) if abs(feedforward) >= quantization_threshold else zero_path_limit
-  return float(np.clip(feedback, -limit, limit))
-
-
-def _encode_path(path: tuple[list[float], list[float], list[float], list[float]], desired_curvature: float,
-                 current_curvature: float, curvature_delta: float, v_ego: float) -> FordPath:
-  distance, _, _, _ = path
-  advance = min(v_ego * _POSE_PREDICTION_TIME, distance[-1])
-  offset_horizon = min(_PATH_MIN_LOOKAHEAD, distance[-1] - advance)
-  angle_horizon = min(max(v_ego, _PATH_MIN_LOOKAHEAD), distance[-1] - advance)
-
-  # Keep the model's remaining path as feedforward. Measured vehicle motion is
-  # a separate, short delay-aligned correction, so catching the requested
-  # curvature cannot erase a turn that is still present in the model path.
-  model_pose = _path_pose(advance, path)
-  model_offset, _ = _relative_pose(advance + offset_horizon, path, model_pose)
-  _, model_angle = _relative_pose(advance + angle_horizon, path, model_pose)
-  vehicle_pose = _predicted_pose(advance, current_curvature, curvature_delta)
-  feedback_offset, feedback_angle = _relative_pose(advance, path, vehicle_pose)
-  gentle_curvature = _POSE_BLEND_CURVATURE[0]
-  feedback_offset = _bounded_feedback(model_offset, feedback_offset, DBC_OFFSET_RESOLUTION,
-                                       0.5 * gentle_curvature * advance ** 2)
-  feedback_angle = _bounded_feedback(model_angle, feedback_angle, DBC_ANGLE_RESOLUTION,
-                                      gentle_curvature * advance)
-
-  offset_curvature = 2.0 * model_offset / max(offset_horizon, 1e-3) ** 2
-  angle_curvature = model_angle / max(angle_horizon, 1e-3)
-  pose_share = _blend_share(max(abs(offset_curvature), abs(angle_curvature), abs(desired_curvature)))
-
-  # Match upstream's C2-only normal driving, then continuously transfer the
-  # command to the model pose for larger maneuvers. An opposing/finished model
-  # path must unload sticky C2 and retain the fast pose needed to unwind it.
-  c2_opposes_path = desired_curvature != 0.0 and desired_curvature * model_angle <= 0.0
-  if c2_opposes_path:
-    pose_share = 1.0
-    curvature = 0.0
-  else:
-    curvature = desired_curvature * (1.0 - pose_share)
-
-  path_offset = pose_share * (model_offset + feedback_offset)
-  path_angle = pose_share * (model_angle + feedback_angle)
-  if abs(path_offset) < 0.5 * DBC_OFFSET_RESOLUTION:
-    path_offset = 0.0
-  if abs(path_angle) < 0.5 * DBC_ANGLE_RESOLUTION:
-    path_angle = 0.0
-  limited_path_angle = float(np.clip(path_angle, *DBC_ANGLE))
-  path_offset += (path_angle - limited_path_angle) * offset_horizon
-  return FordPath(
-    valid=True,
-    path_offset=float(np.clip(path_offset, *DBC_OFFSET)),
-    path_angle=limited_path_angle,
-    curvature=float(np.clip(curvature, *DBC_CURVATURE)),
-    curvature_rate=0.0,
-  )
-
-
-class FordPathController:
-  """Blend normal C2 following into the model's forward C0/C1 pose."""
-
-  def __init__(self, dt: float = 0.01):
-    self.dt = dt
-    self._last_path = FordPath(valid=True)
-    self._curvature_history = deque(maxlen=max(round(_POSE_PREDICTION_TIME / dt) + 1, 2))
-
-  def _limit(self, target: FordPath) -> FordPath:
-    offset_delta = target.path_offset - self._last_path.path_offset
-    angle_delta = target.path_angle - self._last_path.path_angle
-    scale = min(
-      1.0,
-      _PATH_OFFSET_RATE * self.dt / abs(offset_delta) if offset_delta else 1.0,
-      _PATH_ANGLE_RATE * self.dt / abs(angle_delta) if angle_delta else 1.0,
-    )
-    self._last_path = FordPath(
-      True,
-      self._last_path.path_offset + scale * offset_delta,
-      self._last_path.path_angle + scale * angle_delta,
-      self._last_path.curvature + scale * (target.curvature - self._last_path.curvature),
-      0.0,
-    )
-    return self._last_path
-
-  def update(self, model, desired_curvature: float, *, current_curvature: float = 0.0,
-             v_ego: float = 0.0, active: bool = True) -> FordPath:
-    if not active:
-      self._last_path = FordPath(valid=True)
-      self._curvature_history.clear()
-      return FordPath()
-    current_curvature = _finite(current_curvature)
-    self._curvature_history.append(current_curvature)
-    curvature_delta = (current_curvature - self._curvature_history[0]
-                       if len(self._curvature_history) == self._curvature_history.maxlen else 0.0)
-    path = _model_path(model) if model is not None else None
-    if path is None:
-      return self._limit(FordPath(valid=True))
-    return self._limit(_encode_path(path, _finite(desired_curvature), current_curvature, curvature_delta,
-                                    max(_finite(v_ego), 0.0)))
-
-
-def _pscm_slew(value: float, target: float, rate: float, ticks: int) -> float:
-  step = rate * _PSCM_DT * ticks
-  return float(np.clip(target, value - step, value + step))
-
-
-def _pscm_speed_gain(v_ego: float) -> float:
-  return float(np.interp(max(v_ego, 0.0) * 3.6, _PSCM_SPEED_KPH, _PSCM_SPEED_GAIN))
-
-
-def _wire_path(path: FordPath) -> FordPath:
-  return FordPath(
-    valid=path.valid,
-    path_offset=round(path.path_offset / DBC_OFFSET_RESOLUTION) * DBC_OFFSET_RESOLUTION,
-    path_angle=round(path.path_angle / DBC_ANGLE_RESOLUTION) * DBC_ANGLE_RESOLUTION,
-    curvature=round(path.curvature / DBC_CURVATURE_RESOLUTION) * DBC_CURVATURE_RESOLUTION,
-    curvature_rate=round(path.curvature_rate / DBC_CURVATURE_RATE_RESOLUTION) * DBC_CURVATURE_RATE_RESOLUTION,
-  )
-
-
-def _pscm_contributions(state: FordPscmState, v_ego: float) -> tuple[float, float, float]:
-  gain = _pscm_speed_gain(v_ego)
-  return (
-    float(np.clip(0.5 * gain * state.path_offset, -0.5 * gain, 0.5 * gain)),
-    float(np.clip(10.0 * gain * state.path_angle, -0.349609375 * gain, 0.349609375 * gain)),
-    float(np.clip(0.30078125 * gain * state.curvature * v_ego ** 2, -0.5 * gain, 0.5 * gain)),
-  )
-
-
-class FordPscmObserver:
-  """Mirror the firmware's held-command coefficient states at its 250 Hz step."""
-
-  def __init__(self):
-    self.state = FordPscmState()
-    self.command = FordPath(valid=True)
-    self._phase = 0.0
-
-  def reset(self) -> None:
-    self.state = FordPscmState()
-    self.command = FordPath(valid=True)
-    self._phase = 0.0
-
-  def advance(self, elapsed: float) -> None:
-    self._phase += max(elapsed, 0.0)
-    ticks = int((self._phase + 1e-12) / _PSCM_DT)
-    self._phase -= ticks * _PSCM_DT
-    if ticks == 0:
-      return
-    self.state = FordPscmState(
-      _pscm_slew(self.state.path_offset, self.command.path_offset, _PSCM_C0_RATE, ticks),
-      _pscm_slew(self.state.path_angle, self.command.path_angle, _PSCM_C1_RATE, ticks),
-      _pscm_slew(self.state.curvature, self.command.curvature + 10.0 * self.command.curvature_rate,
-                  _PSCM_C2_RATE, ticks),
-    )
-
-  def set_command(self, command: FordPath) -> None:
-    self.command = _wire_path(command)
-
-
-class FordPscmObserverPathController:
-  """Compensate model-path commands for the PSCM coefficient state it still carries."""
-
-  def __init__(self, dt: float = 0.01):
-    self.dt = dt
-    self._last_path = FordPath(valid=True)
-    self._curvature_history = deque(maxlen=max(round(_POSE_PREDICTION_TIME / dt) + 1, 2))
-    self.observer = FordPscmObserver()
-    self._sent_c2 = 0.0
-
-  def _reset(self) -> None:
-    self._last_path = FordPath(valid=True)
-    self._curvature_history.clear()
-    self.observer.reset()
-    self._sent_c2 = 0.0
-
-  def _command_for_state(self, target: FordPath, v_ego: float) -> FordPath:
-    # The target describes the desired fully-settled PSCM contribution. C0 keeps
-    # the remaining C1-saturated residual. C1 supplies the primary contribution
-    # that the known slow C2 state does not yet provide, without a guessed gain.
-    target_state = FordPscmState(target.path_offset, target.path_angle, target.curvature)
-    target_contribution = sum(_pscm_contributions(target_state, v_ego))
-    _, _, observed_c2 = _pscm_contributions(self.observer.state, v_ego)
-    gain = _pscm_speed_gain(v_ego)
-    required_fast = target_contribution - observed_c2
-    c1_contribution = float(np.clip(required_fast, -0.349609375 * gain, 0.349609375 * gain))
-    c0_contribution = required_fast - c1_contribution
-    path_offset = c0_contribution / (0.5 * gain) if gain > 0.0 else 0.0
-    path_angle = c1_contribution / (10.0 * gain) if gain > 0.0 else 0.0
-    return FordPath(
-      valid=True,
-      path_offset=float(np.clip(path_offset, -_PSCM_C0_EFFECTIVE_LIMIT, _PSCM_C0_EFFECTIVE_LIMIT)),
-      path_angle=float(np.clip(path_angle, -_PSCM_C1_EFFECTIVE_LIMIT, _PSCM_C1_EFFECTIVE_LIMIT)),
-      curvature=target.curvature,
-      curvature_rate=target.curvature_rate,
-    )
-
-  def _limit(self, target: FordPath, v_ego_raw: float) -> FordPath:
-    path_offset = float(np.clip(target.path_offset,
-                                self._last_path.path_offset - _PATH_OFFSET_RATE * self.dt,
-                                self._last_path.path_offset + _PATH_OFFSET_RATE * self.dt))
-    path_angle = float(np.clip(target.path_angle,
-                               self._last_path.path_angle - _PATH_ANGLE_RATE * self.dt,
-                               self._last_path.path_angle + _PATH_ANGLE_RATE * self.dt))
-    curvature = CarControllerParams.CURVATURE_LIMITS.apply_limits(
-      target.curvature, self._sent_c2, v_ego_raw, 0.0, True, CarControllerParams.LMC2_STEP,
-    )
-    self._sent_c2 = curvature
-    self._last_path = FordPath(True, path_offset, path_angle, curvature, target.curvature_rate)
-    self.observer.set_command(self._last_path)
-    return self._last_path
-
-  def update(self, model, desired_curvature: float, *, current_curvature: float = 0.0,
-             v_ego: float = 0.0, v_ego_raw: float = 0.0, active: bool = True) -> FordPath:
-    if not active:
-      self._reset()
-      return FordPath()
-
-    self.observer.advance(self.dt)
-    current_curvature = _finite(current_curvature)
-    self._curvature_history.append(current_curvature)
-    curvature_delta = (current_curvature - self._curvature_history[0]
-                       if len(self._curvature_history) == self._curvature_history.maxlen else 0.0)
-    path = _model_path(model) if model is not None else None
-    if path is None:
-      target = FordPath(valid=True)
-    else:
-      target = _encode_path(path, _finite(desired_curvature), current_curvature, curvature_delta,
-                            max(_finite(v_ego), 0.0))
-    v_ego_raw = max(_finite(v_ego_raw), 0.0)
-    command = self._command_for_state(target, v_ego_raw)
-    return self._limit(command, v_ego_raw)
@@ -1,308 +0,0 @@
-"""C2-free curvature requests with bounded yaw tracking for the Lightning RL38 PSCM.
-
-The historical Virtual Angle name/key is retained for settings compatibility.
-C0/C1 remain path geometry, never a fitted wheel-angle or torque command.
-"""
-from collections import deque
-from dataclasses import dataclass
-import math
-import struct
-import numpy as np
-
-from openpilot.selfdrive.controls.lib.ford_path import FordPath, _model_path, _relative_pose, _predicted_pose
-from opendbc.car.ford.values import CarControllerParams, FordFlags
-
-
-FEEDBACK_MIN_SPEED = 2.0
-HEADING_RESOLUTION = .0005
-
-
-def _packed(value, resolution, offset):
-  """Mirror Float32 carControlSP and sign-reversed CANPacker rounding."""
-  value = struct.unpack("f", struct.pack("f", value))[0]
-  return -(math.floor((-value - offset) / resolution + 0.5) * resolution + offset)
-
-
-@dataclass(frozen=True)
-class PathTuning:
-  filter_time: float = 0.3
-  offset_horizon: float = 8.0
-  heading_horizon: float = 7.0
-  heading_time: float = 1.0
-  offset_rate: float = 4.0
-  heading_rate: float = 0.5
-  feedback_gain: float = 1.0
-
-
-@dataclass(frozen=True)
-class PscmStatus:
-  timestamp: float
-  lateral_state: int
-  limit: int
-  capability: int
-  denied: bool
-  valid: bool = True
-
-  def invalid_reason(self, now):
-    if not self.valid or not math.isfinite(self.timestamp) or any(v not in (0, 1, 2, 3) for v in (
-      self.lateral_state, self.limit, self.capability,
-    )):
-      return 'invalid_pscm'
-    if not -.005 <= now - self.timestamp <= .15:
-      return 'stale_pscm'
-    if self.denied or self.lateral_state != 2 or self.capability not in (1, 2):
-      return 'unavailable_pscm'
-    return None
-
-
-class HeadingFeedback:
-  """Bound a heading correction using measured yaw error, not an EPS gain fit.
-
-  The nominal response interval, integration gain and low-speed policy remain
-  experimental. A downstream limit report cannot identify motor effort from
-  the sign of C1 while C0 and the PSCM's own controller are also acting.
-  """
-  def __init__(self, delay, tuning):
-    self.delay, self.tuning = delay, tuning
-    self.reset()
-
-  def reset(self, status='inactive'):
-    self.history = deque()
-    self.bias = 0.
-    self.previous_base = None
-    self.last_measurement_time = self.last_pscm_time = None
-    self.diagnostics = {'heading_bias': 0., 'feedback_status': status, 'feedback_reference_time': None,
-                        'feedback_reference_curvature': None, 'feedback_yaw_error': None}
-
-  def update(self, base, desired, *, yaw_rate, speed, now, measurement_time, dt, previous_command, heading_horizon, driver_override, pscm_status):
-    reason = ('missing_pscm' if pscm_status is None else pscm_status.invalid_reason(now))
-    if reason is None and self.last_pscm_time is not None and pscm_status.timestamp < self.last_pscm_time:
-      reason = 'pscm_timing'
-    if reason is None:
-      reason = ('driver_override' if driver_override or pscm_status.limit == 3 else 'low_speed' if speed < FEEDBACK_MIN_SPEED else
-                'zero_request' if base == 0. else 'disabled' if self.tuning.feedback_gain == 0. else None)
-    if reason is not None:
-      self.reset(reason)
-      return base
-
-    if self.previous_base is not None and base * self.previous_base < 0.:
-      self.reset('reversal')
-    elif self.previous_base and abs(base) < abs(self.previous_base):
-      # Releasing a clipped base, rather than raw curvature, avoids increasing
-      # total C1 by shrinking a negative correction while the base stays capped.
-      self.bias *= abs(base / self.previous_base)
-    self.previous_base = base
-    self.last_pscm_time = pscm_status.timestamp
-    self.history.append((now, desired))
-    while len(self.history) > 2 and self.history[1][0] < now - self.delay - .25:
-      self.history.popleft()
-
-    status = 'no_new_measurement'
-    reference_time = reference_curvature = yaw_error = None
-    if measurement_time != self.last_measurement_time:
-      measurement_dt = 0. if self.last_measurement_time is None else measurement_time - self.last_measurement_time
-      self.last_measurement_time = measurement_time
-      target_time = measurement_time - self.delay
-      # Use the command actually held at the historical instant. Interpolating
-      # toward a later publication would compare against a different request.
-      reference = next((sample for sample in reversed(self.history) if sample[0] <= target_time), None)
-      if reference is None:
-        status = 'history'
-      elif not .002 <= measurement_dt <= .1:
-        status = 'measurement_timing'
-      else:
-        reference_time, reference_curvature = reference
-        yaw_error = speed * reference_curvature - yaw_rate
-        releasing = reference_curvature * desired <= 0. or (abs(reference_curvature) - abs(desired)) * heading_horizon > HEADING_RESOLUTION
-        if releasing:
-          status = 'release'
-        elif pscm_status.limit >= 2:
-          # Freeze all integration: C1 direction is not measured motor effort.
-          # Base-driven release still removes stored demand as the action eases.
-          status = 'pscm_limit'
-        else:
-          increment = self.tuning.feedback_gain * yaw_error * measurement_dt
-          proposed = base + self.bias + increment
-          field_limited = float(np.clip(proposed, -.5, .5))
-          host_limited = previous_command + float(np.clip(field_limited - previous_command,
-                                                          -self.tuning.heading_rate * dt, self.tuning.heading_rate * dt))
-          # Admit the reachable portion of an outward increment, rather than
-          # freezing forever when a large/batched error exceeds one tick's slew.
-          # A base transition must not fabricate a correction opposite the error.
-          if yaw_error * (proposed - host_limited) > 1e-12:
-            self.bias += float(np.clip(host_limited - (base + self.bias), min(0., increment), max(0., increment)))
-            status = 'host_limit'
-          else:
-            self.bias += increment
-            status = 'integrating'
-    self.bias = float(np.clip(self.bias, -.5 - base, .5 - base))
-    self.diagnostics = {'heading_bias': self.bias, 'feedback_status': status, 'feedback_reference_time': reference_time,
-                        'feedback_reference_curvature': reference_curvature, 'feedback_yaw_error': yaw_error}
-    return float(np.clip(base + self.bias, -.5, .5))
-
-
-class PathReference:
-  """Retain model geometry in the current ego frame between model messages."""
-  def __init__(self, tuning):
-    self.tuning = tuning
-    self.path = None
-    self.model_time = None
-
-  def reset(self):
-    self.path = None
-    self.model_time = None
-
-  @staticmethod
-  def advance(path, distance, curvature):
-    stations, x, y, heading = path
-    dx, dy, yaw = _predicted_pose(distance, curvature, 0.0)
-    cosine, sine = math.cos(yaw), math.sin(yaw)
-    return stations - distance, cosine * (x - dx) + sine * (y - dy), -sine * (x - dx) + cosine * (y - dy), heading - yaw
-
-  def update(self, model, *, model_time, now, dt, speed, curvature):
-    if self.path is not None:
-      self.path = self.advance(self.path, speed * dt, curvature)
-    if model_time == self.model_time:
-      return self.path
-    raw = _model_path(model)
-    if raw is None or not all(np.isfinite(a).all() for a in raw):
-      self.reset()
-      return None
-    new = self.advance(tuple(np.array(a) for a in raw), speed * max(now - model_time, 0.0), curvature)
-    if self.path is not None:
-      # Both paths now describe the same ego frame and traveled arc. Only the
-      # model innovation is filtered; measured ego motion is accounted for at
-      # every control tick. Never average two unaligned vehicle-frame paths.
-      elapsed = model_time - self.model_time
-      alpha = elapsed / (self.tuning.filter_time + elapsed)
-      old = self.path
-      values = [new[0]]
-      for index in (1, 2, 3):
-        prior = np.interp(new[0], old[0], old[index])
-        delta = new[index] - prior
-        if index == 3:
-          delta = (delta + np.pi) % (2 * np.pi) - np.pi
-        values.append(prior + alpha * delta)
-      # Do not invent reference history beyond the previous path's coverage.
-      outside = (new[0] < old[0][0]) | (new[0] > old[0][-1])
-      for index in (1, 2, 3):
-        values[index][outside] = new[index][outside]
-      new = tuple(values)
-    self.path = new
-    self.model_time = model_time
-    return self.path
-
-
-class FordVirtualAngleController:
-  """Encode the same absolute planned curvature as C0 and C1.
-
-  The former spatial-heading reference is retained for diagnostic comparison
-  and the existing input-validity gates. A bounded yaw-error integral corrects
-  C1 when fresh PSCM status permits; no fixed EPS gain is assumed.
-  """
-  def __init__(self, response_delay=.2, tuning: PathTuning | None = None):
-    self.tuning = tuning if tuning is not None else PathTuning()
-    if not math.isfinite(response_delay) or not .05 <= response_delay <= .5:
-      raise ValueError("response delay must be within 0.05..0.5 seconds")
-    if not all(math.isfinite(v) and v >= 0 for v in vars(self.tuning).values()) or min(
-      self.tuning.offset_horizon, self.tuning.heading_horizon, self.tuning.heading_time, self.tuning.offset_rate, self.tuning.heading_rate,
-    ) <= 0:
-      raise ValueError("invalid path tuning")
-    self.delay = response_delay
-    self.reference = PathReference(self.tuning)
-    self.feedback = HeadingFeedback(self.delay, self.tuning)
-    self.reset()
-
-  def reset(self):
-    self.reference.reset()
-    self.feedback.reset()
-    self.command = FordPath()
-    self.last_time = None
-    self.last_measurement_time = None
-    self.offset_request = self.heading_request = 0.0
-    self.diagnostics = {'status': 'inactive', 'hypothesis': 'curvature-c0-c1-feedback-v5', 'command': (0., 0., 0., 0.),
-                        **self.feedback.diagnostics}
-
-  def update(self, model, desired_curvature, *, yaw_rate, speed, now, measurement_time, model_time, reference_time,
-             active, valid=True, steering_pressed=False, steering_torque=0., pscm_status: PscmStatus | None = None):
-    finite = all(math.isfinite(v) for v in (desired_curvature, yaw_rate, speed, now, measurement_time, model_time, reference_time))
-    fresh = finite and all(-.005 <= now - timestamp <= .15 for timestamp in (measurement_time, model_time, reference_time))
-    if not active or not valid or model is None or not fresh or not .3 <= speed <= 55 or abs(yaw_rate) > 3 or abs(desired_curvature) > 1:
-      self.reset()
-      self.diagnostics['status'] = 'inactive' if not active else 'invalid_input'
-      self.diagnostics['reason'] = ('inactive' if not active else 'invalid_service' if not valid else 'missing_model' if model is None else
-                                    'nonfinite' if not finite else 'stale_input' if not fresh else 'speed' if not .3 <= speed <= 55 else
-                                    'yaw_rate' if abs(yaw_rate) > 3 else 'desired_curvature')
-      return self.command
-    dt = .01 if self.last_time is None else now - self.last_time
-    if not .002 <= dt <= .1 or (self.last_measurement_time is not None and measurement_time < self.last_measurement_time) or (
-      self.reference.model_time is not None and model_time < self.reference.model_time
-    ):
-      self.reset()
-      self.diagnostics['status'] = 'timing_reset'
-      return self.command
-    current_curvature = yaw_rate / speed
-    self.last_time = now
-    self.last_measurement_time = measurement_time
-    path = self.reference.update(model, model_time=model_time, now=now, dt=dt, speed=speed, curvature=current_curvature)
-    if path is None or path[0][-1] <= 0:
-      self.reset()
-      self.diagnostics['status'] = 'invalid_path'
-      return self.command
-    advance = min(speed * self.delay, path[0][-1])
-    offset_horizon = max(self.tuning.offset_horizon, speed * self.tuning.heading_time)
-    heading_horizon = max(speed * self.tuning.heading_time, self.tuning.heading_horizon)
-    model_heading_horizon = min(heading_horizon, max(path[0][-1] - advance, 0.0))
-    ego = _predicted_pose(advance, current_curvature, 0.)
-    _, model_heading = _relative_pose(advance + model_heading_horizon, path, ego)
-    # The selected action already contains the planner's steering correction and
-    # upstream delay handling. Encode absolute curvature as a virtual parabolic
-    # displacement; measured curvature must not erase a sustained turn request.
-    # This preview sets command scale, not a model of the PSCM's wheel response.
-    offset = .5 * desired_curvature * offset_horizon ** 2
-    target_offset = float(np.clip(offset, -5.11, 5.11))
-    # Absolute feedforward retains sustained turn demand. Measured tracking can
-    # add or subtract a bounded correction; model geometry remains diagnostic.
-    base_heading = float(np.clip(desired_curvature * heading_horizon, -.5, .5))
-    driver_override = steering_pressed or not math.isfinite(steering_torque) or abs(steering_torque) > CarControllerParams.STEER_DRIVER_ALLOWANCE
-    target_heading = self.feedback.update(base_heading, desired_curvature, yaw_rate=yaw_rate, speed=speed, now=now,
-                                          measurement_time=measurement_time, dt=dt, previous_command=self.heading_request,
-                                          heading_horizon=heading_horizon, driver_override=driver_override, pscm_status=pscm_status)
-    delta_offset = target_offset - self.offset_request
-    delta_heading = target_heading - self.heading_request
-    # A slow C1 transition must not hold a C0 correction after action releases it.
-    offset_scale = min(1., self.tuning.offset_rate * dt / abs(delta_offset)) if delta_offset else 1.
-    heading_scale = min(1., self.tuning.heading_rate * dt / abs(delta_heading)) if delta_heading else 1.
-    self.offset_request += offset_scale * delta_offset
-    self.heading_request += heading_scale * delta_heading
-    offset = _packed(self.offset_request, .01, -5.12)
-    heading = _packed(self.heading_request, .0005, -.5)
-    self.command = FordPath(True, offset, heading, 0., 0.)
-    self.diagnostics = {'status': 'driver_override' if driver_override else 'active', 'hypothesis': 'curvature-c0-c1-feedback-v5',
-                        'desired_curvature': desired_curvature, 'offset_target': target_offset, 'heading_target': target_heading,
-                        'heading_base': base_heading, 'feedback_gain': self.tuning.feedback_gain, 'feedback_min_speed': FEEDBACK_MIN_SPEED,
-                        'steering_torque': steering_torque if math.isfinite(steering_torque) else None,
-                        'pscm_valid': pscm_status.valid if pscm_status is not None else False,
-                        'pscm_timestamp': pscm_status.timestamp if pscm_status is not None and math.isfinite(pscm_status.timestamp) else None,
-                        'pscm_age': now - pscm_status.timestamp if pscm_status is not None and math.isfinite(pscm_status.timestamp) else None,
-                        'pscm_limit': pscm_status.limit if pscm_status is not None else None,
-                        'pscm_capability': pscm_status.capability if pscm_status is not None else None,
-                        'pscm_lateral_state': pscm_status.lateral_state if pscm_status is not None else None,
-                        'pscm_denied': pscm_status.denied if pscm_status is not None else None,
-                        **self.feedback.diagnostics,
-                        'model_heading_target': float(np.clip(model_heading, -.5, .5)), 'model_heading_horizon': model_heading_horizon,
-                        'offset_slew_scale': offset_scale, 'heading_slew_scale': heading_scale,
-                        'measurement_age': now - measurement_time, 'model_age': now - model_time, 'reference_age': now - reference_time,
-                        'response_delay': self.delay, 'reference_filter_time': self.tuning.filter_time, 'yaw_rate': yaw_rate,
-                        'offset_horizon': offset_horizon, 'heading_horizon': heading_horizon,
-                        'command': (offset, heading, 0., 0.)}
-    return self.command
-
-
-def select_virtual_angle_controller(CP, enabled, previous_controller):
-  # The Sunnylink toggle selects this controller on the Lightning even when
-  # the startup firmware query omits EPS identification.
-  compatible = CP.brand == 'ford' and CP.flags & FordFlags.CANFD and CP.carFingerprint == 'FORD_F_150_LIGHTNING_MK1'
-  if enabled and compatible:
-    return FordVirtualAngleController(CP.steerActuatorDelay)
-  return previous_controller
@@ -1,229 +0,0 @@
-{
-  "description": "Curvature-driven C0 and full-heading C1 command regression; does not predict counterfactual wheel response. Contains geometry and control signals only, no GPS.",
-  "fixture_sha256": "12782ac1b0d0637945f729a46ad03af16cd58188872b6a65f104e32c4db70e9b",
-  "episodes": [
-    {
-      "name": "left_large",
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-      "range_seconds": [
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-      "evidence_seconds": [
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-      "samples": 532
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-    {
-      "name": "right_large",
-      "route": "84865544361f55cb_00000077--4b55791ce6",
-      "range_seconds": [
-        866.5,
-        872.0
-      ],
-      "evidence_seconds": [
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-        871.0
-      ],
-      "samples": 547
-    },
-    {
-      "name": "left_very_large",
-      "route": "84865544361f55cb_00000077--4b55791ce6",
-      "range_seconds": [
-        880.0,
-        884.0
-      ],
-      "evidence_seconds": [
-        882.9,
-        883.32
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-      "samples": 397
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-    {
-      "name": "right_plateau",
-      "route": "84865544361f55cb_00000077--4b55791ce6",
-      "range_seconds": [
-        964.0,
-        970.0
-      ],
-      "evidence_seconds": [
-        967.2,
-        968.93
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-      "samples": 583
-    },
-    {
-      "name": "oscillation",
-      "route": "84865544361f55cb_00000078--349f5b8695",
-      "range_seconds": [
-        29.0,
-        37.0
-      ],
-      "evidence_seconds": [
-        32.5,
-        36.1
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-      "samples": 795
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-    {
-      "name": "weak_first",
-      "route": "84865544361f55cb_0000007a--5a95fc717e",
-      "range_seconds": [
-        90.5,
-        95.2
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-      "evidence_seconds": [
-        93.5,
-        95.08
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-      "samples": 467
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-    {
-      "name": "weak_second",
-      "route": "84865544361f55cb_0000007a--5a95fc717e",
-      "range_seconds": [
-        119.5,
-        125.3
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-      "evidence_seconds": [
-        122.5,
-        125.2
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-      "samples": 576
-    }
-  ],
-  "sources": {
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-    "84865544361f55cb_00000078--349f5b8695": [
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-        "bytes": 10919702,
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-    "84865544361f55cb_0000007a--5a95fc717e": [
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-        "bytes": 12567837,
-        "sha256": "ab9eb05c5805e286a6ec639bbbbc1cf086bfcf1b440801ad000713db95dfa7fc"
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-        "bytes": 11015857,
-        "sha256": "af4f87f39be37f0a5b23b58de50c2ed8801bdbda6544cd6cd292525fc3bd4fb3"
-      }
-    ]
-  },
-  "pairing": "controlsState cycle time; causal carState speed/yaw/pressed; exact consumed model timestamp and geometry; nearest same-cycle carControl and carControlSP within 5ms.",
-  "yaw_rate": "Negative carState.yawRate, matching the model/control curvature coordinate sign; no wheel-to-curvature conversion.",
-  "desired_curvature": "Exact controlsState.desiredCurvature from the matching controlsState cycle. This is the post-selection, post-limiting request consumed by controlsd; it is not a wheel-angle-to-curvature fit.",
-  "reference_time": "Exact consumed modelV2 publication time, in the same relative seconds as each episode. The extraction cache does not retain consumed lateralManeuverPlan timestamps or validity; model time is an explicit replay assumption and cannot verify alternate-reference freshness."
-}
@@ -1,67 +0,0 @@
-{
-  "description": "Real route80 turn-command regressions. Signal-only fixture; no GPS. Counterfactual commands do not predict physical vehicle response.",
-  "route": "84865544361f55cb_00000080--1643deea7e",
-  "source_commit": "98662df401217a00ec9fc8e73b16857b6c220150",
-  "frozen_v3_controller_sha256": "576f4ec6f2dbc93f7e6c93a69839f69447eb5a0c2f834bd48b24f84a163dc2eb",
-  "fixture_sha256": "c1460e2cf1d3fd52b1a036d923fec7835a7d361126ee0c2decbc3f101ee6653c",
-  "episodes": [
-    {
-      "name": "under_333_339",
-      "range_seconds": [
-        331.5,
-        339.0
-      ],
-      "evidence_seconds": [
-        333.0,
-        339.0
-      ],
-      "samples": 745
-    },
-    {
-      "name": "over_417_420",
-      "range_seconds": [
-        415.5,
-        420.0
-      ],
-      "evidence_seconds": [
-        417.0,
-        420.0
-      ],
-      "samples": 447
-    },
-    {
-      "name": "under_430_435",
-      "range_seconds": [
-        428.5,
-        435.0
-      ],
-      "evidence_seconds": [
-        430.0,
-        435.0
-      ],
-      "samples": 646
-    }
-  ],
-  "sources": [
-    {
-      "name": "84865544361f55cb_00000080--1643deea7e--5--rlog.zst",
-      "bytes": 12531711,
-      "sha256": "059482830794cb0eabe6069b75a9610b900bf2a93d7a6624f53c575cef997157"
-    },
-    {
-      "name": "84865544361f55cb_00000080--1643deea7e--6--rlog.zst",
-      "bytes": 12560505,
-      "sha256": "147276789f5b14913adc4cd16db18f3d4bd27ce8497c9ff96fdf0315c219339f"
-    },
-    {
-      "name": "84865544361f55cb_00000080--1643deea7e--7--rlog.zst",
-      "bytes": 12660797,
-      "sha256": "b311b6ace75819db52b9618154d68c7d12e2751d5046b6d174adb89ef87a223c"
-    }
-  ],
-  "pairing": "Exact controlsState desiredCurvature and consumed model publication timestamp; causal carState speed, negative CAN yaw, and steeringPressed; nearest same-cycle carControl/carControlSP within 5 ms.",
-  "reference_time": "Consumed modelV2 publication time. Controller audit confirms route80 used modelV2 as reference throughout.",
-  "preroll": "Each episode starts from reset 1.5 s before evidence; v3_replay stores those exact cold-start commands and gates, while recorded stores original live path fields.",
-  "benchmark_clean": "Existing route80 benchmark mask: whole interval request minus 0.5 s through response (0.2 s) plus 0.25 s active, unpressed, valid, fresh, and speed >= 2 m/s.",
-  "expected_common_c1": "Independent shadow: clip(desiredCurvature * max(7 m, vEgo * 1 s), +/-0.5 rad), independently slewed at 0.5 rad/s and packed to Float32/sign-reversed CAN semantics. No subtraction of measured curvature."
-}
@@ -1,13 +0,0 @@
-{
-  "description": "PSCM status and raw driver-torque overlay for the existing three route80 request windows. No GPS. No counterfactual vehicle response.",
-  "fixture_sha256": "a9defdc5abdf26724358d606beb16becbdf30faa972974d49b179a9e004d7629",
-  "base_fixture": "ford_curvature_heading_route80.npz",
-  "base_fixture_sha256": "c1460e2cf1d3fd52b1a036d923fec7835a7d361126ee0c2decbc3f101ee6653c",
-  "source_route": "84865544361f55cb_00000080--1643deea7e",
-  "source_commit": "98662df401217a00ec9fc8e73b16857b6c220150",
-  "samples": 1838,
-  "source_cache_sha256": "1cd3e0c00805869ace1c5954dc682644f36f5eddb71785b69e4cb9da40f7f04f",
-  "pairing": "Latest actual bus-0 EPS 972 frame at or before each controlsState cycle; raw steering torque from the exact causal carState used by the base fixture.",
-  "timestamp_policy": "Actual CAN event logMonoTime in route-relative seconds, not the benchmark response-shifted status. The old route predates the new carStateSP status telemetry; source CAN timestamps are an explicit replay approximation.",
-  "validity": "Replay validity uses the paired carState valid and canValid values; enum validity, availability and age are checked by the production feedback controller."
-}
@@ -1,185 +0,0 @@
-import ast
-import io
-import json
-import logging
-from pathlib import Path
-from types import SimpleNamespace
-import unittest
-from unittest.mock import Mock
-
-from openpilot.cereal import custom
-from openpilot.common.logging_extra import SwagFormatter, SwagLogger
-from openpilot.selfdrive.controls.lib.ford_path import FordPathController, FordPscmObserverPathController
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController, PscmStatus
-from openpilot.selfdrive.controls.tests.test_ford_path_reference import circle
-
-
-class TestFordControlsLogging(unittest.TestCase):
-  def emit_controls_event(self, event, controls):
-    # Execute the actual controlsd call with the real logger and formatter,
-    # without launching hardware-dependent Controls or opening logging IPC.
-    source_path = Path(__file__).resolve().parents[1] / 'controlsd.py'
-    source = ast.parse(source_path.read_text())
-    calls = [node for node in ast.walk(source) if isinstance(node, ast.Call)
-             and isinstance(node.func, ast.Attribute) and isinstance(node.func.value, ast.Name)
-             and node.func.value.id == 'cloudlog' and node.args
-             and isinstance(node.args[0], ast.Constant) and node.args[0].value == event]
-    self.assertEqual(len(calls), 1)
-    logger = SwagLogger()
-    logger.setLevel(logging.INFO)  # disabled INFO logging would hide this crash
-    stream = io.StringIO()
-    handler = logging.StreamHandler(stream)
-    handler.setFormatter(SwagFormatter(logger))
-    logger.addHandler(handler)
-    try:
-      expression = ast.Expression(body=calls[0])
-      eval(compile(expression, str(source_path), 'eval'), {'cloudlog': logger, 'self': controls, 'reference_service': 'modelV2'})
-      record = json.loads(stream.getvalue())
-    finally:
-      handler.close()
-    self.assertEqual(record['level'], 'INFO')
-    self.assertEqual(record['msg']['event'], event)
-    return record['msg']
-
-  def test_startup_logs_selected_controller_without_crashing(self):
-    for controller in (FordPathController(), FordPscmObserverPathController(), FordVirtualAngleController()):
-      with self.subTest(controller=type(controller).__name__):
-        record = self.emit_controls_event('Ford path controller selected', SimpleNamespace(ford_path_controller=controller))
-        self.assertEqual(record['controller'], type(controller).__name__)
-
-  def test_periodic_diagnostics_log_without_crashing(self):
-    controller = FordVirtualAngleController()
-    for active, valid, pressed in ((False, True, False), (True, True, False), (True, True, True), (True, False, False)):
-      controller.reset()
-      controller.update(circle(.01), .01, yaw_rate=.05, speed=10.0, now=1.0,
-                        measurement_time=1.0, model_time=1.0, reference_time=1.0, active=active,
-                        valid=valid, steering_pressed=pressed)
-      controls = SimpleNamespace(ford_path_controller=controller, desired_curvature=.01, curvature=.005,
-                                 sm=SimpleNamespace(logMonoTime={'modelV2': 123456789, 'carState': 123450000}))
-      record = self.emit_controls_event('Ford C2-free path tracking', controls)
-      self.assertEqual(record['model_mono_time'], 123456789)
-      self.assertEqual(record['measurement_mono_time'], 123450000)
-      self.assertEqual(record['reference_service'], 'modelV2')
-      self.assertEqual(record['reference_mono_time'], 123456789)
-      self.assertEqual(record['status'], controller.diagnostics['status'])
-      self.assertEqual(record['hypothesis'], 'curvature-c0-c1-feedback-v5')
-      self.assertEqual(record['command'], list(controller.diagnostics['command']))
-      if active and valid:
-        self.assertEqual(record['response_delay'], 0.2)
-        self.assertEqual(record['desired_curvature'], 0.01)
-        self.assertEqual(record['measured_curvature'], 0.005)
-        self.assertAlmostEqual(record['heading_target'], .1)
-        self.assertTrue(all(key in record for key in ('offset_target', 'heading_target', 'model_heading_target', 'model_heading_horizon',
-                                                    'model_age', 'reference_age', 'reference_filter_time')))
-
-  def test_actual_ford_branch_uses_selected_reference_and_disables_invalid_output(self):
-    source_path = Path(__file__).resolve().parents[1] / 'controlsd.py'
-    source = ast.parse(source_path.read_text())
-    controls_class = next(n for n in source.body if isinstance(n, ast.ClassDef) and n.name == 'Controls')
-    state_control = next(n for n in controls_class.body if isinstance(n, ast.FunctionDef) and n.name == 'state_control')
-    branch = next(n for n in state_control.body if isinstance(n, ast.If) and ast.unparse(n.test) == "self.CP.brand == 'ford'")
-    code = compile(ast.Module(body=[branch], type_ignores=[]), str(source_path), 'exec')
-
-    class Subscriptions:
-      frame = 1  # periodic logging is covered separately
-      valid = {'lateralManeuverPlan': False, 'modelV2': True, 'carStateSP': True}
-      logMonoTime = {'carState': 995_000_000, 'modelV2': 980_000_000, 'lateralManeuverPlan': 990_000_000, 'carStateSP': 998_000_000}
-      failed_checks = set()
-
-      def __init__(self):
-        self.state_sp = custom.CarStateSP.new_message()
-        self.state_sp.fordPscmStatus = {'valid': True, 'canMonoTime': 970_000_000, 'lateralState': 2,
-                                      'limit': 1, 'capability': 2, 'denied': False}
-
-      def __getitem__(self, service):
-        if service == 'carStateSP':
-          return self.state_sp
-        raise KeyError(service)
-
-      def all_checks(self, services):
-        return all(self.valid.get(service, True) and service not in self.failed_checks for service in services)
-
-    for maneuver in (False, True):
-      sm = Subscriptions()
-      sm.valid = dict(sm.valid, lateralManeuverPlan=maneuver)
-      controller = FordVirtualAngleController()
-      controller.update = Mock(wraps=controller.update)
-      controls = SimpleNamespace(CP=SimpleNamespace(brand='ford'), sm=sm, ford_virtual_angle=True, ford_path_controller=controller,
-                                 desired_curvature=0.007, curvature=0.002, steer_limited_by_safety=True)
-      cs = SimpleNamespace(vEgo=8.0, yawRate=-.015, canValid=True, steeringPressed=False, steeringTorque=.75)
-      cc = SimpleNamespace(latActive=True)
-      actuator = SimpleNamespace(curvature=0.007)
-      environment = {'self': controls, 'CS': cs, 'CC': cc, 'actuators': actuator, 'model_v2': circle(.007),
-                     'time': SimpleNamespace(monotonic=lambda: 1.0), 'PscmStatus': PscmStatus}
-      exec(code, environment)
-      self.assertTrue(controls.ford_path.valid)
-      self.assertTrue(cc.latActive)
-      self.assertIs(controller.update.call_args.args[0], environment['model_v2'])
-      self.assertEqual(controller.update.call_args.args[1], controls.desired_curvature)
-      args = controller.update.call_args.kwargs
-      self.assertEqual(args['yaw_rate'], .015)
-      self.assertEqual(args['steering_torque'], .75)
-      status = args['pscm_status']
-      self.assertAlmostEqual(status.timestamp, .97)
-      self.assertEqual((status.lateral_state, status.limit, status.capability, status.denied, status.valid), (2, 1, 2, False, True))
-      self.assertAlmostEqual(args['measurement_time'], 0.995)
-      self.assertAlmostEqual(args['model_time'], 0.98)
-      reference_service = 'lateralManeuverPlan' if maneuver else 'modelV2'
-      self.assertAlmostEqual(args['reference_time'], sm.logMonoTime[reference_service] * 1e-9)
-      self.assertEqual(actuator.curvature, 0.0)
-
-      # C0 needs the selected action service; C1 independently needs modelV2.
-      # Reject stale/failed selected services rather than silently fall back or
-      # transmit an active zero path. A non-selected maneuver service is ignored.
-      for stale_service in {reference_service, 'modelV2'}:
-        with self.subTest(maneuver=maneuver, stale_service=stale_service):
-          controller.reset()
-          cc.latActive = True
-          sm.logMonoTime = dict(Subscriptions.logMonoTime, **{stale_service: 500_000_000})
-          exec(code, environment)
-          self.assertFalse(controls.ford_path.valid)
-          self.assertFalse(cc.latActive)
-          self.assertIsNone(controller.reference.path)
-
-      for failed_service in {reference_service, 'modelV2', 'carState', 'vehicleParameters'}:
-        with self.subTest(maneuver=maneuver, failed_service=failed_service):
-          controller.reset()
-          cc.latActive = True
-          sm.logMonoTime = Subscriptions.logMonoTime.copy()
-          sm.failed_checks = {failed_service}
-          exec(code, environment)
-          self.assertFalse(controller.update.call_args.kwargs['valid'])
-          self.assertFalse(controls.ford_path.valid)
-          self.assertFalse(cc.latActive)
-          self.assertIsNone(controller.reference.path)
-
-      if not maneuver:
-        controller.reset()
-        cc.latActive = True
-        sm.logMonoTime = dict(Subscriptions.logMonoTime, lateralManeuverPlan=500_000_000)
-        sm.failed_checks = {'lateralManeuverPlan'}
-        exec(code, environment)
-        self.assertTrue(controls.ford_path.valid)
-        self.assertTrue(cc.latActive)
-
-      # A missing, stale or invalid optional PSCM status must not disable the
-      # existing feedforward request. Feedback receives its own validity/age.
-      for fault in ('service', 'missing', 'stale_can'):
-        with self.subTest(maneuver=maneuver, pscm_fault=fault):
-          controller.reset()
-          cc.latActive = True
-          sm.logMonoTime = Subscriptions.logMonoTime.copy()
-          sm.failed_checks = {'carStateSP'} if fault == 'service' else set()
-          sm.state_sp.fordPscmStatus.valid = fault != 'missing'
-          sm.state_sp.fordPscmStatus.canMonoTime = 500_000_000 if fault == 'stale_can' else 970_000_000
-          exec(code, environment)
-          status = controller.update.call_args.kwargs['pscm_status']
-          self.assertEqual(status.valid, fault == 'stale_can')
-          self.assertAlmostEqual(status.timestamp, .5 if fault == 'stale_can' else .97)
-          self.assertTrue(controller.update.call_args.kwargs['valid'])
-          self.assertTrue(controls.ford_path.valid)
-          self.assertTrue(cc.latActive)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,85 +0,0 @@
-"""Action-to-C0 regressions; these do not simulate PSCM/vehicle response."""
-import math
-import unittest
-
-from openpilot.selfdrive.controls.lib.ford_path import FordPath
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController
-from openpilot.selfdrive.controls.tests.test_ford_path_reference import circle
-
-
-def step(controller, t, desired, model=None, speed=8., yaw_rate=0., **kwargs):
-  inputs = {'yaw_rate': yaw_rate, 'speed': speed, 'now': t, 'measurement_time': t,
-            'model_time': math.floor((t + 1e-6) / .05) * .05, 'reference_time': t, 'active': True}
-  inputs.update(kwargs)
-  return controller.update(circle() if model is None else model, desired, **inputs)
-
-
-class TestFordCurvatureC0(unittest.TestCase):
-  def test_centering_action_survives_an_ego_anchored_model(self):
-    for sign in (-1, 1):
-      controller = FordVirtualAngleController()
-      for i in range(200):
-        # Action can request recovery even when the short model preview is flat.
-        path = step(controller, i * .01, sign * .002, speed=20.)
-      self.assertAlmostEqual(path.path_offset, sign * .4, delta=.0051)
-      self.assertAlmostEqual(path.path_angle, sign * .04, delta=.000251)
-      self.assertEqual((path.curvature, path.curvature_rate), (0., 0.))
-
-  def test_slow_turns_retain_large_absolute_demand_after_curvature_matches(self):
-    for speed in (2., 4., 6.):
-      for sign in (-1, 1):
-        controller = FordVirtualAngleController()
-        for i in range(250):
-          path = step(controller, i * .01, sign * .04, circle(sign * .04), speed, sign * .04 * speed)
-        self.assertAlmostEqual(path.path_offset, sign * 1.28, delta=.0051)
-        self.assertGreater(sign * path.path_angle, .2)
-
-  def test_model_heading_cannot_inject_commands_when_action_requests_zero(self):
-    for sign in (-1, 1):
-      controller = FordVirtualAngleController()
-      for i in range(250):
-        path = step(controller, i * .01, 0., circle(sign * .12), speed=5.)
-      self.assertAlmostEqual(path.path_offset, 0., delta=.0051)
-      self.assertAlmostEqual(path.path_angle, 0., delta=.000251)
-      self.assertGreater(sign * controller.diagnostics['model_heading_target'], .4)
-
-  def test_c1_reversal_cannot_delay_action_c0_release(self):
-    controller = FordVirtualAngleController()
-    for i in range(200):
-      path = step(controller, i * .01, .1, circle(.12), speed=5.)
-    for i in range(200, 280):
-      path = step(controller, i * .01, .003125, circle(.12), speed=5.)
-    self.assertAlmostEqual(path.path_offset, .1)
-    self.assertAlmostEqual(path.path_angle, .1)
-    for i in range(280, 283):
-      path = step(controller, i * .01, 0., circle(-.12), speed=5.)
-    self.assertAlmostEqual(path.path_offset, 0., delta=.0051)
-    self.assertGreater(path.path_angle, .08)  # C1 is still in its own limited transition.
-
-  def test_both_commands_reverse_while_model_heading_requests_the_old_turn(self):
-    controller = FordVirtualAngleController()
-    model = circle(.04)
-    for i in range(200):
-      path = step(controller, i * .01, .01, model)
-    for i in range(200, 240):
-      path = step(controller, i * .01, -.01, model)
-    self.assertLess(path.path_offset, -.3)
-    self.assertLess(path.path_angle, -.07)
-
-  def test_invalid_or_stale_action_clears_both_requests(self):
-    for desired, overrides in ((float('nan'), {}), (float('inf'), {}), (2., {}), (.01, {'reference_time': 0.}),
-                               (.01, {'reference_time': float('nan')}), (.01, {'reference_time': 1.2})):
-      controller = FordVirtualAngleController()
-      step(controller, .99, .01, circle(.04))
-      self.assertEqual(step(controller, 1., desired, circle(.04), **overrides), FordPath())
-      self.assertIsNone(controller.reference.path)
-
-  def test_fresh_action_source_can_change_without_an_inactive_cycle(self):
-    controller = FordVirtualAngleController()
-    self.assertTrue(step(controller, 1., .01, reference_time=.99).valid)
-    # A model/maneuver source switch can select an older but still fresh action.
-    self.assertTrue(step(controller, 1.01, .01, reference_time=.98).valid)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,50 +0,0 @@
-"""Command-reference regressions, not predictions of vehicle response."""
-import unittest
-
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController
-from openpilot.selfdrive.controls.tests.test_ford_curvature_c0 import step
-from openpilot.selfdrive.controls.tests.test_ford_path_reference import circle
-
-
-class TestFordCurvatureHeading(unittest.TestCase):
-  def test_model_turn_cannot_hold_c1_after_action_releases(self):
-    controller = FordVirtualAngleController()
-    model = circle(.12)
-    for i in range(200):
-      path = step(controller, i * .01, .04, model, speed=5.)
-    self.assertAlmostEqual(path.path_angle, .28, delta=.000251)
-    for i in range(200, 270):
-      path = step(controller, i * .01, 0., model, speed=5.)
-    self.assertAlmostEqual(path.path_angle, 0., delta=.000251)
-    self.assertAlmostEqual(path.path_offset, 0., delta=.0051)
-
-  def test_full_heading_survives_flat_geometry_and_matching_actual_curvature(self):
-    for speed in (3., 8., 20.):
-      for sign in (-1, 1):
-        controller = FordVirtualAngleController()
-        for i in range(200):
-          path = step(controller, i * .01, sign * .02, circle(), speed=speed, yaw_rate=sign * .02 * speed)
-        self.assertAlmostEqual(path.path_angle, sign * .02 * max(7., speed), delta=.000251)
-        self.assertEqual((path.curvature, path.curvature_rate), (0., 0.))
-
-  def test_heading_reverses_with_action_while_model_keeps_old_turn(self):
-    controller = FordVirtualAngleController()
-    model = circle(.12)
-    for i in range(200):
-      path = step(controller, i * .01, .04, model, speed=5.)
-    for i in range(200, 320):
-      path = step(controller, i * .01, -.04, model, speed=5.)
-    self.assertAlmostEqual(path.path_angle, -.28, delta=.000251)
-    self.assertLess(path.path_offset, 0.)
-
-  def test_model_shape_does_not_change_valid_action_commands(self):
-    straight, bent = FordVirtualAngleController(), FordVirtualAngleController()
-    for i in range(300):
-      desired = .04 if i < 150 else -.04
-      left = step(straight, i * .01, desired, circle(), speed=8.)
-      right = step(bent, i * .01, desired, circle(.12), speed=8.)
-      self.assertEqual(left, right)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,61 +0,0 @@
-import hashlib
-import json
-from pathlib import Path
-from types import SimpleNamespace
-import unittest
-
-import numpy as np
-
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController
-
-
-class TestFordCurvatureHeadingRoutes(unittest.TestCase):
-  @classmethod
-  def setUpClass(cls):
-    fixture = Path(__file__).parent / 'fixtures/ford_curvature_heading_route80.npz'
-    metadata = json.loads(fixture.with_suffix('.json').read_text())
-    if hashlib.sha256(fixture.read_bytes()).hexdigest() != metadata['fixture_sha256']:
-      raise ValueError('Route80 command fixture hash mismatch')
-    cls.data = data = dict(np.load(fixture))
-    models = [SimpleNamespace(position=SimpleNamespace(x=p[0], y=p[1]), orientation=SimpleNamespace(z=p[2])) for p in data['models']]
-    previous_episode = None
-    commands, gates, statuses = [], [], []
-    for i, now in enumerate(data['t']):
-      if data['episode'][i] != previous_episode:
-        controller = FordVirtualAngleController()
-        previous_episode = data['episode'][i]
-      command = controller.update(models[data['model_index'][i]], data['desired_curvature'][i],
-                                  yaw_rate=data['yaw_rate'][i], speed=data['speed'][i], now=now,
-                                  measurement_time=data['measurement_time'][i], model_time=data['model_time'][i],
-                                  reference_time=data['reference_time'][i], active=bool(data['active'][i]),
-                                  valid=bool(data['valid'][i]), steering_pressed=bool(data['pressed'][i]))
-      commands.append((command.path_offset, command.path_angle, command.curvature, command.curvature_rate))
-      gates.append(command.valid)
-      statuses.append(controller.diagnostics['status'])
-    cls.commands = np.array(commands)
-    cls.gates = np.array(gates)
-    cls.statuses = np.array(statuses)
-
-  def test_c0_and_output_gates_match_frozen_v3(self):
-    np.testing.assert_array_equal(self.commands[:, 0], self.data['v3_replay'][:, 0])
-    np.testing.assert_array_equal(self.gates, self.data['v3_valid'])
-    np.testing.assert_array_equal(self.statuses, self.data['v3_status'])
-    np.testing.assert_array_equal(self.commands[:, 2:], 0.)
-
-  def test_recorded_turns_follow_the_common_curvature_heading(self):
-    # Expected values come from the independent shadow candidate evaluated on
-    # these frozen route inputs. This checks commands, not new vehicle motion.
-    np.testing.assert_array_equal(self.commands[:, 1], self.data['expected_common_c1'])
-    for episode, expected_heading in enumerate((.14375, .286, .1895)):
-      mask = (self.data['episode'] == episode) & self.data['evidence'] & self.data['benchmark_clean']
-      self.assertGreater(int(mask.sum()), 100)
-      self.assertAlmostEqual(float(np.median(abs(self.commands[mask, 1]))), expected_heading, delta=.001)
-    # The over-response witness previously held C1 at its bound even though the
-    # selected action requested substantially less heading over the same preview.
-    mask = (self.data['episode'] == 1) & self.data['evidence'] & self.data['benchmark_clean']
-    self.assertAlmostEqual(float(np.median(abs(self.data['recorded'][mask, 1]))), .5, delta=.0005)
-    self.assertLess(float(np.median(abs(self.commands[mask, 1]))), .30)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,278 +0,0 @@
-import hashlib
-import json
-import math
-from pathlib import Path
-from types import SimpleNamespace
-import unittest
-
-import numpy as np
-
-from opendbc.can import CANPacker, CANParser
-from opendbc.car.ford.fordcan import CanBus, create_lat_ctl2_msg
-from openpilot.cereal import custom
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController, PscmStatus
-
-
-MODEL = SimpleNamespace(position=SimpleNamespace(x=np.linspace(0., 100., 33), y=np.zeros(33)),
-                        orientation=SimpleNamespace(z=np.zeros(33)))
-AUTO_STATUS = object()
-
-
-def step(controller, now, desired=.02, yaw_rate=.08, speed=8., pscm_status=AUTO_STATUS, **overrides):
-  if pscm_status is AUTO_STATUS:
-    pscm_status = PscmStatus(timestamp=now, lateral_state=2, limit=0, capability=2, denied=False)
-  inputs = {'yaw_rate': yaw_rate, 'speed': speed, 'now': now, 'measurement_time': now,
-            'model_time': math.floor((now + 1e-6) / .05) * .05, 'reference_time': now,
-            'active': True, 'pscm_status': pscm_status, 'steering_torque': 0.}
-  inputs.update(overrides)
-  return controller.update(MODEL, desired, **inputs)
-
-
-def warm(controller, desired=.02, yaw_rate=.08, speed=8., count=200):
-  command = None
-  for i in range(count):
-    command = step(controller, i * .01, desired, yaw_rate, speed)
-  return command
-
-
-class TestFordHeadingFeedback(unittest.TestCase):
-  def test_under_and_over_response_change_only_heading(self):
-    for sign in (-1, 1):
-      deficient = FordVirtualAngleController()
-      excessive = FordVirtualAngleController()
-      matched = FordVirtualAngleController()
-      low = warm(deficient, sign * .02, sign * .08)
-      high = warm(excessive, sign * .02, sign * .24)
-      steady = warm(matched, sign * .02, sign * .16)
-      self.assertGreater(sign * low.path_angle, .20)
-      self.assertLess(sign * high.path_angle, .12)
-      self.assertAlmostEqual(sign * steady.path_angle, .16, delta=.0005)
-      self.assertEqual(low.path_offset, high.path_offset)
-      self.assertEqual(low.path_offset, steady.path_offset)
-      self.assertEqual((low.curvature, low.curvature_rate), (0., 0.))
-
-  def test_missing_pscm_status_keeps_the_existing_base(self):
-    controller = FordVirtualAngleController()
-    for i in range(300):
-      command = step(controller, i * .01, pscm_status=None)
-    self.assertAlmostEqual(command.path_angle, .16, delta=.0005)
-    self.assertAlmostEqual(command.path_offset, .64, delta=.01)
-
-  def test_generic_eps_limit_freezes_both_error_directions(self):
-    for yaw_rate in (0., .4):
-      controller = FordVirtualAngleController()
-      before = warm(controller)
-      self.assertGreater(before.path_angle, .20)
-      for i in range(200, 260):
-        now = i * .01
-        command = step(controller, now, yaw_rate=yaw_rate,
-                       pscm_status=PscmStatus(now, 2, 2, 2, False))
-        self.assertAlmostEqual(command.path_angle, before.path_angle, delta=.0005)
-
-  def test_ineligible_feedback_clears_bias_and_requires_fresh_history(self):
-    # These guards affect feedback eligibility, while the existing base path
-    # remains available. Limit 3 reports driver activity and clears, not freezes.
-    cases = [
-      {'pscm_status': None},
-      {'pscm_status': PscmStatus(1., 2, 0, 2, False)},
-      {'pscm_status': PscmStatus(2.01, 2, 0, 2, False)},
-      {'pscm_status': PscmStatus(2., 2, 0, 2, False, False)},
-      {'pscm_status': PscmStatus(2., 1, 0, 2, False)},
-      {'pscm_status': PscmStatus(2., 2, 0, 0, False)},
-      {'pscm_status': PscmStatus(2., 2, 0, 3, False)},
-      {'pscm_status': PscmStatus(2., 2, 0, 2, True)},
-      {'pscm_status': PscmStatus(2., 2, 3, 2, False)},
-      {'pscm_status': PscmStatus(float('nan'), 2, 0, 2, False)},
-      {'pscm_status': PscmStatus(2., 2, 4, 2, False)},
-      {'pscm_status': PscmStatus(1.98, 2, 0, 2, False)},  # Fresh but moves backward.
-      {'steering_pressed': True},
-      {'steering_torque': 1.01},
-      {'steering_torque': -1.01},
-      {'steering_torque': float('nan')},
-      {'speed': 1.9},
-    ]
-    for overrides in cases:
-      with self.subTest(overrides=overrides):
-        controller = FordVirtualAngleController()
-        warm(controller)
-        self.assertGreater(controller.diagnostics['heading_bias'], .04)
-        command = step(controller, 2., **overrides)
-        self.assertTrue(command.valid)
-        self.assertEqual(controller.diagnostics['heading_bias'], 0.)
-        for i in range(201, 220):
-          step(controller, i * .01)
-          self.assertEqual(controller.diagnostics['heading_bias'], 0.)
-        for i in range(220, 232):
-          step(controller, i * .01)
-        self.assertGreater(controller.diagnostics['heading_bias'], 0.)
-
-  def test_repeated_measurement_cannot_be_integrated_again(self):
-    controller = FordVirtualAngleController()
-    before = warm(controller)
-    bias = controller.diagnostics['heading_bias']
-    self.assertGreater(bias, .04)
-    for i in range(200, 213):
-      command = step(controller, i * .01, measurement_time=1.99)
-      self.assertEqual(controller.diagnostics['heading_bias'], bias)
-      self.assertAlmostEqual(command.path_angle, before.path_angle, delta=.0005)
-
-  def test_delayed_reference_is_held_without_future_interpolation(self):
-    controller = FordVirtualAngleController()
-    for i in range(41):
-      step(controller, i * .01, yaw_rate=.16)
-    # No control request existed at .405: historical values straddle that time
-    # at .400 and .415. The future .415 request must not enter the comparison.
-    step(controller, .415, desired=.021, yaw_rate=.16)
-    for now in np.arange(.425, .596, .01):
-      step(controller, float(now), desired=.021, yaw_rate=.16)
-    step(controller, .605, desired=.021, yaw_rate=.16)
-    self.assertAlmostEqual(controller.diagnostics['feedback_reference_time'], .4, places=9)
-    self.assertAlmostEqual(controller.diagnostics['heading_bias'], 0., places=10)
-    step(controller, .625, desired=.021, yaw_rate=.16)
-    self.assertGreater(controller.diagnostics['heading_bias'], 0.)
-
-  def test_zero_and_reversal_cannot_rebuild_previous_turn_bias(self):
-    for next_desired in (0., -.02):
-      controller = FordVirtualAngleController()
-      before = warm(controller)
-      self.assertGreater(controller.diagnostics['heading_bias'], .04)
-      previous = before.path_angle
-      for i in range(200, 220):
-        command = step(controller, i * .01, desired=next_desired)
-        self.assertEqual(controller.diagnostics['heading_bias'], 0.)
-        self.assertLessEqual(command.path_angle, previous + .0005)
-        self.assertLessEqual(abs(command.path_angle - previous), .005501)
-        previous = command.path_angle
-      if next_desired == 0.:
-        for i in range(220, 320):
-          command = step(controller, i * .01, desired=0.)
-        self.assertEqual(controller.diagnostics['heading_bias'], 0.)
-        self.assertAlmostEqual(command.path_angle, 0., delta=.0005)
-
-  def test_eps_limit_still_allows_base_relative_release(self):
-    controller = FordVirtualAngleController()
-    warm(controller)
-    before_bias = controller.diagnostics['heading_bias']
-    self.assertGreater(before_bias, .04)
-    for i in range(200, 280):
-      now = i * .01
-      command = step(controller, now, desired=.01, pscm_status=PscmStatus(now, 2, 2, 2, False))
-      self.assertAlmostEqual(controller.diagnostics['heading_bias'], before_bias * .5, places=10)
-    self.assertAlmostEqual(command.path_angle, .08 + before_bias * .5, delta=.0005)
-
-  def test_release_uses_clipped_base_not_raw_curvature(self):
-    controller = FordVirtualAngleController()
-    before = warm(controller, desired=.1, yaw_rate=1.)
-    before_bias = controller.diagnostics['heading_bias']
-    self.assertLess(before_bias, -.04)
-    # Both requests give clipped base C1=.5. Scaling a negative bias by the raw
-    # curvature reduction would increase total C1 during a release.
-    after = step(controller, 2., desired=.09, yaw_rate=1., pscm_status=PscmStatus(2., 2, 2, 2, False))
-    self.assertAlmostEqual(controller.diagnostics['heading_bias'], before_bias, places=10)
-    self.assertAlmostEqual(after.path_angle, before.path_angle, delta=.0005)
-
-  def test_host_field_limit_prevents_hidden_integral_growth(self):
-    controller = FordVirtualAngleController()
-    for i in range(500):
-      command = step(controller, i * .01, desired=.1, yaw_rate=0.)
-      self.assertAlmostEqual(controller.diagnostics['heading_bias'], 0., places=10)
-      self.assertLessEqual(abs(command.path_angle), .5)
-    self.assertAlmostEqual(command.path_angle, .5, delta=.0005)
-
-  def test_host_slew_limit_does_not_store_undelivered_positive_bias(self):
-    controller = FordVirtualAngleController()
-    for i in range(30):
-      command = step(controller, i * .01, desired=.02, yaw_rate=0.)
-      self.assertAlmostEqual(controller.diagnostics['heading_bias'], 0., places=10)
-      self.assertLessEqual(command.path_angle, (i + 1) * .005 + .0005)
-    for i in range(30, 70):
-      step(controller, i * .01, desired=.02, yaw_rate=0.)
-    self.assertGreater(controller.diagnostics['heading_bias'], 0.)
-
-  def test_large_or_batched_error_uses_available_host_slew(self):
-    for measurement_period, yaw_rate in ((.01, -.4), (.02, -.1)):
-      with self.subTest(measurement_period=measurement_period, yaw_rate=yaw_rate):
-        controller = FordVirtualAngleController()
-        previous = 0.
-        for i in range(600):
-          now = i * .01
-          measurement_time = math.floor((now + 1e-6) / measurement_period) * measurement_period
-          command = step(controller, now, desired=.04, speed=5., yaw_rate=yaw_rate, measurement_time=measurement_time)
-          self.assertLessEqual(abs(command.path_angle - previous), .005501)
-          self.assertLessEqual(abs(command.path_angle), .5)
-          previous = command.path_angle
-        # An increment larger than a control tick's available slew must admit
-        # its deliverable portion, rather than permanently disabling feedback.
-        self.assertGreater(controller.diagnostics['heading_bias'], .05)
-        self.assertGreater(command.path_angle, .40)
-
-  def test_can_packing_preserves_the_combined_feedback_command(self):
-    controller = FordVirtualAngleController()
-    base = FordVirtualAngleController()
-    packer = CANPacker('ford_lincoln_base_pt')
-    parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], 0)
-    bus = CanBus(fingerprint={0: {}})
-    bias_seen = False
-    for i in range(600):
-      sign = 1 if i < 300 else -1
-      command = step(controller, i * .01, desired=sign * .02, yaw_rate=sign * .08)
-      base_command = step(base, i * .01, desired=sign * .02, yaw_rate=sign * .08, pscm_status=None)
-      self.assertEqual(command.path_offset, base_command.path_offset)
-      bias_seen |= abs(controller.diagnostics['heading_bias']) > .04
-      msg = custom.CarControlSP.new_message()
-      msg.fordLateralPath.pathOffset = command.path_offset
-      msg.fordLateralPath.pathAngle = command.path_angle
-      packet = create_lat_ctl2_msg(packer, bus, 2, -msg.fordLateralPath.pathOffset, -msg.fordLateralPath.pathAngle, 0., 0., i % 16)
-      parser.update([i * 10_000_000, [packet]])
-      decoded = parser.vl['LateralMotionControl2']
-      self.assertAlmostEqual(decoded['LatCtlPathOffst_L_Actl'], -command.path_offset)
-      self.assertAlmostEqual(decoded['LatCtlPath_An_Actl'], -command.path_angle)
-      self.assertEqual(decoded['LatCtlCurv_No_Actl'], 0.)
-      self.assertEqual(decoded['LatCtlCrv_NoRate2_Actl'], 0.)
-    self.assertTrue(bias_seen)
-
-  def test_recorded_requests_use_pscm_guards_without_changing_c0(self):
-    directory = Path(__file__).parent / 'fixtures'
-    status_fixture = directory / 'ford_heading_feedback_route80_status.npz'
-    metadata = json.loads(status_fixture.with_suffix('.json').read_text())
-    base_fixture = directory / metadata['base_fixture']
-    self.assertEqual(hashlib.sha256(status_fixture.read_bytes()).hexdigest(), metadata['fixture_sha256'])
-    self.assertEqual(hashlib.sha256(base_fixture.read_bytes()).hexdigest(), metadata['base_fixture_sha256'])
-    data, eps = dict(np.load(base_fixture)), dict(np.load(status_fixture))
-    np.testing.assert_array_equal(data['t'], eps['t'])
-    models = [SimpleNamespace(position=SimpleNamespace(x=p[0], y=p[1]), orientation=SimpleNamespace(z=p[2])) for p in data['models']]
-    previous_episode = None
-    commands, biases, gates = [], [], []
-    limit_freezes = 0
-    for i, now in enumerate(data['t']):
-      if data['episode'][i] != previous_episode:
-        controller = FordVirtualAngleController()
-        previous_episode = data['episode'][i]
-      pscm = PscmStatus(float(eps['pscm_timestamp'][i]), int(eps['lateral_state'][i]), int(eps['limit'][i]),
-                        int(eps['capability'][i]), bool(eps['denied'][i]), bool(eps['valid'][i]))
-      command = controller.update(models[data['model_index'][i]], data['desired_curvature'][i],
-                                  yaw_rate=data['yaw_rate'][i], speed=data['speed'][i], now=now,
-                                  measurement_time=data['measurement_time'][i], model_time=data['model_time'][i],
-                                  reference_time=data['reference_time'][i], active=bool(data['active'][i]), valid=bool(data['valid'][i]),
-                                  steering_pressed=bool(data['pressed'][i]), steering_torque=float(eps['steering_torque'][i]), pscm_status=pscm)
-      commands.append((command.path_offset, command.path_angle, command.curvature, command.curvature_rate))
-      gates.append(command.valid)
-      biases.append(controller.diagnostics['heading_bias'])
-      if pscm.limit == 2:
-        self.assertNotEqual(controller.diagnostics['feedback_status'], 'integrating')
-      limit_freezes += controller.diagnostics['feedback_status'] == 'pscm_limit'
-    commands, biases = np.array(commands), np.array(biases)
-    np.testing.assert_array_equal(commands[:, 0], data['v3_replay'][:, 0])
-    np.testing.assert_array_equal(gates, data['v3_valid'])
-    np.testing.assert_array_equal(commands[:, 2:], 0.)
-    self.assertGreater(limit_freezes, 0)
-    for episode in (0, 2):
-      mask = (data['episode'] == episode) & data['evidence'] & data['benchmark_clean']
-      # Recorded motion is frozen: this establishes correction direction only,
-      # not that a new vehicle drive will close the observed tracking deficit.
-      self.assertGreater(float(np.max(biases[mask])), .001)
-      self.assertGreater(float(np.max(commands[mask, 1] - data['expected_common_c1'][mask])), .005)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,422 +0,0 @@
-import math
-from types import SimpleNamespace
-
-import numpy as np
-
-from openpilot.cereal import custom
-from openpilot.selfdrive.car.helpers import convert_carControlSP
-from openpilot.selfdrive.controls.lib.ford_path import (DBC_ANGLE, DBC_CURVATURE, DBC_OFFSET, FordPath, FordPathController,
-                                                        FordPscmObserver, FordPscmObserverPathController, FordPscmState,
-                                                        _bounded_feedback, _encode_path, _model_path, _predicted_pose,
-                                                        _pscm_contributions, _relative_pose)
-
-
-def _path(curvature: float, speed: float = 8.0):
-  t = np.linspace(0.0, 3.0, 61)
-  distance = speed * t
-  heading = curvature * distance
-  x = np.zeros_like(distance)
-  y = np.zeros_like(distance)
-  for i in range(1, len(distance)):
-    ds = distance[i] - distance[i - 1]
-    average_heading = 0.5 * (heading[i] + heading[i - 1])
-    x[i] = x[i - 1] + ds * math.cos(average_heading)
-    y[i] = y[i - 1] + ds * math.sin(average_heading)
-  return SimpleNamespace(
-    position=SimpleNamespace(t=t.tolist(), x=x.tolist(), y=y.tolist()),
-    orientation=SimpleNamespace(z=heading.tolist()),
-  )
-
-
-def _changing_path(start_curvature: float, end_curvature: float, speed: float = 8.0):
-  t = np.linspace(0.0, 3.0, 61)
-  distance = speed * t
-  curvature = np.interp(distance, [distance[0], min(distance[-1], 7.0)], [start_curvature, end_curvature])
-  heading = np.zeros_like(distance)
-  x = np.zeros_like(distance)
-  y = np.zeros_like(distance)
-  for i in range(1, len(distance)):
-    ds = distance[i] - distance[i - 1]
-    heading[i] = heading[i - 1] + 0.5 * (curvature[i] + curvature[i - 1]) * ds
-    average_heading = 0.5 * (heading[i] + heading[i - 1])
-    x[i] = x[i - 1] + ds * math.cos(average_heading)
-    y[i] = y[i - 1] + ds * math.sin(average_heading)
-  return SimpleNamespace(
-    position=SimpleNamespace(t=t.tolist(), x=x.tolist(), y=y.tolist()),
-    orientation=SimpleNamespace(z=heading.tolist()),
-  )
-
-
-def _command(model, desired_curvature: float, *, current_curvature: float = 0.0, v_ego: float = 8.0):
-  return FordPathController(dt=1.0).update(model, desired_curvature, current_curvature=current_curvature, v_ego=v_ego)
-
-
-def _equivalent_curvature(command) -> float:
-  return 2.0 * command.path_offset / 7.0 ** 2 + 2.0 * command.path_angle / 7.0 + command.curvature
-
-
-def test_gentle_path_uses_only_c2():
-  command = _command(_path(0.004, speed=20.0), 0.004, current_curvature=0.004, v_ego=20.0)
-  assert command.valid
-  assert command.path_offset == 0.0
-  assert command.path_angle == 0.0
-  assert np.isclose(command.curvature, 0.004, atol=1e-6)
-  assert command.curvature_rate == 0.0
-
-
-def test_gentle_path_uses_only_c2_when_model_and_action_disagree():
-  command = _command(_path(0.005), 0.002, current_curvature=0.005)
-  assert command.path_offset == 0.0
-  assert command.path_angle == 0.0
-  assert np.isclose(command.curvature, 0.002, atol=1e-6)
-
-
-def test_spatially_growing_path_adds_fast_pose_before_action_becomes_large():
-  controller = FordPathController(dt=1.0)
-  command = controller.update(_changing_path(0.0, 0.04), 0.012, current_curvature=0.0, v_ego=8.0)
-  assert command.path_offset > 0.0
-  assert command.path_angle > 0.0
-  assert command.curvature < 0.012
-  assert command.curvature_rate == 0.0
-
-
-def test_growing_model_pose_adds_authority_but_c3_is_never_transmitted():
-  constant = _command(_path(0.012), 0.012)
-  growing = _command(_changing_path(0.0, 0.04), 0.012)
-  assert _equivalent_curvature(growing) > _equivalent_curvature(constant)
-  assert constant.curvature_rate == 0.0
-  assert growing.curvature_rate == 0.0
-
-
-def test_local_tracking_error_corrects_without_replacing_forward_pose():
-  model = _changing_path(0.0, 0.04)
-  local_curvature = 0.5 * 0.04 * 2.0 / 7.0
-  aligned = _command(model, 0.012, current_curvature=local_curvature)
-  under = _command(model, 0.012, current_curvature=0.0)
-  assert aligned.path_offset > 0.0
-  assert aligned.path_angle > 0.0
-  assert under.path_offset > aligned.path_offset
-  assert under.path_angle > aligned.path_angle
-
-
-def test_large_maneuver_uses_fast_pose_and_zeros_c2():
-  command = _command(_path(0.04), 0.04)
-  assert command.path_offset > 0.5
-  assert command.path_angle > 0.2
-  assert command.curvature == 0.0
-  assert command.curvature_rate == 0.0
-
-
-def test_model_pose_can_trigger_maneuver_when_action_is_late():
-  command = _command(_path(0.04), 0.002)
-  assert command.path_offset > 0.5
-  assert command.path_angle > 0.2
-  assert command.curvature == 0.0
-
-
-def test_gentle_model_pose_does_not_replace_a_collapsed_action():
-  command = _command(_path(0.005), 0.0, current_curvature=0.005)
-  assert command.path_offset == 0.0
-  assert command.path_angle == 0.0
-  assert command.curvature == 0.0
-
-
-def test_changing_gentle_curve_keeps_upstream_strength_c2():
-  command = _command(_changing_path(0.0, 0.008), 0.004, current_curvature=0.0)
-  assert np.isclose(command.curvature, 0.004)
-  assert command.path_offset == 0.0
-  assert command.path_angle == 0.0
-
-
-def test_action_only_maneuver_cannot_invent_large_model_pose():
-  command = _command(_path(0.002), 0.04)
-  assert 0.0 < command.path_offset < 0.1
-  assert 0.0 < command.path_angle < 0.03
-  assert command.curvature == 0.0
-
-
-def test_nearby_demands_blend_continuously_without_a_mode_threshold():
-  low = _command(_path(0.0119), 0.0119)
-  high = _command(_path(0.0121), 0.0121)
-  assert abs(high.path_offset - low.path_offset) < 0.05
-  assert abs(high.path_angle - low.path_angle) < 0.03
-  assert abs(high.curvature - low.curvature) < 0.001
-
-
-def test_leaving_c2_normal_band_does_not_drop_total_authority():
-  normal = _command(_path(0.006), 0.006)
-  transition = _command(_path(0.0061), 0.0061)
-  assert transition.curvature <= normal.curvature
-  assert _equivalent_curvature(transition) >= _equivalent_curvature(normal)
-
-
-def test_low_speed_still_uses_available_model_pose():
-  command = _command(_path(0.04, speed=2.0), 0.04, v_ego=2.0)
-  assert command.path_offset > 0.0
-  assert command.path_angle > 0.0
-
-
-def test_higher_speed_advances_predicted_pose_and_extends_heading_horizon():
-  model = _changing_path(0.0, 0.015, speed=20.0)
-  slow = _command(model, 0.012, v_ego=7.0)
-  fast = _command(model, 0.012, v_ego=20.0)
-  assert fast.path_offset > slow.path_offset
-  assert fast.path_angle > slow.path_angle
-
-
-def test_short_model_uses_available_endpoint():
-  model = _path(0.04, speed=1.0)
-  command = _command(model, 0.04, v_ego=1.0)
-  assert command.valid
-  assert command.path_offset > 0.0
-  assert command.path_angle > 0.0
-
-
-def test_turn_entry_coordinates_c2_release_with_fast_pose_attack():
-  controller = FordPathController(dt=0.01)
-  for _ in range(20):
-    assert controller.update(_path(0.004), 0.004, v_ego=8.0).curvature > 0.0
-  outputs = [controller.update(_path(0.04), 0.04, current_curvature=0.01, v_ego=8.0) for _ in range(100)]
-  assert 0.0 < outputs[0].curvature < 0.004
-  assert outputs[0].path_offset > 0.0
-  assert outputs[0].path_angle > 0.0
-  assert outputs[-1].curvature == 0.0
-
-
-def test_turn_exit_allows_c2_to_take_over_while_fast_pose_drains():
-  controller = FordPathController(dt=0.01)
-  for _ in range(20):
-    controller.update(_path(0.04), 0.04, current_curvature=0.02, v_ego=8.0)
-  outputs = [controller.update(_path(0.004), 0.004, current_curvature=0.004, v_ego=8.0) for _ in range(100)]
-  assert 0.0 < outputs[0].curvature < 0.004
-  assert outputs[0].path_offset != 0.0 or outputs[0].path_angle != 0.0
-  assert outputs[-1].path_offset == 0.0
-  assert outputs[-1].path_angle == 0.0
-
-
-def test_100hz_handoff_preserves_total_authority_without_entry_drop_or_exit_overshoot():
-  controller = FordPathController(dt=0.01)
-  normal = controller.update(_path(0.006), 0.006, current_curvature=0.006, v_ego=8.0)
-  entries = [controller.update(_path(0.04), 0.04, current_curvature=0.01, v_ego=8.0) for _ in range(100)]
-  entry_authority = np.asarray([_equivalent_curvature(command) for command in entries])
-  assert np.all(np.diff(entry_authority) >= -1e-9)
-  assert entry_authority[0] >= _equivalent_curvature(normal)
-
-  exits = [controller.update(_path(0.004), 0.004, current_curvature=0.004, v_ego=8.0) for _ in range(100)]
-  exit_authority = np.asarray([_equivalent_curvature(command) for command in exits])
-  assert np.all(np.diff(exit_authority) <= 1e-9)
-  assert np.all(exit_authority >= 0.004 - 1e-9)
-
-
-def test_measured_tracking_error_closes_bidirectionally_without_abandoning_the_turn():
-  model = _path(0.04)
-  under = _command(model, 0.04, current_curvature=0.005)
-  on_target = _command(model, 0.04, current_curvature=0.04)
-  over = _command(model, 0.04, current_curvature=0.05)
-  assert under.path_offset > on_target.path_offset
-  assert under.path_angle > on_target.path_angle
-  assert 0.0 < over.path_offset < on_target.path_offset
-  assert 0.0 < over.path_angle < on_target.path_angle
-
-
-def test_gentle_curve_does_not_add_fast_tracking_trim():
-  model = _path(0.004)
-  under = _command(model, 0.004, current_curvature=0.002)
-  on_target = _command(model, 0.004, current_curvature=0.004)
-  over = _command(model, 0.004, current_curvature=0.006)
-  assert under.path_offset == on_target.path_offset == over.path_offset == 0.0
-  assert under.path_angle == on_target.path_angle == over.path_angle == 0.0
-  assert np.allclose([under.curvature, on_target.curvature, over.curvature], 0.004, atol=2e-6)
-
-
-def test_overshoot_trim_cannot_erase_a_modeled_turn():
-  model = _path(0.04)
-  on_target = _command(model, 0.04, current_curvature=0.04)
-  over = _command(model, 0.04, current_curvature=0.06)
-  assert over.path_offset > 0.95 * on_target.path_offset
-  assert over.path_angle > 0.9 * on_target.path_angle
-
-
-def test_corrupt_measured_curvature_cannot_reverse_a_modeled_turn():
-  command = _command(_path(0.04), 0.04, current_curvature=0.5)
-  assert command.path_offset > 0.0
-  assert command.path_angle > 0.0
-  assert command.curvature == 0.0
-
-
-def test_feedback_preserves_half_lsb_feedforward_direction():
-  for feedforward, resolution in ((0.006, 0.01), (0.0004, 0.0005)):
-    result = feedforward + _bounded_feedback(feedforward, -1.0, resolution, 1.0)
-    assert result >= 0.5 * resolution
-
-
-def test_recent_curvature_trend_advances_vehicle_pose_without_a_response_gain():
-  model = _model_path(_path(0.04))
-  assert model is not None
-  constant = _encode_path(model, 0.04, current_curvature=0.02, curvature_delta=0.0, v_ego=8.0)
-  rising = _encode_path(model, 0.04, current_curvature=0.02, curvature_delta=0.01, v_ego=8.0)
-  assert 0.0 < rising.path_offset < constant.path_offset
-  assert 0.0 < rising.path_angle < constant.path_angle
-
-
-def test_model_path_exit_zeros_lingering_c2_and_countersteers():
-  command = _command(_path(0.0), 0.004, current_curvature=0.006)
-  assert command.path_offset <= 0.0
-  assert command.path_angle < 0.0
-  assert command.curvature == 0.0
-
-
-def test_model_path_reversal_zeros_opposing_lingering_c2():
-  command = _command(_path(-0.004), 0.004, current_curvature=0.002)
-  assert command.path_offset < 0.0
-  assert command.path_angle < 0.0
-  assert command.curvature == 0.0
-
-
-def test_s_turn_reverses_model_pose_without_slow_c2():
-  controller = FordPathController(dt=0.05)
-  for _ in range(10):
-    controller.update(_path(0.04), 0.04, v_ego=8.0)
-  outputs = [controller.update(_path(-0.04), -0.04, v_ego=8.0) for _ in range(10)]
-  assert all(command.curvature == 0.0 for command in outputs)
-  assert np.all(np.diff([command.path_offset for command in outputs]) < 0.0)
-  assert np.all(np.diff([command.path_angle for command in outputs]) < 0.0)
-  assert outputs[-1].path_offset < 0.0
-  assert outputs[-1].path_angle < 0.0
-
-
-def test_output_limits_and_rates_are_bounded():
-  controller = FordPathController()
-  outputs = [controller.update(_path(0.2), 0.2, v_ego=8.0) for _ in range(100)]
-  assert all(DBC_OFFSET[0] <= command.path_offset <= DBC_OFFSET[1] for command in outputs)
-  assert all(DBC_ANGLE[0] <= command.path_angle <= DBC_ANGLE[1] for command in outputs)
-  assert all(DBC_CURVATURE[0] <= command.curvature <= DBC_CURVATURE[1] for command in outputs)
-  assert np.max(np.abs(np.diff([command.path_offset for command in outputs]))) <= 0.04 + 1e-9
-  assert np.max(np.abs(np.diff([command.path_angle for command in outputs]))) <= 0.01 + 1e-9
-
-
-def test_clipped_path_angle_uses_available_offset_to_preserve_endpoint():
-  horizon = 7.0
-  for curvature, angle_limit in ((-0.1, DBC_ANGLE[0]), (0.1, DBC_ANGLE[1])):
-    model = _path(curvature)
-    command = _command(model, curvature, current_curvature=curvature, v_ego=horizon)
-    path = _model_path(model)
-    assert path is not None
-    advance = 0.1 * horizon
-    model_offset, model_angle = _relative_pose(advance + horizon, path,
-                                                _predicted_pose(advance, curvature, 0.0))
-
-    assert command.path_angle == angle_limit
-    assert np.isclose(command.path_offset + horizon * command.path_angle,
-                      model_offset + horizon * model_angle)
-
-
-def test_invalid_model_ramps_pose_to_zero_and_inactive_resets():
-  controller = FordPathController(dt=0.01)
-  for _ in range(20):
-    active = controller.update(_path(0.04), 0.04, v_ego=8.0)
-  invalid = controller.update(None, 0.0, v_ego=8.0)
-  assert invalid.valid
-  assert abs(invalid.path_offset) < abs(active.path_offset)
-  assert abs(invalid.path_angle) < abs(active.path_angle)
-  assert not controller.update(_path(0.0), 0.0, v_ego=8.0, active=False).valid
-
-
-def test_sunnypilot_path_message_round_trip():
-  message = custom.CarControlSP.new_message()
-  message.fordLateralPath.pathOffset = 0.3
-  message.fordLateralPath.pathAngle = -0.2
-  message.fordLateralPath.curvature = 0.008
-  message.fordLateralPath.curvatureRate = -0.0004
-  message.fordLateralPath.valid = True
-  path = convert_carControlSP(message.as_reader()).fordLateralPath
-  assert np.isclose(path.pathOffset, 0.3)
-  assert np.isclose(path.pathAngle, -0.2)
-  assert np.isclose(path.curvature, 0.008)
-  assert np.isclose(path.curvatureRate, -0.0004)
-  assert path.valid
-
-
-def test_pscm_observer_mirrors_exact_250hz_slew_and_c3_target():
-  observer = FordPscmObserver()
-  observer.set_command(FordPath(True, 1.0, 0.5, 0.0, 0.001))
-  observer.advance(1.0)
-  assert np.isclose(observer.state.path_offset, 1.0)
-  assert np.isclose(observer.state.path_angle, 0.100006103515625)
-  assert np.isclose(observer.state.curvature, 0.0030059814453125)
-
-
-def test_pscm_observer_tracks_wire_quantized_commands():
-  observer = FordPscmObserver()
-  observer.set_command(FordPath(True, 0.006, 0.0004, 0.000011, 0.0))
-  assert observer.command.path_offset == 0.01
-  assert observer.command.path_angle == 0.0005
-  assert observer.command.curvature == 0.00002
-
-
-def test_pscm_c2_contribution_is_speed_scheduled():
-  state = FordPscmObserver().state
-  state = type(state)(curvature=0.004)
-  low = _pscm_contributions(state, 5.0)[2]
-  high = _pscm_contributions(state, 20.0)[2]
-  assert high > low * 10.0
-
-
-def test_pscm_observer_fills_missing_gentle_c2_with_fast_fields():
-  controller = FordPscmObserverPathController(dt=0.01)
-  command = controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
-                              v_ego=20.0, v_ego_raw=20.0)
-  assert command.path_offset > 0.0
-  assert command.path_angle > 0.0
-  assert command.curvature > 0.0
-
-
-def test_pscm_observer_uses_c0_only_after_c1_reaches_its_effective_limit():
-  controller = FordPscmObserverPathController(dt=0.01)
-  small = controller._command_for_state(FordPath(True, 0.2, 0.0, 0.0, 0.0), 8.0)
-  large = controller._command_for_state(FordPath(True, 1.0, 0.5, 0.0, 0.0), 8.0)
-  assert small.path_offset == 0.0
-  assert small.path_angle > 0.0
-  assert large.path_offset > 0.0
-  assert large.path_angle == 0.349609375 / 10.0
-
-
-def test_pscm_observer_preserves_c2_residual_across_c0_c1_headroom():
-  controller = FordPscmObserverPathController(dt=0.01)
-  target = FordPath(True, 0.0, 0.0, 0.004, 0.0)
-  command = controller._command_for_state(target, 20.0)
-  target_contribution = sum(_pscm_contributions(FordPscmState(curvature=target.curvature), 20.0))
-  command_contributions = _pscm_contributions(FordPscmState(command.path_offset, command.path_angle), 20.0)
-  assert np.isclose(sum(command_contributions), target_contribution)
-
-  controller.observer.state = FordPscmState(curvature=0.004)
-  unwind = controller._command_for_state(FordPath(valid=True), 20.0)
-  unwind_contributions = _pscm_contributions(FordPscmState(unwind.path_offset, unwind.path_angle), 20.0)
-  lingering_c2 = _pscm_contributions(controller.observer.state, 20.0)[2]
-  assert np.isclose(sum(unwind_contributions) + lingering_c2, 0.0)
-
-
-def test_pscm_observer_unloads_fast_residual_as_c2_loads():
-  controller = FordPscmObserverPathController(dt=0.01)
-  outputs = [controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
-                               v_ego=20.0, v_ego_raw=20.0) for _ in range(200)]
-  assert outputs[0].path_angle > outputs[-1].path_angle >= 0.0
-  assert controller.observer.state.curvature > 0.003
-
-
-def test_pscm_observer_counters_lingering_c2_during_model_exit():
-  controller = FordPscmObserverPathController(dt=0.01)
-  for _ in range(200):
-    controller.update(_path(0.004, speed=20.0), 0.004, current_curvature=0.004,
-                      v_ego=20.0, v_ego_raw=20.0)
-  command = controller.update(_path(0.0, speed=20.0), 0.0, current_curvature=0.004,
-                              v_ego=20.0, v_ego_raw=20.0)
-  assert command.path_angle < 0.0
-  assert command.curvature < controller.observer.state.curvature
-
-
-def test_pscm_observer_avoids_ineffective_c0_c1_windup():
-  controller = FordPscmObserverPathController(dt=1.0)
-  command = controller.update(_path(0.2), 0.2, v_ego=8.0, v_ego_raw=8.0)
-  assert abs(command.path_offset) <= 1.0
-  assert abs(command.path_angle) <= 0.349609375 / 10.0
@@ -1,195 +0,0 @@
-import math
-import hashlib
-import json
-from pathlib import Path
-from types import SimpleNamespace
-import unittest
-
-import numpy as np
-
-from opendbc.can import CANPacker, CANParser
-from opendbc.car.ford.fordcan import CanBus, create_lat_ctl2_msg
-from openpilot.cereal import custom
-
-from openpilot.selfdrive.controls.lib.ford_path import FordPath
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController
-
-
-def circle(curvature=0.0, offset=0.0):
-  arc = np.linspace(0, 60, 241)
-  heading = curvature * arc
-  x = np.sin(heading) / curvature if curvature else arc
-  y = (1 - np.cos(heading)) / curvature if curvature else np.zeros(len(arc))
-  return SimpleNamespace(position=SimpleNamespace(x=x, y=y + offset), orientation=SimpleNamespace(z=heading))
-
-
-def run_step(controller, model, t, curvature=0.0, speed=8.0, desired_curvature=0.0, **kwargs):
-  inputs = {'yaw_rate': curvature * speed, 'speed': speed, 'now': t, 'measurement_time': t,
-            'model_time': math.floor((t + 1e-6) / .05) * .05, 'reference_time': t, 'active': True}
-  inputs.update(kwargs)
-  return controller.update(model, desired_curvature, **inputs)
-
-
-class TestFordPathReference(unittest.TestCase):
-  def test_model_translation_cannot_add_c0_when_action_is_zero(self):
-    for offset in (-.8, .8):
-      controller = FordVirtualAngleController()
-      model = circle(offset=offset)
-      for i in range(500):
-        path = run_step(controller, model, i * .01)
-      self.assertAlmostEqual(path.path_offset, 0., delta=.01)
-      self.assertAlmostEqual(path.path_angle, 0., delta=.0005)
-      self.assertEqual((path.curvature, path.curvature_rate), (0, 0))
-
-  def test_large_path_demands_survive_even_when_measured_curvature_matches(self):
-    for sign in (-1, 1):
-      for curvature, speed, min_offset, min_heading in ((.02, 8., .4, .14), (.08, 4., 1.8, .45)):
-        controller = FordVirtualAngleController()
-        model = circle(sign * curvature)
-        for i in range(600):
-          path = run_step(controller, model, i * .01, curvature=sign * curvature, speed=speed, desired_curvature=sign * curvature)
-        self.assertGreater(sign * path.path_offset, min_offset)
-        self.assertGreater(sign * path.path_angle, min_heading)
-        self.assertEqual((path.curvature, path.curvature_rate), (0, 0))
-
-  def test_ego_motion_is_not_delayed_by_the_model_filter(self):
-    controller = FordVirtualAngleController()
-    model = circle(offset=.5)
-    run_step(controller, model, 0., curvature=.02, speed=10.)
-    initial = tuple(a.copy() for a in controller.reference.path)
-    for i in range(1, 11):
-      run_step(controller, model, i * .01, curvature=.02, speed=10., model_time=0.)
-    _, x, y, heading = controller.reference.path
-    yaw = .02  # 1 m traveled on 0.02/m curvature
-    dx, dy = math.sin(yaw) / .02, (1 - math.cos(yaw)) / .02
-    expected_x = math.cos(yaw) * (initial[1] - dx) + math.sin(yaw) * (initial[2] - dy)
-    expected_y = -math.sin(yaw) * (initial[1] - dx) + math.cos(yaw) * (initial[2] - dy)
-    np.testing.assert_allclose(x, expected_x, atol=1e-10)
-    np.testing.assert_allclose(y, expected_y, atol=1e-10)
-    np.testing.assert_allclose(heading, initial[3] - yaw, atol=1e-10)
-
-  def test_model_noise_is_filtered_for_diagnostics_without_steering_the_command(self):
-    controller = FordVirtualAngleController()
-    values = []
-    for i in range(1600):
-      t = i * .01
-      mt = math.floor((t + 1e-6) / .05) * .05
-      angle = .02 + .01 * math.sin(2 * math.pi * 1.78 * mt)
-      model = circle()
-      model.position.y = model.position.x * math.sin(angle)
-      model.position.x = model.position.x * math.cos(angle)
-      model.orientation.z[:] = angle
-      path = run_step(controller, model, t)
-      self.assertAlmostEqual(path.path_angle, 0.)
-      values.append(controller.diagnostics['model_heading_target'])
-    values = np.array(values[600:])
-    self.assertAlmostEqual(float(np.mean(values)), .02, delta=.001)
-    self.assertLess(float(np.ptp(values)), .009)  # raw heading varies by 0.02 rad
-
-  def test_invalid_or_stale_path_resets_and_reengages_from_zero(self):
-    for overrides in ({'valid': False}, {'active': False}, {'speed': .1}, {'model_time': 0.},
-                      {'measurement_time': 0.}, {'yaw_rate': float('nan')}):
-      controller = FordVirtualAngleController()
-      for i in range(100):
-        run_step(controller, circle(.03), i * .01, desired_curvature=.03)
-      self.assertEqual(run_step(controller, circle(.03), 1., **overrides), FordPath())
-      path = run_step(controller, circle(.03), 1.01, desired_curvature=.03)
-      self.assertLessEqual(abs(path.path_offset), .05)
-      self.assertLessEqual(abs(path.path_angle), .0055)
-
-  def test_clock_faults_clear_the_reference_and_slew_state(self):
-    for now, overrides in ((1.04, {}), (1.25, {}), (1.06, {'measurement_time': 1.049}), (1.06, {'model_time': 1.049})):
-      controller = FordVirtualAngleController()
-      run_step(controller, circle(.03), 1.)
-      run_step(controller, circle(.03), 1.05)
-      path = run_step(controller, circle(.03), now, **overrides)
-      self.assertEqual(path, FordPath())
-      self.assertEqual(controller.diagnostics['status'], 'timing_reset')
-      self.assertIsNone(controller.reference.path)
-      self.assertEqual((controller.offset_request, controller.heading_request), (0., 0.))
-
-  def test_malformed_new_geometry_cannot_keep_an_old_active_request(self):
-    malformed = [None, circle(), circle(), circle()]
-    malformed[1].position.y[5] = float('nan')
-    malformed[2].position.x = []
-    malformed[3].position.x[:] = 0.
-    for model in malformed:
-      controller = FordVirtualAngleController()
-      run_step(controller, circle(.03), 1.)
-      self.assertEqual(run_step(controller, model, 1.05), FordPath())
-      self.assertIsNone(controller.reference.path)
-
-  def test_independent_slew_and_dbc_bounds_during_large_reversal(self):
-    controller = FordVirtualAngleController()
-    previous = FordPath()
-    for i in range(900):
-      curvature = .1 if i < 400 else -.1
-      path = run_step(controller, circle(curvature), i * .01, speed=5., desired_curvature=2 * curvature)
-      self.assertLessEqual(abs(path.path_offset), 5.11)
-      self.assertLessEqual(abs(path.path_angle), .5)
-      self.assertLessEqual(abs(path.path_offset - previous.path_offset), .050001)
-      self.assertLessEqual(abs(path.path_angle - previous.path_angle), .005501)
-      self.assertEqual((path.curvature, path.curvature_rate), (0, 0))
-      previous = path
-      if i == 399:
-        self.assertAlmostEqual(path.path_offset, 5.11)
-    self.assertAlmostEqual(path.path_offset, -5.11)
-    self.assertLess(path.path_angle, -.3)
-
-  def test_float32_and_can_packing_preserve_the_path(self):
-    controller = FordVirtualAngleController()
-    packer = CANPacker('ford_lincoln_base_pt')
-    parser = CANParser('ford_lincoln_base_pt', [('LateralMotionControl2', 100)], 0)
-    bus = CanBus(fingerprint={0: {}})
-    for i in range(600):
-      curvature = .08 if i < 300 else -.08
-      path = run_step(controller, circle(curvature), i * .01, speed=5., desired_curvature=curvature)
-      msg = custom.CarControlSP.new_message()
-      msg.fordLateralPath.pathOffset = path.path_offset
-      msg.fordLateralPath.pathAngle = path.path_angle
-      packet = create_lat_ctl2_msg(packer, bus, 2, -msg.fordLateralPath.pathOffset, -msg.fordLateralPath.pathAngle, 0., 0., i % 16)
-      parser.update([i * 10_000_000, [packet]])
-      decoded = parser.vl['LateralMotionControl2']
-      self.assertAlmostEqual(decoded['LatCtlPathOffst_L_Actl'], -path.path_offset)
-      self.assertAlmostEqual(decoded['LatCtlPath_An_Actl'], -path.path_angle)
-      self.assertEqual(decoded['LatCtlCurv_No_Actl'], 0.)
-
-  def test_recorded_large_maneuvers_keep_substantial_path_demand(self):
-    fixture = Path(__file__).parent / 'fixtures/ford_c2_free_path_routes.npz'
-    metadata = json.loads(fixture.with_suffix('.json').read_text())
-    self.assertEqual(hashlib.sha256(fixture.read_bytes()).hexdigest(), metadata['fixture_sha256'])
-    z = np.load(fixture)
-    models = [SimpleNamespace(position=SimpleNamespace(x=p[0], y=p[1]), orientation=SimpleNamespace(z=p[2])) for p in z['models']]
-    previous_episode = None
-    commands = []
-    for i, t in enumerate(z['t']):
-      if z['episode'][i] != previous_episode:
-        controller = FordVirtualAngleController()
-        previous_episode = z['episode'][i]
-      path = controller.update(models[z['model_index'][i]], z['desired_curvature'][i], yaw_rate=z['yaw_rate'][i], speed=z['speed'][i], now=t,
-                               measurement_time=z['measurement_time'][i], model_time=z['model_time'][i],
-                               reference_time=z['reference_time'][i],
-                               active=bool(z['active'][i]), valid=bool(z['valid'][i]), steering_pressed=bool(z['pressed'][i]))
-      commands.append((path.path_offset, path.path_angle))
-      self.assertEqual((path.curvature, path.curvature_rate), (0, 0))
-    commands = np.array(commands)
-    for episode in range(4):
-      mask = (z['episode'] == episode) & z['evidence']
-      # Do not reward a quiet controller for throwing away large maneuver demand.
-      # This is a command-envelope check against the earlier path controller,
-      # not a claim that the measured motion was solely due to these fields.
-      reference = np.median(abs(z['recorded'][mask, :2]), axis=0)
-      actual = np.median(abs(commands[mask]), axis=0)
-      self.assertGreater(actual[0], .7 * reference[0])
-      self.assertGreater(actual[1], .7 * reference[1])
-      direction = np.sign(np.median(z['recorded'][mask, 1]))
-      self.assertGreater(direction * np.median(commands[mask, 1]), 0.)
-    for episode in (5, 6):
-      mask = (z['episode'] == episode) & z['evidence']
-      # Both newly supplied failed turns must receive heading as a path term,
-      # rather than the v1 controller's tiny acceleration-error correction.
-      self.assertGreater(np.median(abs(commands[mask, 1])), .03)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -1,61 +0,0 @@
-from pathlib import Path
-import tempfile
-from types import SimpleNamespace
-import unittest
-
-from opendbc.car.ford.values import FordFlags
-from openpilot.selfdrive.controls.lib.ford_path import FordPathController, FordPscmObserverPathController
-from openpilot.selfdrive.controls.lib.ford_virtual_angle import (
-  FordVirtualAngleController, select_virtual_angle_controller,
-)
-
-
-def car_params(**kwargs):
-  values = {'brand': 'ford', 'flags': FordFlags.CANFD, 'carFingerprint': 'FORD_F_150_LIGHTNING_MK1',
-                'steerActuatorDelay': 0.2, 'carFw': [SimpleNamespace(ecu='eps', fwVersion=b'RL38-14D003-AA')]}
-  values.update(kwargs)
-  return SimpleNamespace(**values)
-
-
-class TestVirtualAngleSelection(unittest.TestCase):
-  def test_opt_in_and_exact_vehicle_scope(self):
-    for previous in (FordPathController(), FordPscmObserverPathController()):
-      self.assertIs(select_virtual_angle_controller(car_params(), False, previous), previous)
-      for overrides in ({'brand': 'tesla'}, {'flags': 0}, {'carFingerprint': 'FORD_F_150_MK14'}):
-        self.assertIs(select_virtual_angle_controller(car_params(**overrides), True, previous), previous)
-      self.assertIsInstance(select_virtual_angle_controller(car_params(), True, previous), FordVirtualAngleController)
-
-  def test_toggle_controls_selection_independently_of_firmware_query(self):
-    for firmware in ([], [SimpleNamespace(ecu='engine', fwVersion=b'engine')],
-                     [SimpleNamespace(ecu='eps', fwVersion=b'RL38-14D003-AA')],
-                     [SimpleNamespace(ecu='eps', fwVersion=b'other')]):
-      for previous in (FordPathController(), FordPscmObserverPathController()):
-        with self.subTest(firmware=firmware, previous=type(previous).__name__):
-          cp = car_params(carFw=firmware, steerActuatorDelay=.3)
-          self.assertIs(select_virtual_angle_controller(cp, False, previous), previous)
-          chosen = select_virtual_angle_controller(cp, True, previous)
-          self.assertIsInstance(chosen, FordVirtualAngleController)
-          self.assertEqual(chosen.delay, .3)
-
-  def test_old_setting_cannot_enable_new_controller(self):
-    from openpilot.common.params import Params
-    with tempfile.TemporaryDirectory(prefix='ford-virtual-params-') as directory:
-      params = Params(directory)
-      # Simulate a stored key left on an upgraded device; it is no longer registered.
-      Path(params.get_param_path('FordSharedPathController')).write_text('1')
-      self.assertNotIn(b'FordSharedPathController', params.all_keys())
-      self.assertIs(params.get_default_value('FordVirtualAngleController'), False)
-      self.assertFalse(params.get_bool('FordVirtualAngleController'))
-      previous = FordPathController()
-      # Route83 had the toggle on but no EPS firmware records in CarParams.
-      cp = car_params(carFw=[])
-      self.assertIs(select_virtual_angle_controller(cp, params.get_bool('FordVirtualAngleController'), previous), previous)
-      params.put_bool('FordVirtualAngleController', True, block=True)
-      chosen = select_virtual_angle_controller(cp, params.get_bool('FordVirtualAngleController'), previous)
-      params.put_bool('FordVirtualAngleController', False, block=True)
-      self.assertIsInstance(chosen, FordVirtualAngleController)  # only selected at startup
-      self.assertIs(select_virtual_angle_controller(cp, params.get_bool('FordVirtualAngleController'), previous), previous)
-
-
-if __name__ == '__main__':
-  unittest.main()
@@ -10,11 +10,6 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
 from openpilot.selfdrive.modeld.helpers import TG_INPUT_DEVICES_PATH, chestnut_present, modeld_pkl_path


-CAMERA_CONFIGS = [
-  (_ar_ox_fisheye.width, _ar_ox_fisheye.height),  # tici: 1928x1208
-  (_os_fisheye.width, _os_fisheye.height),        # mici: 1344x760
-]
-
 Import('env', 'arch')
 chunker_file = File("#openpilot/common/file_chunker.py")
 lenv = env.Clone()
@@ -24,20 +19,22 @@ tinygrad_files = ["#"+x for x in glob.glob(env.Dir("#tinygrad_repo").relpath + "
                  if 'pycache' not in x and os.path.isfile(os.path.join(tinygrad_root, x))]

 def estimate_pickle_max_size(onnx_size):
-  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
+  # QCOM programs for models with spatial recurrent features can approach 2x
+  # the ONNX size. Overestimating only adds an empty trailing chunk.
+  return 2.0 * onnx_size + 10 * 1024 * 1024

 if arch == 'comma_arm64':
+  from openpilot.common.hardware import HARDWARE
+  camera = _os_fisheye if HARDWARE.get_device_type() == "mici" else _ar_ox_fisheye
+  camera_configs = [(camera.width, camera.height)]
  tg_backend = 'QCOM'
  tg_flags = f'DEV={tg_backend} IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1'
 else:
+  camera_configs = [(c.width, c.height) for c in (_ar_ox_fisheye, _os_fisheye)]
  tg_backend = 'CPU'
  tg_flags = f'DEV=CPU' if arch == 'Darwin' else 'DEV=CPU:LLVM'

 tg_devices = { # which device to put jit inputs to at runtime
-  'openpilot.selfdrive.modeld.modeld': {
-    'default': {'WARP_DEV': tg_backend, 'QUEUE_DEV': tg_backend},
-    'chestnut': {'WARP_DEV': tg_backend, 'QUEUE_DEV': 'AMD'}
-  },
  'openpilot.selfdrive.modeld.dmonitoringmodeld': {
    'default': {'DEV': tg_backend}
  },
@@ -45,7 +42,7 @@ tg_devices = { # which device to put jit inputs to at runtime

 CHESTNUT = chestnut_present()
 if CHESTNUT:
-  chestnut_tg_flags = f'DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV={tg_backend} FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2'
+  chestnut_tg_flags = 'DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1'
  # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
  chestnut_lock = File("models/.chestnut.lock").abspath

@@ -76,10 +73,9 @@ frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
 if not os.getenv('SKIP_TINYGRAD_COMPILE'):
  for chestnut in [False, True] if CHESTNUT else [False]:
    target_pkl_path = File(modeld_pkl_path(chestnut)).abspath
-    # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a chestnut
-    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
+    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
    driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
-    camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
+    camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in camera_configs)
    # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
    taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
@@ -107,7 +103,7 @@ if not os.getenv('SKIP_TINYGRAD_COMPILE'):
    actions = Action(do_compile, "  [CHESTNUT] $TARGET") if chestnut else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
    node = lenv.Command(
      chunk_targets,
-      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
+      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(camera_res_args), Value(chunk_targets), chunker_file],
      actions,
    )
    if chestnut:
@@ -121,7 +117,7 @@ lenv.Command(fn + "_metadata.pkl", [fn + ".onnx"] + tinygrad_files + script_file

 dm_w, dm_h = DM_INPUT_SIZE
 compile_dm_warp_script = [File(f"{modeld_dir}/compile_dm_warp.py")]
-for cam_w, cam_h in CAMERA_CONFIGS:
+for cam_w, cam_h in camera_configs:
  dm_pkl_path = File(f"models/dm_warp_{cam_w}x{cam_h}_tinygrad.pkl").abspath
  cmd = (f'{tg_flags} {mac_brew_string} python3 {modeld_dir}/compile_dm_warp.py '
         f'--camera-resolution {cam_w}x{cam_h} --warp-to {dm_w}x{dm_h} '
@@ -143,5 +139,4 @@ def tg_compile(flags, model_name):
     Action(do_chunk, "  [CHUNK] $TARGET")],
  )

-if not os.getenv('SKIP_TINYGRAD_COMPILE'):
-  tg_compile(tg_flags, 'dmonitoring_model')
+tg_compile(tg_flags, 'dmonitoring_model')
@@ -37,17 +37,12 @@ from tinygrad.engine.jit import TinyJit


 NV12Frame = namedtuple("NV12Frame", ['width', 'height', 'stride', 'y_height', 'uv_height', 'size'])
-WARP_INPUTS = ['tfm', 'big_tfm']
-POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-
-UV_SCALE_MATRIX = np.array([[0.5, 0, 0], [0, 0.5, 0], [0, 0, 1]], dtype=np.float32)
-UV_SCALE_MATRIX_INV = np.linalg.inv(UV_SCALE_MATRIX)
-
-WARP_DEV = os.getenv('WARP_DEV')
+MODELD_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']


-def make_random_images(keys, shape, device=None):
-  return {k: Tensor.randint(shape, low=0, high=256, dtype='uint8', device=device).realize() for k in keys}
+def nv12_copy_size(stride: int, y_height: int, uv_height: int) -> int:
+  # Retain the padded Y and UV plane storage, but skip the trailing kernel/guard allocation.
+  return stride * (y_height + uv_height)


 def warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad, border_fill_val=None):
@@ -99,7 +94,7 @@ def make_frame_prepare(nv12: NV12Frame, model_w, model_h):

  def frame_prepare_tinygrad(input_frame, M_inv):
    # UV_SCALE @ M_inv @ UV_SCALE_INV simplifies to elementwise scaling
-    M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=WARP_DEV)
+    M_inv_uv = M_inv * Tensor([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], device=Device.DEFAULT)
    # deinterleave NV12 UV plane (UVUV... -> separate U, V)
    uv = input_frame[uv_offset:uv_offset + uv_height * stride].reshape(uv_height, stride)
    with Context(SPLIT_REDUCEOP=0):
@@ -118,49 +113,43 @@ def make_frame_prepare(nv12: NV12Frame, model_w, model_h):
  return frame_prepare_tinygrad


-def make_warp_input_queues(vision_input_shapes, frame_skip, device):
-  img = vision_input_shapes['img']  # (1, 12, 128, 256)
-  n_frames = img[1] // 6
-  img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3])
-
-  npy = {
-    'tfm': np.zeros((3, 3), dtype=np.float32),
-    'big_tfm': np.zeros((3, 3), dtype=np.float32),
-  }
-  input_queues = {
-    'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
-    **{k: Tensor(v, device='NPY').realize() for k, v in npy.items()},
-  }
-  return input_queues, npy
-
-
 def get_policy_npy_shapes(input_shapes):
  dp = input_shapes['desire_pulse']  # (1, 25, 8)
  tc = input_shapes['traffic_convention']  # (1, 2)
  at = input_shapes['action_t']  # (1, 2)
-  fb = input_shapes['features_buffer']  # (1, 24, 512)
+  fb = input_shapes['features_buffer']  # (1, T-1, ...) e.g. (1, 24, 32, 512) with spatial features
+  feat_dim = math.prod(fb[2:])
  # TODO prev_feat shouldn't exist and be handled inside the JIT, but corrupt on QCOM for now
-  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
+  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], feat_dim)}
  return shapes, [math.prod(s) for s in shapes.values()]


-def make_input_queues(input_shapes, frame_skip, device):
-  input_queues, npy = make_warp_input_queues(input_shapes, frame_skip, device)
-
-  fb = input_shapes['features_buffer']  # (1, 24, 512), past features only; the model appends the current frame's feature
+def make_input_queues(input_shapes, frame_skip, device, frame_copy_size):
+  img = input_shapes['img']  # (1, 12, 128, 256)
+  fb = input_shapes['features_buffer']  # (1, T-1, ...), past features only; the model appends the current frame's feature
+  feat_dim = math.prod(fb[2:])
  dp = input_shapes['desire_pulse']  # (1, 25, 8)
+  n_frames = img[1] // 6
+  img_buf_shape = (frame_skip * (n_frames - 1) + 1, 6, img[2], img[3])

-  shapes, sizes = get_policy_npy_shapes(input_shapes)
-  packed_npy_inputs = np.zeros(sum(sizes), dtype=np.float32)
+  policy_shapes, _ = get_policy_npy_shapes(input_shapes)
+  shapes = {'tfm': (3, 3), 'big_tfm': (3, 3)} | policy_shapes
+  sizes = [math.prod(s) for s in shapes.values()]
+  packed_npy_size = sum(sizes) * np.dtype(np.float32).itemsize
+  packed_input = np.zeros(packed_npy_size + 2 * frame_copy_size, dtype=np.uint8)
+  packed_npy_inputs = packed_input[:packed_npy_size].view(np.float32)
+  frames = packed_input[packed_npy_size:]
+  frame_views = {'img': frames[:frame_copy_size], 'big_img': frames[frame_copy_size:]}
  # views into the packed inputs, to be refilled at runtime
-  npy.update({k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)})
-  input_queues.update({
-    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
+  npy = {k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)}
+  input_queues = {
+    'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
+    'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
+    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], feat_dim), dtype=np.float32), device=device).contiguous().realize(),
    'desire_q': Tensor(np.zeros((frame_skip * dp[1], dp[0], dp[2]), dtype=np.float32), device=device).contiguous().realize(),
-    'packed_npy_inputs': Tensor(packed_npy_inputs, device='NPY').realize(),
-  })
-  return input_queues, npy
+    'packed_npy_inputs': Tensor(packed_input, device='NPY').realize(),
+  }
+  return input_queues, npy, frame_views


 def shift_and_sample(buf, new_val, sample_fn):
@@ -176,13 +165,15 @@ def sample_desire(buf, frame_skip):
  return buf.reshape(-1, frame_skip, *buf.shape[1:]).max(1).flatten(0, 1).unsqueeze(0)


-def make_warp(nv12, model_w, model_h, frame_skip):
+def make_warp(nv12, model_w, model_h):
  frame_prepare = make_frame_prepare(nv12, model_w, model_h)

  def warp(tfm, big_tfm, frame, big_frame):
-    tfm = tfm.to(WARP_DEV)
-    big_tfm = big_tfm.to(WARP_DEV)
-    Tensor.realize(tfm, big_tfm)
+    tfm = tfm.to(Device.DEFAULT)
+    big_tfm = big_tfm.to(Device.DEFAULT)
+    frame = frame.to(Device.DEFAULT)
+    big_frame = big_frame.to(Device.DEFAULT)
+    Tensor.realize(tfm, big_tfm, frame, big_frame)

    warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
    warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
@@ -195,10 +186,10 @@ def make_run_policy(model_runner, model_metadata, frame_skip):
  sample_desire_fn = partial(sample_desire, frame_skip=frame_skip)
  sample_skip_fn = partial(sample_skip, frame_skip=frame_skip)
  npy_shapes, npy_sizes = get_policy_npy_shapes(model_metadata['input_shapes'])
+  model_input_dtypes = {name: spec.dtype for name, spec in model_runner.graph_inputs.items()}

  def run_policy(warped, img_q, big_img_q, feat_q, desire_q, packed_npy_inputs):
    packed_npy_inputs = packed_npy_inputs.to(Device.DEFAULT)
-    warped = warped.to(Device.DEFAULT)
    Tensor.realize(packed_npy_inputs, warped)

    img = shift_and_sample(img_q, warped[0:1], sample_skip_fn)
@@ -211,33 +202,50 @@ def make_run_policy(model_runner, model_metadata, frame_skip):
    inputs = {
      'img': img,
      'big_img': big_img,
-      'features_buffer': feat_buf,
+      'features_buffer': feat_buf.reshape(model_metadata['input_shapes']['features_buffer']),
      'desire_pulse': desire_buf,
      'traffic_convention': traffic_convention,
      'action_t': action_t,
    }
+    inputs = {name: value.cast(model_input_dtypes[name]) for name, value in inputs.items()}
    out = next(iter(model_runner(inputs).values())).cast('float32')
    return out,
  return run_policy


-def compile_jit(jit, make_random_inputs, input_keys, make_queues):
-  SEED = 42
-  def random_inputs_run(fn, seed, test_val=None, test_buffers=None, expect_match=True):
-    input_queues, npy = make_queues(Device.DEFAULT)
-    rng = np.random.default_rng(seed)
-    Tensor.manual_seed(seed)
+def make_run_model(warp, run_policy, model_metadata, frame_copy_size):
+  _, policy_sizes = get_policy_npy_shapes(model_metadata['input_shapes'])
+  packed_npy_size = (18 + sum(policy_sizes)) * np.dtype(np.float32).itemsize

-    testing = test_val is not None or test_buffers is not None
-    n_runs = 1 if testing else 3
+  def run_model(img_q, big_img_q, feat_q, desire_q, packed_npy_inputs):
+    packed_input = packed_npy_inputs.to(Device.DEFAULT)
+    Tensor.realize(packed_input)
+    packed_npy_inputs = packed_input[:packed_npy_size].bitcast('float32')
+    frame = packed_input[packed_npy_size:packed_npy_size + frame_copy_size]
+    big_frame = packed_input[packed_npy_size + frame_copy_size:]
+    tfm, big_tfm, policy_inputs = packed_npy_inputs.split([9, 9, sum(policy_sizes)])
+    warped = warp(tfm.reshape(3, 3), big_tfm.reshape(3, 3), frame, big_frame)
+    return run_policy(warped, img_q, big_img_q, feat_q, desire_q, policy_inputs)
+  return run_model
+
+
+def compile_jit(jit, input_keys, make_queues, benchmark_runs):
+  if benchmark_runs < 1:
+    raise ValueError("benchmark_runs must be at least 1")
+
+  SEED = 42
+  def random_inputs_run(fn, seed, n_runs, test_val=None, test_buffers=None, expect_match=True):
+    input_queues, npy, frame_views = make_queues(Device.DEFAULT)
+    rng = np.random.default_rng(seed)

    for i in range(n_runs):
      for v in npy.values():
        v[:] = rng.standard_normal(v.shape).astype(v.dtype)
+      for v in frame_views.values():
+        v[:] = rng.integers(0, 256, size=v.shape, dtype=np.uint8)
      Device.default.synchronize()
-      random_inputs = make_random_inputs()
      st = time.perf_counter()
-      outs = fn(**{k: input_queues[k] for k in input_keys}, **random_inputs)
+      outs = fn(**{k: input_queues[k] for k in input_keys})
      mt = time.perf_counter()
      Device.default.synchronize()
      et = time.perf_counter()
@@ -256,14 +264,15 @@ def compile_jit(jit, make_random_inputs, input_keys, make_queues):
    return val, buffers

  print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED)
-  print('pickle round trip')
+  test_val, test_buffers = random_inputs_run(jit, SEED, 3)
+  print(f'pickle round trip ({benchmark_runs} runs per seed)')
  with tempfile.TemporaryFile(dir=".") as f:
    dump_oob(jit, f)
    f.seek(0)
-    jit = load_oob(f)
-  random_inputs_run(jit, SEED, test_val, test_buffers, expect_match=True)
-  random_inputs_run(jit, SEED+1, test_val, test_buffers, expect_match=False)
+    loaded_jit = load_oob(f)
+  random_inputs_run(loaded_jit, SEED, benchmark_runs, test_val, test_buffers, expect_match=True)
+  random_inputs_run(loaded_jit, SEED+1, benchmark_runs, test_val, test_buffers, expect_match=False)
+  # Keep the original so per-resolution JITs share model weight buffers in the final pickle.
  return jit


@@ -292,27 +301,31 @@ if __name__ == "__main__":
  p.add_argument('--onnx', required=True)
  p.add_argument('--output', required=True)
  p.add_argument('--frame-skip', type=int, required=True)
+  p.add_argument('--benchmark-runs', type=int, default=1,
+                 help='timed loaded-JIT runs for each correctness seed')
  args = p.parse_args()

  model_path = read_file_chunked_to_disk(args.onnx)
  model_w, model_h = args.model_size

  model_runner = OnnxRunner(model_path)
-  out = {'metadata': make_metadata_dict(model_path)}
+  out = {
+    'metadata': make_metadata_dict(model_path),
+    'input_devices': {'model': Device.DEFAULT},
+    'run_model': {},
+  }

-  run_policy_jit = TinyJit(make_run_policy(model_runner, out['metadata'], args.frame_skip), prune=True)
-
-  make_policy_queues = partial(make_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, *out['metadata']['input_shapes']['img'][2:]), device=WARP_DEV)
-  out['run_policy'] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS,
-                                  make_policy_queues)
+  run_policy = make_run_policy(model_runner, out['metadata'], args.frame_skip)

  for cam_w, cam_h in args.camera_resolutions:
    nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
-    warp = TinyJit(make_warp(nv12, model_w, model_h, args.frame_skip), prune=True)
-    make_warp_queues = partial(make_warp_input_queues, out['metadata']['input_shapes'], args.frame_skip)
-    out[(cam_w,cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
+    frame_copy_size = nv12_copy_size(nv12.stride, nv12.y_height, nv12.uv_height)
+    make_model_queues = partial(make_input_queues, out['metadata']['input_shapes'], args.frame_skip,
+                                frame_copy_size=frame_copy_size)
+    warp = make_warp(nv12, model_w, model_h)
+    run_model_jit = TinyJit(make_run_model(warp, run_policy, out['metadata'], frame_copy_size), prune=True)
+    out['run_model'][(cam_w,cam_h)] = compile_jit(run_model_jit, MODELD_INPUTS, make_model_queues,
+                                                  args.benchmark_runs)

  with open(args.output, "wb") as f:
    dump_oob(out, f)
@@ -64,6 +64,7 @@ def fill_driving_model_data(msg: capnp._DynamicStructBuilder, modelv2_send: capn
  driving_model_data.frameIdExtra = modelV2.frameIdExtra
  driving_model_data.frameDropPerc = modelV2.frameDropPerc
  driving_model_data.modelExecutionTime = modelV2.modelExecutionTime
+  driving_model_data.big = modelV2.big
  driving_model_data.action = modelV2.action
  driving_model_data.meta.laneChangeState = modelV2.meta.laneChangeState
  driving_model_data.meta.laneChangeDirection = modelV2.meta.laneChangeDirection
@@ -7,10 +7,12 @@ import tempfile
 from pathlib import Path

 from openpilot.common.file_chunker import get_manifest_path
-from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_USB_IDS, USB_DEVICES_PATH
+from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, USB_DEVICES_PATH, is_chestnut_usb_id

 MODELS_DIR = Path(__file__).resolve().parent / 'models'
 TG_INPUT_DEVICES_PATH = MODELS_DIR / 'tg_input_devices.json'
+CHESTNUT_POWERED_VOLTAGE = 5000
+CHESTNUT_PCIE_READY = 0x78


 def get_tg_input_devices(process_name: str, chestnut: bool):
@@ -50,7 +52,7 @@ def chestnut_present() -> bool:
    try:
      usb_id = (int((d / "idVendor").read_text(), 16), int((d / "idProduct").read_text(), 16))
      product = (d / "product").read_text().strip()
-      if usb_id in CHESTNUT_USB_IDS and product == f"custom {CHESTNUT_FW_VERSION}-CLEAN":
+      if is_chestnut_usb_id(*usb_id) and product == CHESTNUT_USB_PRODUCT:
        return True
    except Exception:
      pass
@@ -58,3 +60,7 @@ def chestnut_present() -> bool:

 def chestnut_compiled() -> bool:
  return Path(get_manifest_path(modeld_pkl_path(chestnut=True))).is_file()
+
+
+def chestnut_ready(state) -> bool:
+  return state.supplyVoltage >= CHESTNUT_POWERED_VOLTAGE and not state.supplyFault and state.pcieLtssm == CHESTNUT_PCIE_READY
@@ -4,8 +4,8 @@ import ctypes
 from functools import cached_property
 import os
 os.environ['GMMU'] = '0' # for chestnut fast loading, noop for qcom
-from tinygrad.tensor import Tensor
 from tinygrad.device import Device
+import usb1
 import struct
 import threading
 import time
@@ -28,17 +28,17 @@ from openpilot.common.transformations.model import get_warp_matrix
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
 from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, should_stop, smooth_value, get_curvature_from_plan
 from openpilot.selfdrive.modeld.parse_model_outputs import Parser
-from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, WARP_INPUTS, POLICY_INPUTS
+from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, nv12_copy_size, MODELD_INPUTS
 from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_driving_model_data, fill_pose_msg, PublishState
 from openpilot.common.file_chunker import open_file_chunked
+from openpilot.common.hardware.usb import CHESTNUT_USB_IDS
 from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
-from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, modeld_pkl_path, get_tg_input_devices, load_oob
+from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, chestnut_ready, modeld_pkl_path, load_oob

 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
 from openpilot.sunnypilot.selfdrive.controls.lib.relc import RoadEdgeLaneChangeController

-PROCESS_NAME = "openpilot.selfdrive.modeld.modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')

 LAT_SMOOTH_SECONDS = 0.0
@@ -83,6 +83,37 @@ class ChestnutState:
    self.valid = True
    self.sends = 0
    self.metrics = {}
+    self._asm_usb = None
+
+  def _close_asm_usb(self) -> None:
+    if self._asm_usb is not None:
+      self._asm_usb.close()
+      self._asm_usb = None
+
+  def _open_asm_usb(self):
+    context = usb1.USBContext()
+    for vendor_id, product_id in CHESTNUT_USB_IDS:
+      if (handle := context.openByVendorIDAndProductID(vendor_id, product_id, skip_on_error=True)) is not None:
+        return handle
+    context.close()
+
+  def _read_ina(self) -> tuple[int, int, bool]:
+    if "AMD" in Device._opened_devices and self._asm_usb is None:
+      try:
+        raw = Device["AMD"].iface.pci_dev.usb.usb.control_read(0xC0, 5)
+        return struct.unpack('<Hh?', bytes(raw))
+      except Exception:
+        pass
+    if self._asm_usb is None:
+      self._asm_usb = self._open_asm_usb()
+    if self._asm_usb is None:
+      raise usb1.USBErrorNoDevice
+    try:
+      raw = self._asm_usb.controlRead(0xC0, 0xC0, 0, 0, 5, timeout=100)
+    except usb1.USBError:
+      self._close_asm_usb()
+      raise
+    return struct.unpack('<Hh?', bytes(raw))

  @cached_property
  def power_limit(self) -> int:
@@ -118,13 +149,15 @@ class ChestnutState:
        setattr(state, k, v)

    asm_valid = False
+    try:
+      # ASM runs on USB-C power, these still read without a gpu
+      state.supplyVoltage, state.supplyCurrent, state.supplyFault = self._read_ina()
+      asm_valid = True
+    except Exception:
+      pass
    if "AMD" in Device._opened_devices:
      try:
-        # ASM runs on USB-C power, these still read without a gpu
-        asm = Device["AMD"].iface.pci_dev.usb
-        state.pcieLtssm = asm.read(0xB450, 1)[0]
-        state.supplyVoltage, state.supplyCurrent = struct.unpack('<Hh', bytes(asm.usb.control_read(0xC0, 5))[:4])
-        asm_valid = True
+        state.pcieLtssm = Device["AMD"].iface.pci_dev.usb.read(0xB450, 1)[0]
      except Exception:
        pass

@@ -147,9 +180,9 @@ class ModelState(ModelStateBase):

  def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
    ModelStateBase.__init__(self)
-    input_devices = get_tg_input_devices(PROCESS_NAME, chestnut)
-    self.WARP_DEV, self.QUEUE_DEV = input_devices['WARP_DEV'], input_devices['QUEUE_DEV']
    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
+    input_devices = jits['input_devices']
+    self.model_device = input_devices['model']
    metadata = jits['metadata']
    self.input_shapes = metadata['input_shapes']
    self.vision_input_names = [k for k in self.input_shapes if 'img' in k]
@@ -159,13 +192,11 @@ class ModelState(ModelStateBase):
    self.chestnut = chestnut

    self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
-    self.full_frames: dict[str, Tensor] = {}
-    self._blob_cache: dict[tuple[str, int], Tensor] = {}
+    self.frame_copy_size = nv12_copy_size(*get_nv12_info(cam_w, cam_h)[:3])
+    self.input_queues, self.npy, self.frame_views = make_input_queues(
+      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
    self.parser = Parser()
-    self.frame_buf_params = {k: get_nv12_info(cam_w, cam_h) for k in ('img', 'big_img')}
-    self.run_policy = jits['run_policy']
-    self.warp = jits[(cam_w,cam_h)]
+    self.run_model = jits['run_model'][(cam_w,cam_h)]

  def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
    parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
@@ -173,14 +204,8 @@ class ModelState(ModelStateBase):

  def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
          inputs: dict[str, np.ndarray], after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray]:
-    for key in bufs.keys():
-      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
-      yuv_size = self.frame_buf_params[key][3]
-      # There is a ringbuffer of imgs, just cache tensors pointing to all of them
-      cache_key = (key, ptr)
-      if cache_key not in self._blob_cache:
-        self._blob_cache[cache_key] = Tensor.from_blob(ptr, (yuv_size,), dtype='uint8', device=self.WARP_DEV)
-      self.full_frames[key] = self._blob_cache[cache_key]
+    for key, buf in bufs.items():
+      np.copyto(self.frame_views[key], np.frombuffer(buf.data, dtype=np.uint8, count=self.frame_copy_size))

    # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
    inputs['desire_pulse'][0] = 0
@@ -191,11 +216,7 @@ class ModelState(ModelStateBase):
    self.npy['tfm'][:,:] = transforms['img'][:,:]
    self.npy['big_tfm'][:,:] = transforms['big_img'][:,:]

-    warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames['img'], big_frame=self.full_frames['big_img'])
-
-    outs, = self.run_policy(
-      **{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped
-    )
+    outs, = self.run_model(**{k: self.input_queues[k] for k in MODELD_INPUTS})
    if after_enqueue is not None:
      after_enqueue()
    model_output = outs.numpy()[0]
@@ -209,25 +230,37 @@ class ModelState(ModelStateBase):
    return outputs_dict

  def warmup(self) -> None:
-    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], dtype=np.uint8) for k in self.vision_input_names}
+    dummy_frames = {k: np.zeros(self.frame_copy_size, dtype=np.uint8) for k in self.vision_input_names}
    eye = np.eye(3, dtype=np.float32)
    dims = {'desire_pulse': ModelConstants.DESIRE_LEN, 'traffic_convention': 2, 'action_t': 2}
    self.run(dummy_frames, dict.fromkeys(self.vision_input_names, eye), {k: np.zeros(v, dtype=np.float32) for k, v in dims.items()})
-    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
+    self.input_queues, self.npy, self.frame_views = make_input_queues(
+      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
    self.prev_desire[:] = 0
-    self.full_frames.clear()
-    self._blob_cache.clear()


 def main(demo=False):
  cloudlog.warning("modeld init")

-  CHESTNUT = chestnut_present() and chestnut_compiled()
+  chestnut_available = chestnut_present() and chestnut_compiled()
+  CHESTNUT = False
+  if chestnut_available:
+    poller = messaging.Poller()
+    sock = messaging.sub_sock("chestnutState", poller=poller, conflate=True)
+    deadline = time.monotonic() + 4. / SERVICE_LIST['deviceState'].frequency
+    while not CHESTNUT and (remaining := deadline - time.monotonic()) > 0.:
+      if not poller.poll(round(remaining * 1000)):
+        break
+      msg = messaging.recv_one_or_none(sock)
+      CHESTNUT = msg is not None and msg.valid and chestnut_ready(msg.chestnutState)
  if CHESTNUT:
    os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
  params = Params()
  params.put_bool("ChestnutLoading", CHESTNUT)
-  params.remove("ChestnutActive")
+  if chestnut_available and not CHESTNUT:
+    params.put_bool("ChestnutActive", False)
+  else:
+    params.remove("ChestnutActive")

  config_realtime_process(7, 54)

@@ -271,7 +304,11 @@ def main(demo=False):
    loader.start()
    loader.join(BIG_MODEL_TIMEOUT)
    model = big_model
+    if model is None:
+      params.put_bool("ChestnutModelError", True)
    params.put_bool("ChestnutActive", model is not None)
+    if model is not None:
+      params.remove("ChestnutModelError")

  small_model = ModelState(vipc_client_main.width, vipc_client_main.height, False) if model is None or CHESTNUT else None
  if model is None:
@@ -405,6 +442,7 @@ def main(demo=False):
        raise
      # fallback to small model
      cloudlog.exception("big model failed, fall back to small")
+      params.put_bool("ChestnutModelError", True)
      params.put_bool("ChestnutActive", False)
      assert small_model is not None
      model = small_model
@@ -431,12 +469,11 @@ def main(demo=False):
      l_lane_change_prob = desire_state[log.Desire.laneChangeLeft]
      r_lane_change_prob = desire_state[log.Desire.laneChangeRight]
      lane_change_prob = l_lane_change_prob + r_lane_change_prob
-      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob)
-      modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
-      modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
-
      mdv2sp_send = messaging.new_message('modelDataV2SP')
      left_edge, right_edge = RELC.update_and_fill(modelv2_send.modelV2, mdv2sp_send.modelDataV2SP, v_ego)
+      DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob, left_edge, right_edge)
+      modelv2_send.modelV2.meta.laneChangeState = DH.lane_change_state
+      modelv2_send.modelV2.meta.laneChangeDirection = DH.lane_change_direction
      mdv2sp_send.modelDataV2SP.laneTurnDirection = DH.lane_turn_direction

      fill_driving_model_data(drivingdata_send, modelv2_send)
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a501760a9d1d5fef0eab2b8c5d122d06124fc26dc8e0782e0aa94b82a208f0ff
-size 1757355221
+oid sha256:1791d5940b2c048d0639813426dd2cf1d6f2a6727ed51e17c8bcea8bbe754123
+size 765950064
@@ -123,22 +123,22 @@ void fill_panda_state(cereal::PandaState::Builder &ps, cereal::PandaState::Panda
  ps.setUptime(health.uptime_pkt);
  ps.setSafetyTxBlocked(health.safety_tx_blocked_pkt);
  ps.setSafetyRxInvalid(health.safety_rx_invalid_pkt);
-  ps.setIgnitionLine(health.ignition_line_pkt);
-  ps.setIgnitionCan(health.ignition_can_pkt);
-  ps.setControlsAllowed(health.controls_allowed_pkt);
+  ps.setIgnitionLine((health.flags_pkt & HEALTH_FLAG_IGNITION_LINE) != 0U);
+  ps.setIgnitionCan((health.flags_pkt & HEALTH_FLAG_IGNITION_CAN) != 0U);
+  ps.setControlsAllowed((health.flags_pkt & HEALTH_FLAG_CONTROLS_ALLOWED) != 0U);
  ps.setTxBufferOverflow(health.tx_buffer_overflow_pkt);
  ps.setRxBufferOverflow(health.rx_buffer_overflow_pkt);
  ps.setPandaType(hw_type);
  ps.setSafetyModel(cereal::CarParams::SafetyModel(health.safety_mode_pkt));
  ps.setSafetyParam(health.safety_param_pkt);
  ps.setFaultStatus(cereal::PandaState::FaultStatus(health.fault_status_pkt));
-  ps.setPowerSaveEnabled((bool)(health.power_save_enabled_pkt));
-  ps.setHeartbeatLost((bool)(health.heartbeat_lost_pkt));
+  ps.setPowerSaveEnabled((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U);
+  ps.setHeartbeatLost((health.flags_pkt & HEALTH_FLAG_HEARTBEAT_LOST) != 0U);
  ps.setAlternativeExperience(health.alternative_experience_pkt);
  ps.setHarnessStatus(cereal::PandaState::HarnessStatus(health.car_harness_status_pkt));
-  ps.setInterruptLoad(health.interrupt_load_pkt);
+  ps.setInterruptLoad(health.interrupt_load_pkt / 255.0f);
  ps.setFanPower(health.fan_power);
-  ps.setSafetyRxChecksInvalid((bool)(health.safety_rx_checks_invalid_pkt));
+  ps.setSafetyRxChecksInvalid((health.flags_pkt & HEALTH_FLAG_SAFETY_RX_CHECKS_INVALID) != 0U);
  ps.setSpiErrorCount(health.spi_error_count_pkt);
  ps.setSbu1Voltage(health.sbu1_voltage_mV / 1000.0f);
  ps.setSbu2Voltage(health.sbu2_voltage_mV / 1000.0f);
@@ -198,10 +198,10 @@ std::optional<bool> send_panda_states(PubMaster *pm, Panda *panda, bool is_onroa
  }

  if (spoofing_started) {
-    health.ignition_line_pkt = 1;
+    health.flags_pkt |= HEALTH_FLAG_IGNITION_LINE;
  }

-  bool ignition_local = ((health.ignition_line_pkt != 0) || (health.ignition_can_pkt != 0)) && !always_offroad;
+  bool ignition_local = ((health.flags_pkt & (HEALTH_FLAG_IGNITION_LINE | HEALTH_FLAG_IGNITION_CAN)) != 0U) && !always_offroad;

  // Make sure CAN buses are live: safety_setter_thread does not work if Panda CAN are silent and there is only one other CAN node
  if (health.safety_mode_pkt == (uint8_t)(cereal::CarParams::SafetyModel::SILENT)) {
@@ -209,7 +209,7 @@ std::optional<bool> send_panda_states(PubMaster *pm, Panda *panda, bool is_onroa
  }

  bool power_save_desired = !ignition_local;
-  if (health.power_save_enabled_pkt != power_save_desired) {
+  if (((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U) != power_save_desired) {
    panda->set_power_saving(power_save_desired);
  }

@@ -19,6 +19,30 @@
  },
  "Offroad_ChestnutBranch": {
    "text": "Chestnut detected! Switch to the %1 branch to use chestnut-class models.",
+    "severity": -1
+  },
+  "Offroad_ChestnutNotDetected": {
+    "text": "Chestnut not detected. Check USB and 12V connections.",
+    "severity": 0
+  },
+  "Offroad_ChestnutOverheated": {
+    "text": "Chestnut overheated. Ensure good airflow. Current GPU temperature is %1.",
+    "severity": 0
+  },
+  "Offroad_ChestnutPcieUnavailable": {
+    "text": "%1",
+    "severity": 0
+  },
+  "Offroad_ChestnutUncompiled": {
+    "text": "Chestnut model not compiled. Keep ignition on and reboot the comma.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUpdateFailed": {
+    "text": "Chestnut update failed. Check the USB cable.",
+    "severity": 0
+  },
+  "Offroad_ChestnutUsbSlow": {
+    "text": "Chestnut USB link is slow. Check the USB cable. The current speed is %1.",
    "severity": 0
  },
  "Offroad_UnregisteredHardware": {
@@ -32,14 +32,7 @@ from openpilot.sunnypilot.selfdrive.car.car_specific import CarSpecificEventsSP
 from openpilot.sunnypilot.selfdrive.car.cruise_helpers import CruiseHelper
 from openpilot.sunnypilot.selfdrive.car.intelligent_cruise_button_management.controller import IntelligentCruiseButtonManagement
 from openpilot.sunnypilot.selfdrive.selfdrived.button_state_tracker import ButtonStateTracker
-from openpilot.sunnypilot.selfdrive.selfdrived.assisted_driving_milestones import (
-  AssistCategory,
-  AssistedDrivingMilestones,
-  MilestoneEvent,
-  MilestoneStore,
-)
 from openpilot.sunnypilot.selfdrive.selfdrived.events import EventsSP
-from openpilot.sunnypilot.system.statsd import statlog

 REPLAY = "REPLAY" in os.environ
 SIMULATION = "SIMULATION" in os.environ
@@ -95,8 +88,7 @@ class SelfdriveD(CruiseHelper):
    self.big_model_ready_t = 0.

    # Setup sockets
-    self.pm = messaging.PubMaster(['selfdriveState', 'onroadEvents'] +
-                                  ['selfdriveStateSP', 'onroadEventsSP', 'assistedDrivingMilestoneState'])
+    self.pm = messaging.PubMaster(['selfdriveState', 'onroadEvents'] + ['selfdriveStateSP', 'onroadEventsSP'])

    self.gps_location_service = get_gps_location_service(self.params)
    self.gps_packets = [self.gps_location_service]
@@ -135,7 +127,6 @@ class SelfdriveD(CruiseHelper):
      self.params.remove("ExperimentalMode")

    self.CS_prev = car.CarState.new_message()
-    self.car_state_log_mono_time = 0
    self.AM = AlertManager()
    self.events = Events()

@@ -146,11 +137,6 @@ class SelfdriveD(CruiseHelper):
    self.cruise_mismatch_counter = 0
    self.last_steering_pressed_frame = 0
    self.distance_traveled = 0
-    self.assisted_driving_milestones = AssistedDrivingMilestones(MilestoneStore(self.params))
-    self.assisted_driving_milestones_enabled = bool(self.params.get("AssistedDrivingMilestonesEnabled", return_default=True))
-    self.assisted_driving_milestone_drive_id = ""
-    self._milestone_event: MilestoneEvent | None = None
-    self._milestone_event_expires_ns = 0
    self.last_functional_fan_frame = 0
    self.events_prev = []
    self.logged_comm_issue = None
@@ -542,8 +528,6 @@ class SelfdriveD(CruiseHelper):
  def data_sample(self):
    _car_state = messaging.recv_one(self.car_state_sock)
    CS = _car_state.carState if _car_state else self.CS_prev
-    if _car_state is not None:
-      self.car_state_log_mono_time = _car_state.logMonoTime

    self.sm.update(0)

@@ -662,31 +646,6 @@ class SelfdriveD(CruiseHelper):
      self.pm.send('onroadEventsSP', ce_send_sp)
    self.events_sp_prev = self.events_sp.names.copy()

-  def publish_assisted_driving_milestones(self, now_ns: int, event: MilestoneEvent | None) -> None:
-    if event is not None:
-      self._milestone_event = event
-      self._milestone_event_expires_ns = now_ns + 1_000_000_000
-    elif now_ns >= self._milestone_event_expires_ns:
-      self._milestone_event = None
-
-    if event is None and self.sm.frame % 10 != 0:
-      return
-
-    snapshot = self.assisted_driving_milestones.snapshot()
-    msg = messaging.new_message("assistedDrivingMilestoneState")
-    msg.valid = True
-    state = msg.assistedDrivingMilestoneState
-    state.enabled = self.assisted_driving_milestones_enabled
-    state.madsDistanceMeters = snapshot.distances_meters[AssistCategory.MADS]
-    state.fullAssistDistanceMeters = snapshot.distances_meters[AssistCategory.FULL_ASSIST]
-    if self._milestone_event is not None:
-      state.event.id = self._milestone_event.event_id
-      state.event.category = self._milestone_event.category.value
-      state.event.distanceMeters = self._milestone_event.distance_meters
-      state.event.previousDistanceMeters = self._milestone_event.previous_distance_meters
-      state.event.unit = self._milestone_event.unit.value
-    self.pm.send("assistedDrivingMilestoneState", msg)
-
  def step(self):
    CS = self.data_sample()
    self.update_events(CS)
@@ -696,28 +655,6 @@ class SelfdriveD(CruiseHelper):
      self.mads.update(CS)
    self.update_alerts(CS)

-    now_ns = time.monotonic_ns()
-    if not self.assisted_driving_milestone_drive_id:
-      self.assisted_driving_milestone_drive_id = self.params.get("CurrentRoute") or ""
-      self.assisted_driving_milestones.set_drive_id(self.assisted_driving_milestone_drive_id)
-    car_control = self.sm['carControl']
-    milestone_event = self.assisted_driving_milestones.update(
-      self.car_state_log_mono_time,
-      CS.vEgo,
-      lat_active=car_control.latActive,
-      long_active=car_control.longActive,
-      is_metric=self.is_metric,
-      enabled=self.assisted_driving_milestones_enabled,
-    )
-    if milestone_event is not None:
-      cloudlog.event("assisted_driving_milestone_reached",
-                     event_id=milestone_event.event_id,
-                     category=milestone_event.category.value,
-                     distance_meters=milestone_event.distance_meters)
-      statlog.gauge(f"assisted_driving_milestone.{milestone_event.category.value}.meters",
-                    milestone_event.distance_meters)
-    self.publish_assisted_driving_milestones(now_ns, milestone_event)
-
    self.button_state_tracker.update(CS)
    self.publish_selfdriveState(CS)

@@ -730,7 +667,6 @@ class SelfdriveD(CruiseHelper):
      self.disengage_on_accelerator = self.params.get_bool("DisengageOnAccelerator")
      self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
      self.personality = self.params.get("LongitudinalPersonality", return_default=True)
-      self.assisted_driving_milestones_enabled = bool(self.params.get("AssistedDrivingMilestonesEnabled", return_default=True))

      self.mads.read_params()
      time.sleep(0.1)
@@ -744,7 +680,6 @@ class SelfdriveD(CruiseHelper):
        self.step()
        self.rk.monitor_time()
    finally:
-      self.assisted_driving_milestones.close()
      e.set()
      t.join()

@@ -152,7 +152,7 @@ def migrate_drivingModelData(msgs):
  add_ops = []
  for _, msg in msgs:
    dmd = messaging.new_message('drivingModelData', valid=msg.valid, logMonoTime=msg.logMonoTime)
-    for field in ["frameId", "frameIdExtra", "frameDropPerc", "modelExecutionTime", "action"]:
+    for field in ["frameId", "frameIdExtra", "frameDropPerc", "modelExecutionTime", "big", "action"]:
      setattr(dmd.drivingModelData, field, getattr(msg.modelV2, field))
    for meta_field in ["laneChangeState", "laneChangeState"]:
      setattr(dmd.drivingModelData.meta, meta_field, getattr(msg.modelV2.meta, meta_field))
@@ -33,9 +33,9 @@ MODEL_REPLAY_BUCKET="model_replay_master"
 GITHUB = GithubUtils(API_TOKEN, DATA_TOKEN)

 EXEC_TIMINGS = [
-  # model, instant max, average max
-  ("modelV2", 0.05, 0.028),
-  ("driverStateV2", 0.05, 0.018),
+  # model, instant max, average max, chestnut average max
+  ("modelV2", 0.05, 0.03, 0.05),
+  ("driverStateV2", 0.05, 0.018, 0.018),
 ]

 def get_log_fn(test_route, ref="master"):
@@ -169,11 +169,13 @@ def model_replay(lr, frs):
  dmonitoringmodeld_msgs = replay_process(dmonitoringmodeld, dmodeld_logs, frs)

  msgs = modeld_msgs + dmonitoringmodeld_msgs
+  chestnut = any(m.modelV2.big for m in modeld_msgs if m.which() == "modelV2")

  header = ['model', 'max instant', 'max instant allowed', 'average', 'max average allowed', 'test result']
  rows = []
  timings_ok = True
-  for (s, instant_max, avg_max) in EXEC_TIMINGS:
+  for (s, instant_max, avg_max, chestnut_avg_max) in EXEC_TIMINGS:
+    avg_max = chestnut_avg_max if chestnut else avg_max
    ts = [getattr(m, s).modelExecutionTime for m in msgs if m.which() == s]
    # TODO some init can happen in first iteration
    ts = ts[1:]
@@ -1,7 +1,7 @@
 import time
 import pyray as rl

-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.selfdrive.ui.ui_state import ui_state
@@ -26,8 +26,8 @@ class BodyLayout(Widget):
    self._last_input_time = time.monotonic()
    self._was_active = False
    self._offroad_label = UnifiedLabel("turn on ignition to use", 95 if gui_app.big_ui() else 45, FontWeight.DISPLAY,
-                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                       alignment=TextAlignment.CENTER,
+                                       alignment_vertical=TextAlignmentVertical.MIDDLE)

  def draw_dot_grid(self, rect: rl.Rectangle, dots: list[tuple[int, int]], color: rl.Color):
    spacing = min(rect.height / GRID_ROWS, rect.width / GRID_COLS)
@@ -8,7 +8,7 @@ from openpilot.selfdrive.ui.widgets.exp_mode_button import ExperimentalModeButto
 from openpilot.selfdrive.ui.widgets.prime import PrimeWidget
 from openpilot.selfdrive.ui.widgets.setup import SetupWidget
 from openpilot.system.ui.lib.text_measure import measure_text_cached
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignment
 from openpilot.system.ui.lib.multilang import tr, trn
 from openpilot.system.ui.widgets.label import gui_label
 from openpilot.system.ui.widgets import Widget
@@ -178,7 +178,7 @@ class HomeLayout(Widget):

    version_rect = rl.Rectangle(self.header_rect.x + self.header_rect.width - version_text_width, self.header_rect.y,
                                version_text_width, self.header_rect.height)
-    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=TextAlignment.RIGHT)

  def _render_home_content(self):
    self._render_left_column()
@@ -5,7 +5,7 @@ from enum import IntEnum

 import pyray as rl
 from openpilot.common.basedir import BASEDIR
-from openpilot.system.ui.lib.application import FontWeight, gui_app
+from openpilot.system.ui.lib.application import FontWeight, TextAlignment, gui_app
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import Button, ButtonStyle
@@ -115,9 +115,9 @@ class TermsPage(Widget):
    self._on_accept = on_accept
    self._on_decline = on_decline

-    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=TextAlignment.LEFT)
    self._desc = Label(tr("You must accept the Terms of Service to use sunnypilot. Read the latest terms at https://sunnypilot.ai/terms before continuing."),
-                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT)

    self._decline_btn = Button(tr("Decline"), click_callback=on_decline)
    self._accept_btn = Button(tr("Agree"), button_style=ButtonStyle.PRIMARY, click_callback=on_accept)
@@ -150,7 +150,7 @@ class DeclinePage(Widget):
  def __init__(self, back_callback=None):
    super().__init__()
    self._text = Label(tr("You must accept the Terms of Service in order to use sunnypilot."),
-                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT)
    self._back_btn = Button(tr("Back"), click_callback=back_callback)
    self._uninstall_btn = Button(tr("Decline, uninstall sunnypilot"), button_style=ButtonStyle.DANGER,
                                 click_callback=self._on_uninstall_clicked)
@@ -199,6 +199,9 @@ class SoftwareLayout(Widget):
        selection = self._branch_dialog.selection
        ui_state.params.put("UpdaterTargetBranch", selection, block=True)
        self._branch_btn.action_item.set_value(selection)
+        self._download_btn.action_item.set_enabled(False)
+        self._waiting_for_updater = True
+        self._waiting_start_ts = time.monotonic()
        subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
      self._branch_dialog = None

@@ -1,4 +1,5 @@
 import datetime
+import math
 import time

 from openpilot.cereal import log
@@ -8,7 +9,7 @@ from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.layouts import HBoxLayout
 from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignment, TextAlignmentVertical
 from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.common.version import RELEASE_BRANCHES

@@ -69,8 +70,8 @@ class AlertsPill(Widget):

      count_rect = rl.Rectangle(self.rect.x + self.COUNT_OFFSET, self.rect.y, pill_w - self.COUNT_OFFSET, pill_h)
      gui_label(count_rect, str(alert_count), font_size=36,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                alignment=TextAlignment.CENTER,
+                alignment_vertical=TextAlignmentVertical.MIDDLE)


 class NetworkIcon(Widget):
@@ -139,7 +140,9 @@ class MiciHomeLayout(Widget):
    self._version_text = self._get_version_text()

    self._experimental_icon = IconWidget("icons_mici/experimental_mode.png", (48, 48))
+    self._usb_icon = IconWidget("icons_mici/usb.png", (62, 40))
    self._chestnut_icon = IconWidget("icons_mici/chestnut_green.png", (68, 40))
+    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
    self._chestnut_failed_icon = IconWidget("icons_mici/chestnut_orange.png", (68, 40))
    self._mic_icon = IconWidget("icons_mici/microphone.png", (32, 46))
    self._body_icon = IconWidget("icons_mici/body.png", (54, 37))
@@ -150,13 +153,15 @@ class MiciHomeLayout(Widget):
      IconWidget("icons_mici/settings.png", (48, 48), opacity=0.9),
      NetworkIcon(),
      self._experimental_icon,
+      self._usb_icon,
      self._chestnut_icon,
+      self._chestnut_loading_icon,
      self._chestnut_failed_icon,
      self._body_icon,
      self._mic_icon,
    ], spacing=18)

-    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
+    self._openpilot_label = UnifiedLabel("openpilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
    self._version_label = UnifiedLabel("", font_size=36, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
    self._large_version_label = UnifiedLabel("", font_size=64, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
    self._date_label = UnifiedLabel("", font_size=36, text_color=rl.GRAY, font_weight=FontWeight.ROMAN, max_width=480, wrap_text=False)
@@ -247,12 +252,20 @@ class MiciHomeLayout(Widget):
        self._version_commit_label.render()

    # ***** Center-aligned bottom section icons *****
+    usb_connected = ui_state.usb_connected
+    usb_unknown = ui_state.usb_unknown
+    chestnut_state = ui_state.chestnut_state
    self._experimental_icon.set_visible(ui_state.experimental_mode)
    if gui_app.sunnypilot_ui():
      self._set_chestnut_visibility()
    else:
-      self._chestnut_icon.set_visible(ui_state.chestnut_state in (ChestnutState.READY, ChestnutState.LOADING, ChestnutState.ACTIVE))
-      self._chestnut_failed_icon.set_visible(ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
+      self._usb_icon.set_visible(usb_connected and usb_unknown)
+      self._chestnut_icon.set_visible(not usb_unknown and chestnut_state not in
+                                      (ChestnutState.LOADING, ChestnutState.UNCOMPILED, ChestnutState.FAILED) and
+                                      (usb_connected or chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE)))
+      self._chestnut_loading_icon.set_visible(not usb_unknown and chestnut_state == ChestnutState.LOADING)
+      self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+      self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
    self._mic_icon.set_visible(ui_state.recording_audio)
    self._body_icon.set_visible(bool(ui_state.is_body))

@@ -1,8 +1,5 @@
-import os
-
 import pyray as rl
 import openpilot.cereal.messaging as messaging
-from openpilot.common.hardware import PC
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
 from openpilot.selfdrive.ui.mici.layouts.settings.settings import SettingsLayout
 from openpilot.selfdrive.ui.mici.layouts.offroad_alerts import MiciOffroadAlerts
@@ -64,8 +61,7 @@ class MiciMainLayout(Scroller):

    # Start onboarding if terms or training not completed, make sure to push after self
    self._onboarding_window = OnboardingWindow(lambda: gui_app.pop_widgets_to(self))
-    skip_onboarding_for_milestone_preview = PC and os.getenv("SP_MILESTONE_PREVIEW") == "1"
-    if not self._onboarding_window.completed and not skip_onboarding_for_milestone_preview:
+    if not self._onboarding_window.completed:
      gui_app.push_widget(self._onboarding_window)

    # initialize correct onroad layout
@@ -123,8 +119,6 @@ class MiciMainLayout(Scroller):
        self._onroad_time_delay = rl.get_time()
      else:
        self._scroll_to(self._home_layout)
-        if hasattr(self._home_layout, "request_drive_summary"):
-          self._home_layout.request_drive_summary()

    # FIXME: these two pops can interrupt user interacting in the settings
    if self._onroad_time_delay is not None and rl.get_time() - self._onroad_time_delay >= ONROAD_DELAY:
@@ -11,7 +11,7 @@ from openpilot.common.hardware import HARDWARE
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import Scroller
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr

 REFRESH_INTERVAL = 5.0  # seconds
@@ -62,12 +62,12 @@ class AlertItem(Widget):
    self._icon_green = gui_app.texture("icons_mici/offroad_alerts/green_wheel.png", self.ICON_SIZE, self.ICON_SIZE)

    self._title_label = UnifiedLabel(text="", font_size=32, font_weight=FontWeight.SEMI_BOLD, text_color=self.TEXT_COLOR,
-                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP, line_height=0.95)
+                                     alignment=TextAlignment.LEFT,
+                                     alignment_vertical=TextAlignmentVertical.TOP, line_height=0.95)

    self._body_label = UnifiedLabel(text="", font_size=28, font_weight=FontWeight.ROMAN, text_color=self.TEXT_COLOR,
-                                    alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-                                    alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, line_height=0.95)
+                                    alignment=TextAlignment.LEFT,
+                                    alignment_vertical=TextAlignmentVertical.BOTTOM, line_height=0.95)

    self._title_text = ""
    self._body_text = ""
@@ -200,8 +200,8 @@ class MiciOffroadAlerts(Scroller):

    # Create empty state label
    self._empty_label = UnifiedLabel(tr("no alerts"), 65, FontWeight.DISPLAY, rl.WHITE,
-                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                     alignment=TextAlignment.CENTER,
+                                     alignment_vertical=TextAlignmentVertical.MIDDLE)

    # Build initial alert list
    self._build_alerts()
@@ -4,7 +4,7 @@ import pyray as rl
 from collections.abc import Callable
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.qrcode import make_texture
-from openpilot.system.ui.lib.application import FontWeight, gui_app
+from openpilot.system.ui.lib.application import FontWeight, gui_app, TextAlignment
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import SmallCircleIconButton
 from openpilot.system.ui.widgets.scroller import NavScroller, Scroller
@@ -35,7 +35,7 @@ class DriverCameraSetupDialog(BaseCabinCameraDialog):

    if not self._camera_view.frame:
      gui_label(rect, tr("camera starting"), font_size=64, font_weight=FontWeight.BOLD,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
+                alignment=TextAlignment.CENTER)
      rl.end_scissor_mode()
      return

@@ -74,6 +74,10 @@ class SoftwareInfoLayoutMici(Widget):


 class CheckUpdateButton(BigButton):
+  UPDATER_PROC = "openpilot.system.updated.updated"
+  CHECK_FOR_UPDATE = "SIGUSR1"
+  DOWNLOAD_UPDATE = "SIGHUP"
+
  def __init__(self):
    self._txt_update_icon = gui_app.texture("icons_mici/settings/device/update.png", 64, 75)
    self._txt_up_to_date_icon = gui_app.texture("icons_mici/settings/device/up_to_date.png", 64, 64)
@@ -97,15 +101,20 @@ class CheckUpdateButton(BigButton):
      gui_app.push_widget(dlg)
      return

+    self._signal_updater(self.DOWNLOAD_UPDATE if self.get_value() == "download update" else self.CHECK_FOR_UPDATE)
+
+  def check_for_update(self):
+    self._signal_updater(self.CHECK_FOR_UPDATE)
+
+  def _signal_updater(self, sig: str):
    self.set_enabled(False)
    self._state = UpdaterState.WAITING_FOR_UPDATER
+    self._hide_value_t = None
+    self.set_value("")
    self.set_icon(self._txt_update_icon)

    def run():
-      if self.get_value() == "download update":
-        subprocess.run("pkill -SIGHUP -f openpilot.system.updated.updated", shell=True)
-      else:
-        subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
+      subprocess.run(f"pkill -{sig} -f {self.UPDATER_PROC}", shell=True)

    threading.Thread(target=run, daemon=True).start()

@@ -184,7 +193,7 @@ class CheckUpdateButton(BigButton):

 class InstallUpdateButton(BigButton):
  def __init__(self):
-    super().__init__("install update", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
+    super().__init__("install now", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
    self.set_visible(lambda: ui_state.is_offroad() and ui_state.params.get_bool("UpdateAvailable"))

  def _update_state(self):
@@ -232,8 +241,9 @@ class BranchSelectPage(NavScroller):


 class TargetBranchButton(BigButton):
-  def __init__(self):
+  def __init__(self, check_update_btn: CheckUpdateButton):
    super().__init__("target branch", ui_state.params.get("UpdaterTargetBranch") or "")
+    self._check_update_btn = check_update_btn
    self.set_click_callback(self._on_click)
    self.set_visible(not ui_state.params.get_bool("IsTestedBranch"))
    self.set_enabled(lambda: ui_state.is_offroad())
@@ -246,12 +256,15 @@ class TargetBranchButton(BigButton):
      self.set_value(target)

  def _on_click(self):
+    if not ui_state.params.get("UpdaterAvailableBranches"):
+      gui_app.push_widget(BigDialog("", tr("Failed to get available branches. Ensure you're connected to the internet and try again.")))
+      return
    gui_app.push_widget(BranchSelectPage(self._on_select))

  def _on_select(self, branch: str):
    ui_state.params.put("UpdaterTargetBranch", branch, block=True)
    self.set_value(branch)
-    subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
+    self._check_update_btn.check_for_update()


 class SoftwareLayoutMici(NavScroller):
@@ -265,10 +278,11 @@ class SoftwareLayoutMici(NavScroller):
                                                        gui_app.texture("icons_mici/settings/device/uninstall.png", 64, 64),
                                                        uninstall_openpilot_callback, exit_on_confirm=False)

+    check_update_btn = CheckUpdateButton()
    self._scroller.add_widgets([
      SoftwareInfoLayoutMici(),
-      CheckUpdateButton(),
+      check_update_btn,
      InstallUpdateButton(),
-      TargetBranchButton(),
+      TargetBranchButton(check_update_btn),
      uninstall_openpilot_btn,
    ])
@@ -47,7 +47,6 @@ class TogglesLayoutMici(NavScroller):
    is_metric_toggle = BigParamControl("use metric units", "IsMetric")
    ldw_toggle = BigParamControl("lane departure warnings", "IsLdwEnabled")
    always_on_dm_toggle = BigParamControl("always-on driver monitor", "AlwaysOnDM")
-    milestone_celebrations_toggle = BigParamControl("assisted driving milestones", "AssistedDrivingMilestonesEnabled")
    record_front = BigParamControl("record & upload cabin camera", "RecordFront", toggle_callback=restart_needed_callback)
    record_mic = BigParamControl("record & upload mic audio", "RecordAudio", toggle_callback=restart_needed_callback)
    enable_openpilot = BigParamControl("enable sunnypilot", "OpenpilotEnabledToggle", toggle_callback=restart_needed_callback)
@@ -58,7 +57,6 @@ class TogglesLayoutMici(NavScroller):
      is_metric_toggle,
      ldw_toggle,
      always_on_dm_toggle,
-      milestone_celebrations_toggle,
      record_front,
      record_mic,
      enable_openpilot,
@@ -70,7 +68,6 @@ class TogglesLayoutMici(NavScroller):
      ("IsMetric", is_metric_toggle),
      ("IsLdwEnabled", ldw_toggle),
      ("AlwaysOnDM", always_on_dm_toggle),
-      ("AssistedDrivingMilestonesEnabled", milestone_celebrations_toggle),
      ("RecordFront", record_front),
      ("RecordAudio", record_mic),
      ("OpenpilotEnabledToggle", enable_openpilot),
@@ -10,7 +10,7 @@ from opendbc.car.structs import car
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.common.filter_simple import BounceFilter, FirstOrderFilter
 from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel

@@ -20,7 +20,6 @@ AlertSize = log.SelfdriveState.AlertSize
 AlertStatus = log.SelfdriveState.AlertStatus

 ALERT_MARGIN = 18
-ALERT_BACKGROUND_OPACITY = 0.90

 ALERT_FONT_SMALL = 66 - 50
 ALERT_FONT_BIG = 88 - 40
@@ -280,7 +279,7 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
  def _draw_background(self, alert: Alert) -> None:
    # draw top gradient for alert text at top
    color = ALERT_COLORS.get(alert.status, ALERT_COLORS[AlertStatus.normal])
-    color = rl.Color(color.r, color.g, color.b, int(255 * ALERT_BACKGROUND_OPACITY * self._alpha_filter.x))
+    color = rl.Color(color.r, color.g, color.b, int(255 * 0.90 * self._alpha_filter.x))
    translucent_color = rl.Color(color.r, color.g, color.b, int(0 * self._alpha_filter.x))

    small_alert_height = round(self._rect.height * 0.583) # 140px at mici height
@@ -334,7 +333,7 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
    self._alert_text1_label.set_text(alert_text1)
    self._alert_text1_label.set_text_color(color)
    self._alert_text1_label.set_font_size(font_size)
-    self._alert_text1_label.set_alignment(rl.GuiTextAlignment.TEXT_ALIGN_LEFT if icon_side != 'left' else rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+    self._alert_text1_label.set_alignment(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
    self._alert_text1_label.render(text_rect1)

    alert_text2 = alert.text2.lower()
@@ -366,5 +365,5 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
      self._alert_text2_label.set_text(alert_text2)
      self._alert_text2_label.set_text_color(color)
      self._alert_text2_label.set_font_size(small_font_size)
-      self._alert_text2_label.set_alignment(rl.GuiTextAlignment.TEXT_ALIGN_LEFT if icon_side != 'left' else rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+      self._alert_text2_label.set_alignment(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
      self._alert_text2_label.render(text_rect2)
@@ -11,7 +11,7 @@ from openpilot.selfdrive.ui.mici.onroad.hud_renderer import HudRenderer
 from openpilot.selfdrive.ui.mici.onroad.model_renderer import ModelRenderer
 from openpilot.selfdrive.ui.mici.onroad.confidence_ball import ConfidenceBall
 from openpilot.selfdrive.ui.mici.onroad.cameraview import CameraView
-from openpilot.system.ui.lib.application import FontWeight, gui_app, MousePos, MouseEvent
+from openpilot.system.ui.lib.application import FontWeight, gui_app, MousePos, MouseEvent, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets import Widget
 from openpilot.common.filter_simple import BounceFilter
@@ -19,15 +19,10 @@ from openpilot.common.transformations.camera import DEVICE_CAMERAS, DeviceCamera
 from openpilot.common.transformations.orientation import rot_from_euler
 from enum import IntEnum

-MILESTONE_CELEBRATION_ENABLED = gui_app.sunnypilot_ui()
-
 if gui_app.sunnypilot_ui():
  from openpilot.selfdrive.ui.sunnypilot.mici.onroad.hud_renderer import HudRendererSP as HudRenderer
  from openpilot.selfdrive.ui.sunnypilot.ui_state import OnroadTimerStatus

-  if MILESTONE_CELEBRATION_ENABLED:
-    from openpilot.selfdrive.ui.sunnypilot.onroad.milestone_celebration import MilestoneCelebration
-
 OpState = log.SelfdriveState.OpenpilotState
 CALIBRATED = log.ExtrinsicsCalibration.Status.calibrated
 NARROW_ROAD_CAM = VisionStreamType.VISION_STREAM_NARROW_ROAD
@@ -161,11 +156,10 @@ class AugmentedRoadView(CameraView):
    self._alert_renderer = AlertRenderer()
    self._driver_state_renderer = DriverStateRenderer()
    self._confidence_ball = ConfidenceBall()
-    self._milestone_celebration = self._child(MilestoneCelebration()) if MILESTONE_CELEBRATION_ENABLED else None
    self._offroad_label = UnifiedLabel("start the car to\nuse sunnypilot", 54, FontWeight.DISPLAY,
                                       text_color=rl.Color(255, 255, 255, int(255 * 0.9)),
-                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+                                       alignment=TextAlignment.CENTER,
+                                       alignment_vertical=TextAlignmentVertical.MIDDLE)

    self._fade_texture = gui_app.texture("icons_mici/onroad/onroad_fade.png")

@@ -229,12 +223,6 @@ class AugmentedRoadView(CameraView):

    alert_to_render, not_animating_out = self._alert_renderer.will_render()

-    if self._milestone_celebration is not None:
-      if alert_to_render is not None:
-        self._milestone_celebration.cancel_for_alert()
-      else:
-        self._milestone_celebration.render(self._content_rect)
-
    # Hide DMoji when disengaged unless AlwaysOnDM is enabled
    should_draw_dmoji = (not self._hud_renderer.drawing_top_icons() and
                         (ui_state.status != UIStatus.DISENGAGED or ui_state.always_on_dm))
@@ -259,6 +247,7 @@ class AugmentedRoadView(CameraView):
    self._confidence_ball.render(self.rect)

    self._bookmark_icon.render(self.rect)
+
  def _switch_stream_if_needed(self, sm):
    if sm['selfdriveState'].experimentalMode and WIDE_CAM in self.available_streams:
      v_ego = sm['carState'].vEgo
@@ -366,12 +355,10 @@ class AugmentedRoadView(CameraView):
    return self._cached_matrix

  def show_event(self):
-    super().show_event()
    if gui_app.sunnypilot_ui():
      ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.RESUME)

  def hide_event(self):
-    super().hide_event()
    if gui_app.sunnypilot_ui():
      ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.PAUSE)

@@ -4,7 +4,7 @@ from openpilot.cereal.visionipc import VisionStreamType
 from openpilot.selfdrive.ui.mici.onroad.cameraview import CameraView
 from openpilot.selfdrive.ui.mici.onroad.driver_state import DriverStateRenderer
 from openpilot.selfdrive.ui.ui_state import ui_state, device
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.nav_widget import NavWidget
@@ -76,7 +76,7 @@ class BaseCabinCameraDialog(Widget):

    if not self._camera_view.frame:
      gui_label(rect, tr("camera starting"), font_size=54, font_weight=FontWeight.BOLD,
-                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
+                alignment=TextAlignment.CENTER)
      rl.end_scissor_mode()
      self._publish_alert_sound(None)
      return
@@ -124,12 +124,12 @@ class BaseCabinCameraDialog(Widget):
    awareness_pct = dm_state.visionPolicyState.awarenessPercent if is_vision else dm_state.wheeltouchPolicyState.awarenessPercent
    gui_label(rl.Rectangle(rect.x + 2, rect.y + 2, rect.width, rect.height),
              f"Awareness: {awareness_pct:.0f}%", font_size=44, font_weight=FontWeight.MEDIUM,
-              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+              alignment=TextAlignment.RIGHT,
+              alignment_vertical=TextAlignmentVertical.TOP,
              color=rl.Color(0, 0, 0, 180))
    gui_label(rect, f"Awareness: {awareness_pct:.0f}%", font_size=44, font_weight=FontWeight.MEDIUM,
-              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+              alignment=TextAlignment.RIGHT,
+              alignment_vertical=TextAlignmentVertical.TOP,
              color=rl.Color(255, 255, 255, int(255 * 0.9)))

    if dm_state.alertLevel == log.DriverMonitoringState.AlertLevel.none:
@@ -137,16 +137,16 @@ class BaseCabinCameraDialog(Widget):

    # Show alert level
    alert_level_str = f"{'Pay Attention' if is_vision else 'Touch Wheel'} - level {dm_state.alertLevel}"
-    alignment = rl.GuiTextAlignment.TEXT_ALIGN_RIGHT if self.driver_state_renderer.is_rhd else rl.GuiTextAlignment.TEXT_ALIGN_LEFT
+    alignment = TextAlignment.RIGHT if self.driver_state_renderer.is_rhd else TextAlignment.LEFT

    shadow_rect = rl.Rectangle(rect.x + 2, rect.y + 2, rect.width, rect.height)
    gui_label(shadow_rect, alert_level_str, font_size=40, font_weight=FontWeight.BOLD,
              alignment=alignment,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM,
+              alignment_vertical=TextAlignmentVertical.BOTTOM,
              color=rl.Color(0, 0, 0, 180))
    gui_label(rect, alert_level_str, font_size=40, font_weight=FontWeight.BOLD,
              alignment=alignment,
-              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM,
+              alignment_vertical=TextAlignmentVertical.BOTTOM,
              color=rl.Color(255, 255, 255, int(255 * 0.9)))

  def _load_eye_textures(self):
@@ -6,7 +6,7 @@ from collections.abc import Callable
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.scroller import DO_ZOOM
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos, TextAlignmentVertical
 from openpilot.common.filter_simple import BounceFilter

 if TYPE_CHECKING:
@@ -125,10 +125,10 @@ class BigButton(Widget):
    self._rotate_icon_t: float | None = None

    self._label = UnifiedLabel(text, font_size=self._get_label_font_size(), font_weight=FontWeight.BOLD,
-                               text_color=LABEL_COLOR, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM, scroll=scroll,
+                               text_color=LABEL_COLOR, alignment_vertical=TextAlignmentVertical.BOTTOM, scroll=scroll,
                               line_height=0.9)
    self._sub_label = UnifiedLabel(value, font_size=COMPLICATION_SIZE, font_weight=FontWeight.ROMAN,
-                                   text_color=COMPLICATION_GREY, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+                                   text_color=COMPLICATION_GREY, alignment_vertical=TextAlignmentVertical.BOTTOM)
    self._update_label_layout()

    self._load_images()
@@ -167,9 +167,9 @@ class BigButton(Widget):
  def _update_label_layout(self):
    self._label.set_font_size(self._get_label_font_size())
    if self.value:
-      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
+      self._label.set_alignment_vertical(TextAlignmentVertical.TOP)
    else:
-      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+      self._label.set_alignment_vertical(TextAlignmentVertical.BOTTOM)

  def set_text(self, text: str):
    self.text = text
@@ -356,8 +356,8 @@ class GreyBigButton(BigButton):
    self._sub_label.set_font_size(36)
    self._sub_label.set_text_color(rl.Color(255, 255, 255, int(255 * 0.9)))
    self._sub_label.set_font_weight(FontWeight.DISPLAY_REGULAR)
-    self._sub_label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE if not self._label.text else
-                                           rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM)
+    self._sub_label.set_alignment_vertical(TextAlignmentVertical.MIDDLE if not self._label.text else
+                                           TextAlignmentVertical.BOTTOM)
    self._sub_label.set_line_height(0.95)

  @property
@@ -4,7 +4,7 @@ from dataclasses import dataclass
 from openpilot.cereal import messaging, log
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.common.hardware import COMMA_HARDWARE
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 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
@@ -76,10 +76,10 @@ class AlertRenderer(Widget):
    self.font_bold: rl.Font = gui_app.font(FontWeight.BOLD)

    # font size is set dynamically
-    self._full_text1_label = Label("", font_size=0, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                   text_alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
-    self._full_text2_label = Label("", font_size=ALERT_FONT_BIG, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-                                   text_alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
+    self._full_text1_label = Label("", font_size=0, font_weight=FontWeight.BOLD, text_alignment=TextAlignment.CENTER,
+                                   text_alignment_vertical=TextAlignmentVertical.TOP)
+    self._full_text2_label = Label("", font_size=ALERT_FONT_BIG, text_alignment=TextAlignment.CENTER,
+                                   text_alignment_vertical=TextAlignmentVertical.TOP)

  def get_alert(self, sm: messaging.SubMaster) -> Alert | None:
    """Generate the current alert based on selfdrive state."""
@@ -4,7 +4,7 @@ from openpilot.cereal.visionipc import VisionStreamType
 from openpilot.selfdrive.ui.onroad.cameraview import CameraView
 from openpilot.selfdrive.ui.onroad.driver_state import DriverStateRenderer
 from openpilot.selfdrive.ui.ui_state import ui_state, device
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets.label import gui_label

@@ -38,7 +38,7 @@ class CabinCameraDialog(CameraView):
        tr("camera starting"),
        font_size=100,
        font_weight=FontWeight.BOLD,
-        alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+        alignment=TextAlignment.CENTER,
      )
      return -1

@@ -24,8 +24,14 @@ ALERT_RAMP_TIME = 4 # seconds to ramp to max volume for warningImmediate
 SELFDRIVE_STATE_TIMEOUT = 5 # 5 seconds
 FILTER_DT = 1. / (micd.SAMPLE_RATE / micd.FFT_SAMPLES)

+AMBIENT_DB = 26 # DB where MIN_VOLUME is applied
 DB_SCALE = 30 # AMBIENT_DB + DB_SCALE is where MAX_VOLUME is applied

+VOLUME_BASE = 20
+if HARDWARE.get_device_type() == "tizi":
+  AMBIENT_DB = 30
+  VOLUME_BASE = 10
+
 AudibleAlert = log.SelfdriveState.AudibleAlert
 AudibleAlertSP = custom.SelfdriveStateSP.AudibleAlert

@@ -47,7 +53,6 @@ sound_list: dict[int, tuple[str, int | None, float]] = {
  AudibleAlert.promptDistracted: ("dm_warning.wav", None, MAX_VOLUME),

  AudibleAlert.preAlert: ("pre_alert.wav", 1, MAX_VOLUME),
-  AudibleAlert.complete: ("milestone.wav", 1, MAX_VOLUME),

  AudibleAlert.warningSoft: ("critical.wav", None, MAX_VOLUME),
  AudibleAlert.warningImmediate: ("dm_critical.wav", None, MAX_VOLUME),
@@ -55,14 +60,6 @@ sound_list: dict[int, tuple[str, int | None, float]] = {
  **sound_list_sp,
 }

-
-def calculate_volume_for_device(weighted_db: float, device_type: str) -> float:
-  ambient_db = 30 if device_type in ("mici", "tizi") else 26
-  volume_base = 10 if device_type in ("mici", "tizi") else 20
-  volume_boost = 1.5 if device_type == "mici" else 1.0
-  volume = ((weighted_db - ambient_db) / DB_SCALE) * (MAX_VOLUME - MIN_VOLUME) + MIN_VOLUME
-  return min(MAX_VOLUME, volume_boost * math.pow(volume_base, (np.clip(volume, MIN_VOLUME, MAX_VOLUME) - 1)))
-
 def check_selfdrive_timeout_alert(sm):
  ss_missing = time.monotonic() - sm.recv_time['selfdriveState']

@@ -77,7 +74,6 @@ class Soundd(QuietMode):
  def __init__(self):
    super().__init__()

-    self.device_type = HARDWARE.get_device_type()
    self.load_sounds()

    self.current_alert = AudibleAlert.none
@@ -89,7 +85,6 @@ class Soundd(QuietMode):

    self.selfdrive_timeout_alert = False
    self.pending_stop = False
-    self.last_milestone_event_id = 0

    self.spl_filter_weighted = FirstOrderFilter(0, 2.5, FILTER_DT, initialized=False)

@@ -169,19 +164,9 @@ class Soundd(QuietMode):
      self.update_alert(AudibleAlert.none)
      self.selfdrive_timeout_alert = False

-  def update_milestone_alert(self, sm):
-    if not sm.updated['assistedDrivingMilestoneState']:
-      return
-    milestone_state = sm['assistedDrivingMilestoneState']
-    event_id = milestone_state.event.id
-    if not milestone_state.enabled or event_id == 0 or event_id == self.last_milestone_event_id:
-      return
-    self.last_milestone_event_id = event_id
-    if self.current_alert == AudibleAlert.none and not self.enabled:
-      self.update_alert(AudibleAlert.complete)
-
  def calculate_volume(self, weighted_db):
-    return calculate_volume_for_device(weighted_db, self.device_type)
+    volume = ((weighted_db - AMBIENT_DB) / DB_SCALE) * (MAX_VOLUME - MIN_VOLUME) + MIN_VOLUME
+    return math.pow(VOLUME_BASE, (np.clip(volume, MIN_VOLUME, MAX_VOLUME) - 1))

  @retry(attempts=10, delay=3)
  def get_stream(self, sd):
@@ -195,7 +180,7 @@ class Soundd(QuietMode):
    import sounddevice as sd
    micd.patch_sounddevice(sd)

-    sm = messaging.SubMaster(['selfdriveState', 'selfdriveStateSP', 'soundPressure', 'assistedDrivingMilestoneState'])
+    sm = messaging.SubMaster(['selfdriveState', 'selfdriveStateSP', 'soundPressure'])

    with self.get_stream(sd) as stream:
      rk = Ratekeeper(20)
@@ -213,7 +198,6 @@ class Soundd(QuietMode):
            self.current_volume = self.calculate_volume(float(self.spl_filter_weighted.x))

        self.get_audible_alert(sm)
-        self.update_milestone_alert(sm)

        # Ramp up immediate warning sound over 4s
        if self.current_alert == AudibleAlert.warningImmediate:
@@ -6,7 +6,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 import pyray as rl
 from openpilot.selfdrive.ui.layouts.home import HomeLayout, HomeLayoutState, HEAD_BUTTON_FONT_SIZE, SPACING
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment
 from openpilot.system.ui.lib.text_measure import measure_text_cached
 from openpilot.system.ui.lib.multilang import tr, trn
 from openpilot.system.ui.widgets.label import gui_label
@@ -59,7 +59,7 @@ class HomeLayoutSP(HomeLayout):
      desc_size = measure_text_cached(gui_app.font(FontWeight.NORMAL), description, BRAND_FONT_SIZE)
      desc_width = desc_size.x
      desc_rect = rl.Rectangle(version_right - desc_width, self.header_rect.y, desc_width, self.header_rect.height)
-      gui_label(desc_rect, description, BRAND_FONT_SIZE, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
+      gui_label(desc_rect, description, BRAND_FONT_SIZE, rl.WHITE, alignment=TextAlignment.RIGHT)

    brand_size = measure_text_cached(gui_app.font(FontWeight.AUDIOWIDE), brand, BRAND_FONT_SIZE)
    spacing = BRAND_DESC_SPACING if description else 0
@@ -6,7 +6,7 @@ See the LICENSE.md file in the root directory for more details.
 """
 import pyray as rl
 from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import FontWeight
+from openpilot.system.ui.lib.application import FontWeight, TextAlignment
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.button import Button, ButtonStyle
@@ -20,7 +20,7 @@ class SunnylinkConsentPage(Widget):
    self._done_callback = done_callback
    self._step = 0

-    self._title = self._child(Label(tr("sunnylink"), font_size=90, font_weight=FontWeight.AUDIOWIDE, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT))
+    self._title = self._child(Label(tr("sunnylink"), font_size=90, font_weight=FontWeight.AUDIOWIDE, text_alignment=TextAlignment.LEFT))

    self._content = [
      {
@@ -43,7 +43,7 @@ class SunnylinkConsentPage(Widget):
    self._primary_btn = self._child(Button("", button_style=ButtonStyle.PRIMARY, click_callback=lambda: self._handle_choice("enable")))
    self._secondary_btn = self._child(Button("", button_style=ButtonStyle.NORMAL, click_callback=lambda: self._handle_choice("secondary")))
    self._danger_btn = self._child(Button("", button_style=ButtonStyle.DANGER, click_callback=lambda: self._handle_choice("disable")))
-    self._desc = self._child(Label("", font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT))
+    self._desc = self._child(Label("", font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=TextAlignment.LEFT))

  def _handle_choice(self, choice):
    if choice == "enable":
@@ -9,7 +9,7 @@ from openpilot.cereal import custom
 from openpilot.selfdrive.ui.sunnypilot.layouts.onboarding import SunnylinkConsentPage
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
 from openpilot.system.ui.lib.multilang import tr
 from openpilot.system.ui.sunnypilot.widgets.list_view import button_item_sp
 from openpilot.system.ui.sunnypilot.widgets.list_view import toggle_item_sp
@@ -32,8 +32,8 @@ class SunnylinkHeader(Widget):
      font_size=90,
      font_weight=FontWeight.AUDIOWIDE,
      text_color=rl.WHITE,
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
      wrap_text=False,
      elide=False
    )
@@ -43,8 +43,8 @@ class SunnylinkHeader(Widget):
      font_size=40,
      font_weight=FontWeight.NORMAL,
      text_color=rl.Color(0, 255, 0, 255),  # Green
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
      wrap_text=True,
      elide=False
    )
@@ -55,8 +55,8 @@ class SunnylinkHeader(Widget):
      font_size=35,
      font_weight=FontWeight.NORMAL,
      text_color=rl.Color(255, 165, 0, 255),  # Orange
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.CENTER,
+      alignment_vertical=TextAlignmentVertical.TOP,
      wrap_text=True,
      elide=False
    )
@@ -109,8 +109,8 @@ class SunnylinkDescriptionItem(Widget):
      font_size=40,
      font_weight=FontWeight.NORMAL,
      text_color=rl.WHITE,
-      alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
-      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
+      alignment=TextAlignment.LEFT,
+      alignment_vertical=TextAlignmentVertical.TOP,
      wrap_text=True,
      elide=False,
    )
@@ -5,90 +5,29 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 import math
-import time

 import pyray as rl

 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
 from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.system.ui.lib.application import FontWeight
-from openpilot.system.ui.lib.multilang import tr
-from openpilot.system.ui.widgets.icon_widget import IconWidget
-from openpilot.system.ui.widgets.label import UnifiedLabel, gui_label
-
-METERS_PER_MILE = 1609.344
-METERS_PER_KILOMETER = 1000.0
-SUMMARY_DURATION_SECONDS = 10.0
-SUMMARY_WAIT_SECONDS = 3.0
-
-
-def _nonnegative_float(value) -> float:
-  try:
-    return max(0.0, float(value))
-  except (TypeError, ValueError):
-    return 0.0
+from openpilot.system.ui.widgets.label import UnifiedLabel


 class MiciHomeLayoutSP(MiciHomeLayout):
  def __init__(self):
    super().__init__()
    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
-    self._chestnut_loading_icon = IconWidget("icons_mici/chestnut.png", (68, 40))
-    self._chestnut_loading_icon.set_visible(False)
-    failed_idx = self._status_bar_layout.widgets.index(self._chestnut_failed_icon)
-    self._status_bar_layout.widgets.insert(failed_idx + 1, self._chestnut_loading_icon)
-    initial_summary = ui_state.params.get("LastDriveAssistedDrivingSummary", return_default=True) or {}
-    self._last_summary_id = initial_summary.get("id", 0)
-    self._summary_wait_until = 0.0
-    self._summary_visible_until = 0.0
-    self._drive_summary = {}
-
-  def request_drive_summary(self) -> None:
-    self._summary_wait_until = time.monotonic() + SUMMARY_WAIT_SECONDS
-
-  def _render(self, _: rl.Rectangle) -> None:
-    super()._render(_)
-    now = time.monotonic()
-    if now < self._summary_wait_until:
-      summary = ui_state.params.get("LastDriveAssistedDrivingSummary", return_default=True) or {}
-      summary_id = summary.get("id", 0)
-      if summary_id and summary_id != self._last_summary_id:
-        self._last_summary_id = summary_id
-        distances = summary.get("distancesMeters", {})
-        enabled = ui_state.params.get_bool("AssistedDrivingMilestonesEnabled")
-        if enabled and any(_nonnegative_float(distances.get(category, 0.0)) > 0.0 for category in ("mads", "fullAssist")):
-          self._drive_summary = summary
-          self._summary_visible_until = now + SUMMARY_DURATION_SECONDS
-        self._summary_wait_until = 0.0
-
-    if now < self._summary_visible_until:
-      self._draw_drive_summary(_)
-
-  def _draw_drive_summary(self, rect: rl.Rectangle) -> None:
-    distances = self._drive_summary.get("distancesMeters", {})
-    metric = self._drive_summary.get("unit") == "metric"
-    meters_per_unit = METERS_PER_KILOMETER if metric else METERS_PER_MILE
-    unit = "KM" if metric else "MI"
-    mads = _nonnegative_float(distances.get("mads", 0.0)) / meters_per_unit
-    full_assist = _nonnegative_float(distances.get("fullAssist", 0.0)) / meters_per_unit
-
-    rl.draw_rectangle_rec(rect, rl.Color(0, 0, 0, 235))
-    gui_label(rl.Rectangle(rect.x, rect.y + 14, rect.width, 52), tr("DRIVE COMPLETE"), 42,
-              font_weight=FontWeight.SEMI_BOLD, alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
-    gui_label(rl.Rectangle(rect.x + 20, rect.y + 78, rect.width / 2 - 30, 42), tr("MADS"), 28,
-              color=rl.Color(255, 255, 255, 184), alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
-    gui_label(rl.Rectangle(rect.x + rect.width / 2 + 10, rect.y + 78, rect.width / 2 - 30, 42), tr("FULL ASSIST"), 28,
-              color=rl.Color(255, 255, 255, 184), alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
-    gui_label(rl.Rectangle(rect.x + 20, rect.y + 116, rect.width / 2 - 30, 72), f"{mads:.1f} {unit}", 48,
-              font_weight=FontWeight.DISPLAY, alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
-    gui_label(rl.Rectangle(rect.x + rect.width / 2 + 10, rect.y + 116, rect.width / 2 - 30, 72), f"{full_assist:.1f} {unit}", 48,
-              font_weight=FontWeight.DISPLAY, alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)

  def _set_chestnut_visibility(self):
-    # stock has no loading tier: it shows green from the moment a big model is available. keep the
-    # pulse so the status bar and the onroad HUD agree on what loading looks like.
-    loading = ui_state.chestnut_state == ChestnutState.LOADING
-    self._chestnut_loading_icon._opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
-    self._chestnut_loading_icon.set_visible(loading)
-    self._chestnut_icon.set_visible(not loading and ui_state.chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE))
-    self._chestnut_failed_icon.set_visible(ui_state.chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
+    usb_connected = ui_state.usb_connected
+    usb_unknown = ui_state.usb_unknown
+    chestnut_state = ui_state.chestnut_state
+    loading = chestnut_state == ChestnutState.LOADING
+
+    self._usb_icon.set_visible(usb_connected and usb_unknown)
+    self._chestnut_loading_icon.set_opacity(0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0)))
+    self._chestnut_loading_icon.set_visible(not usb_unknown and loading)
+    self._chestnut_icon.set_visible(not usb_unknown and not loading and
+                                    chestnut_state in (ChestnutState.READY, ChestnutState.ACTIVE))
+    self._chestnut_failed_icon.set_visible(not usb_unknown and chestnut_state in (ChestnutState.UNCOMPILED, ChestnutState.FAILED))
@@ -1,228 +0,0 @@
-"""Render assisted-driving milestone celebrations over the on-road view."""
-
-import math
-import random
-import time
-from collections import deque
-from dataclasses import dataclass
-
-import pyray as rl
-
-from openpilot.cereal import custom
-from openpilot.selfdrive.ui.mici.onroad.alert_renderer import ALERT_BACKGROUND_OPACITY
-from openpilot.selfdrive.ui.mici.onroad.hud_renderer import FONT_SIZES
-from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import FontWeight, gui_app
-from openpilot.system.ui.lib.multilang import tr
-from openpilot.system.ui.lib.text_measure import measure_text_cached
-from openpilot.system.ui.widgets import Widget
-
-
-CELEBRATION_DURATION = 4.5
-PARTICLE_COUNT = 150
-METERS_PER_MILE = 1609.344
-METERS_PER_KILOMETER = 1000.0
-
-CONFETTI_COLORS = (
-  rl.Color(255, 55, 95, 255),
-  rl.Color(255, 183, 3, 255),
-  rl.Color(48, 209, 88, 255),
-  rl.Color(36, 179, 255, 255),
-  rl.Color(112, 72, 232, 255),
-  rl.Color(255, 45, 196, 255),
-)
-
-
-@dataclass(frozen=True)
-class ConfettiParticle:
-  x: float
-  y: float
-  width: float
-  height: float
-  speed: float
-  drift: float
-  angle: float
-  spin: float
-  phase: float
-  color: rl.Color
-
-
-@dataclass(frozen=True)
-class CelebrationMilestone:
-  event_id: int
-  full_assist: bool
-  distance_meters: float
-  previous_distance_meters: float
-  metric: bool
-
-
-class MilestoneCelebration(Widget):
-  """Pure renderer for typed assisted-driving milestone events."""
-
-  def __init__(self):
-    super().__init__()
-    self._drive_started_time = -1.0
-    self._celebration_started_time: float | None = None
-    self._current_milestone: CelebrationMilestone | None = None
-    self._pending_milestones: deque[CelebrationMilestone] = deque()
-    self._last_event_id = 0
-    self._particles = self._make_particles()
-
-  @staticmethod
-  def _make_particles() -> list[ConfettiParticle]:
-    rng = random.Random(20260828)
-    return [
-      ConfettiParticle(
-        x=rng.random(),
-        y=rng.uniform(-0.25, 0.95),
-        width=rng.uniform(10, 24),
-        height=rng.uniform(24, 58),
-        speed=rng.uniform(0.12, 0.34),
-        drift=rng.uniform(-0.035, 0.035),
-        angle=rng.uniform(0, 360),
-        spin=rng.uniform(-150, 150),
-        phase=rng.uniform(0, math.tau),
-        color=CONFETTI_COLORS[rng.randrange(len(CONFETTI_COLORS))],
-      )
-      for _ in range(PARTICLE_COUNT)
-    ]
-
-  def _render(self, rect: rl.Rectangle, /) -> None:
-    now = time.monotonic()
-    if ui_state.started_time != self._drive_started_time:
-      self._drive_started_time = ui_state.started_time
-      self._celebration_started_time = None
-      self._current_milestone = None
-      self._pending_milestones.clear()
-
-    self._consume_event(suppress=False)
-
-    if self._current_milestone is None and self._pending_milestones:
-      self._current_milestone = self._pending_milestones.popleft()
-      self._celebration_started_time = now
-
-    if self._celebration_started_time is None or self._current_milestone is None:
-      return
-
-    elapsed = now - self._celebration_started_time
-    if elapsed >= CELEBRATION_DURATION:
-      self._celebration_started_time = None
-      self._current_milestone = None
-      return
-
-    alpha = min(1.0, elapsed / 0.2, (CELEBRATION_DURATION - elapsed) / 0.8)
-    self._draw_background_scrim(rect, alpha)
-    self._draw_confetti(rect, elapsed, alpha)
-    self._draw_milestone(rect, elapsed, alpha, self._current_milestone)
-
-  def cancel_for_alert(self) -> None:
-    self._consume_event(suppress=True)
-    self._celebration_started_time = None
-    self._current_milestone = None
-    self._pending_milestones.clear()
-
-  def _consume_event(self, suppress: bool) -> None:
-    if not ui_state.sm.updated["assistedDrivingMilestoneState"]:
-      return
-    state = ui_state.sm["assistedDrivingMilestoneState"]
-    event = state.event
-    if not state.enabled:
-      self._celebration_started_time = None
-      self._current_milestone = None
-      self._pending_milestones.clear()
-      return
-    if event.id == 0 or event.id == self._last_event_id:
-      return
-    self._last_event_id = event.id
-    if suppress:
-      return
-    self._pending_milestones.append(CelebrationMilestone(
-      event_id=event.id,
-      full_assist=event.category == custom.AssistedDrivingMilestoneState.Category.fullAssist,
-      distance_meters=event.distanceMeters,
-      previous_distance_meters=event.previousDistanceMeters,
-      metric=event.unit == custom.AssistedDrivingMilestoneState.Unit.metric,
-    ))
-
-  def _draw_confetti(self, rect: rl.Rectangle, elapsed: float, alpha: float) -> None:
-    travel_height = rect.height * 1.45
-    compact = rect.height <= 300
-    particle_scale = rect.height / 1080.0
-    particles = self._particles[:100] if compact else self._particles
-    for particle in particles:
-      x = rect.x + rect.width * (particle.x + particle.drift * elapsed + 0.012 * math.sin(elapsed * 3 + particle.phase))
-      y = rect.y - rect.height * 0.2 + (particle.y * travel_height + particle.speed * rect.height * elapsed) % travel_height
-      flip = 0.2 + 0.8 * abs(math.sin(elapsed * 5 + particle.phase))
-      particle_rect = rl.Rectangle(x, y, particle.width * particle_scale * flip, particle.height * particle_scale)
-      origin = rl.Vector2(particle_rect.width / 2, particle_rect.height / 2)
-      color = rl.Color(particle.color.r, particle.color.g, particle.color.b, int(255 * alpha))
-      rl.draw_rectangle_pro(particle_rect, origin, particle.angle + particle.spin * elapsed, color)
-
-  @staticmethod
-  def _draw_milestone(rect: rl.Rectangle, elapsed: float, alpha: float, milestone: CelebrationMilestone) -> None:
-    # Match the comma four set-speed hierarchy: DISPLAY number with a MAX-sized label.
-    scale = rect.height / 240.0
-    pulse = 1.0 + 0.025 * math.sin(min(elapsed, 0.6) / 0.6 * math.pi)
-    number_size = int(FONT_SIZES.set_speed * scale * pulse)
-    milestone_size = int(FONT_SIZES.max_speed * scale * pulse)
-    category_size = int(22 * scale * pulse)
-    unit_size = category_size
-
-    display_font = gui_app.font(FontWeight.DISPLAY)
-    semibold_font = gui_app.font(FontWeight.SEMI_BOLD)
-    tween_progress = min(elapsed / 0.85, 1.0)
-    tween_progress = 1.0 - (1.0 - tween_progress) ** 3
-    meters_per_unit = METERS_PER_KILOMETER if milestone.metric else METERS_PER_MILE
-    previous_distance = milestone.previous_distance_meters / meters_per_unit
-    milestone_distance = milestone.distance_meters / meters_per_unit
-    displayed_distance = previous_distance + (milestone_distance - previous_distance) * tween_progress
-    if tween_progress >= 1.0:
-      number = f"{round(milestone_distance):,}"
-    else:
-      number = f"{displayed_distance:,.1f}"
-    unit = tr("KM") if milestone.metric else tr("MI")
-    category = tr("FULL ASSIST") if milestone.full_assist else tr("MADS")
-    milestone_label = tr("MILESTONE")
-
-    unit_bounds = measure_text_cached(semibold_font, unit, unit_size)
-    number_bounds = measure_text_cached(display_font, number, number_size)
-    max_number_width = rect.width * 0.72 - unit_bounds.x - 8 * scale
-    if number_bounds.x > max_number_width:
-      number_size = max(1, int(number_size * max_number_width / number_bounds.x))
-      number_bounds = measure_text_cached(display_font, number, number_size)
-    category_bounds = measure_text_cached(semibold_font, category, category_size)
-    milestone_bounds = measure_text_cached(semibold_font, milestone_label, milestone_size)
-
-    center_x = rect.x + rect.width / 2
-    center_y = rect.y + rect.height / 2
-    text_color = rl.Color(255, 255, 255, int(255 * 0.9 * alpha))
-    secondary_color = rl.Color(255, 255, 255, int(255 * 0.72 * alpha))
-    number_line_width = number_bounds.x + 8 * scale + unit_bounds.x
-    number_x = center_x - number_line_width / 2
-    number_y = center_y - 76 * scale
-    unit_y = center_y + 14 * scale
-    category_y = center_y - 91 * scale
-    milestone_y = center_y + 50 * scale
-
-    rl.draw_text_ex(semibold_font, category, rl.Vector2(center_x - category_bounds.x / 2, category_y),
-                    category_size, 0, secondary_color)
-    rl.draw_text_ex(display_font, number, rl.Vector2(number_x, number_y), number_size, 0, text_color)
-    rl.draw_text_ex(semibold_font, unit, rl.Vector2(number_x + number_bounds.x + 8 * scale, unit_y),
-                    unit_size, 0, secondary_color)
-    rl.draw_text_ex(semibold_font, milestone_label, rl.Vector2(center_x - milestone_bounds.x / 2, milestone_y),
-                    milestone_size, 0, text_color)
-
-  @staticmethod
-  def _draw_background_scrim(rect: rl.Rectangle, alpha: float) -> None:
-    # Match the alert background: a mostly opaque black core fading to transparent.
-    fade_height = round(rect.height * 0.25)
-    solid_height = round(rect.height * 0.50)
-    solid_color = rl.Color(0, 0, 0, int(255 * ALERT_BACKGROUND_OPACITY * alpha))
-    transparent = rl.Color(0, 0, 0, 0)
-    x = int(rect.x)
-    y = int(rect.y)
-    width = int(rect.width)
-
-    rl.draw_rectangle_gradient_v(x, y, width, fade_height, transparent, solid_color)
-    rl.draw_rectangle(x, y + fade_height, width, solid_height, solid_color)
-    rl.draw_rectangle_gradient_v(x, y + fade_height + solid_height, width, fade_height, solid_color, transparent)
@@ -35,8 +35,7 @@ class UIStateSP:
    self.is_sp_release: bool = self.params.get_bool("IsReleaseSpBranch")
    self.sm_services_ext = [
      "modelManagerSP", "selfdriveStateSP", "longitudinalPlanSP", "backupManagerSP",
-      "gpsLocation", "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay",
-      "assistedDrivingMilestoneState",
+      "gpsLocation", "lateralTorqueParameters", "carStateSP", "liveMapDataSP", "carParamsSP", "lateralDelay"
    ]

    self.sunnylink_state = SunnylinkState()
@@ -1,45 +0,0 @@
-#!/usr/bin/env python3
-"""Generate the assisted-driving milestone celebration chime."""
-
-import math
-import wave
-from array import array
-from pathlib import Path
-
-
-SAMPLE_RATE = 48_000
-DURATION_SECONDS = 0.82
-NOTES = (
-  (0.00, 523.25),
-  (0.11, 659.25),
-  (0.22, 783.99),
-)
-
-
-def note_sample(age: float, frequency: float) -> float:
-  if not 0 <= age <= 0.58:
-    return 0.0
-  attack = min(age / 0.008, 1.0)
-  release = min((0.58 - age) / 0.15, 1.0)
-  envelope = attack * release * math.exp(-3.8 * age)
-  tone = math.sin(math.tau * frequency * age) + 0.16 * math.sin(math.tau * frequency * 2 * age)
-  return envelope * tone
-
-
-def main() -> None:
-  output = Path(__file__).parents[4] / "openpilot/selfdrive/assets/sounds/milestone.wav"
-  samples = array('h')
-  for frame in range(round(SAMPLE_RATE * DURATION_SECONDS)):
-    t = frame / SAMPLE_RATE
-    value = 0.38 * sum(note_sample(t - start, frequency) for start, frequency in NOTES)
-    samples.append(round(max(-1.0, min(1.0, value)) * 32767))
-
-  with wave.open(str(output), "wb") as wav:
-    wav.setnchannels(1)
-    wav.setsampwidth(2)
-    wav.setframerate(SAMPLE_RATE)
-    wav.writeframes(samples.tobytes())
-
-
-if __name__ == "__main__":
-  main()
@@ -1,38 +0,0 @@
-#!/usr/bin/env python3
-"""Publish deterministic milestone events for the local comma-four UI preview."""
-
-import itertools
-import time
-
-from openpilot.cereal import messaging
-
-
-def main() -> None:
-  pm = messaging.PubMaster(["assistedDrivingMilestoneState"])
-  milestones = itertools.cycle(((1, 0, "mads"), (2, 1, "fullAssist"), (5, 2, "mads"), (10, 5, "fullAssist")))
-  event_id = 0
-  milestone, previous_milestone, category = 0, 0, "mads"
-  next_event_time = time.monotonic() + 1.0
-
-  while True:
-    now = time.monotonic()
-    if now >= next_event_time:
-      event_id += 1
-      milestone, previous_milestone, category = next(milestones)
-      next_event_time = now + 6.0
-
-    msg = messaging.new_message("assistedDrivingMilestoneState")
-    state = msg.assistedDrivingMilestoneState
-    state.enabled = True
-    if event_id:
-      state.event.id = event_id
-      state.event.category = category
-      state.event.distanceMeters = milestone * 1609.344
-      state.event.previousDistanceMeters = previous_milestone * 1609.344
-      state.event.unit = "imperial"
-    pm.send("assistedDrivingMilestoneState", msg)
-    time.sleep(0.1)
-
-
-if __name__ == "__main__":
-  main()
@@ -1,27 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-repo_root="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../../.." && pwd)"
-replay_pid=""
-preview_pid=""
-
-cleanup() {
-  for pid in "$preview_pid" "$replay_pid"; do
-    if [[ -n "$pid" ]]; then
-      kill "$pid" 2>/dev/null || true
-      wait "$pid" 2>/dev/null || true
-    fi
-  done
-}
-trap cleanup EXIT INT TERM
-
-export PATH="$repo_root/.venv/bin:$PATH"
-export SP_MILESTONE_PREVIEW=1
-playback="${SP_MILESTONE_PLAYBACK:-1}"
-
-"$repo_root/openpilot/tools/replay/replay" --demo --playback "$playback" &
-replay_pid=$!
-"$repo_root/.venv/bin/python" "$repo_root/openpilot/selfdrive/ui/tests/milestone_preview.py" &
-preview_pid=$!
-
-"$repo_root/.venv/bin/python" "$repo_root/openpilot/selfdrive/ui/mici/onroad/augmented_road_view.py"
@@ -4,63 +4,12 @@ import time
 from openpilot.common.test import OpenpilotTestCase
 from openpilot.cereal import log, messaging
 from openpilot.cereal.messaging import SubMaster, PubMaster
-from openpilot.selfdrive.ui.soundd import SELFDRIVE_STATE_TIMEOUT, Soundd, calculate_volume_for_device, check_selfdrive_timeout_alert
+from openpilot.selfdrive.ui.soundd import SELFDRIVE_STATE_TIMEOUT, check_selfdrive_timeout_alert

 AudibleAlert = log.SelfdriveState.AudibleAlert


 class TestSoundd(OpenpilotTestCase):
-  @staticmethod
-  def milestone_submaster(event_id=42):
-    class SubMasterStub:
-      def __init__(self):
-        self.updated = {'assistedDrivingMilestoneState': True}
-        msg = messaging.new_message('assistedDrivingMilestoneState')
-        msg.assistedDrivingMilestoneState.enabled = True
-        msg.assistedDrivingMilestoneState.event.id = event_id
-        self.data = {'assistedDrivingMilestoneState': msg.assistedDrivingMilestoneState}
-
-      def __getitem__(self, service):
-        return self.data[service]
-
-    return SubMasterStub()
-
-  def test_comma_four_volume_is_50_percent_louder_than_comma_three_x(self):
-    for weighted_db in (20.0, 30.0, 40.0, 50.0):
-      with self.subTest(weighted_db=weighted_db):
-        comma_three_x_volume = calculate_volume_for_device(weighted_db, "tizi")
-        comma_four_volume = calculate_volume_for_device(weighted_db, "mici")
-        assert comma_four_volume == min(1.0, comma_three_x_volume * 1.5)
-
-  def test_milestone_chime_uses_typed_milestone_event_once(self):
-    soundd = Soundd()
-    sm = self.milestone_submaster()
-    soundd.update_milestone_alert(sm)
-
-    assert soundd.current_alert == AudibleAlert.complete
-    soundd.current_alert = AudibleAlert.none
-    soundd.update_milestone_alert(sm)
-    assert soundd.current_alert == AudibleAlert.none
-
-  def test_safety_alert_consumes_milestone_without_replaying_it(self):
-    soundd = Soundd()
-    sm = self.milestone_submaster()
-    soundd.current_alert = AudibleAlert.warningImmediate
-
-    soundd.update_milestone_alert(sm)
-    soundd.current_alert = AudibleAlert.none
-    soundd.update_milestone_alert(sm)
-
-    assert soundd.current_alert == AudibleAlert.none
-
-  def test_quiet_mode_consumes_milestone_without_playing_it(self):
-    soundd = Soundd()
-    soundd.enabled = True
-
-    soundd.update_milestone_alert(self.milestone_submaster())
-
-    assert soundd.current_alert == AudibleAlert.none
-
  def test_check_selfdrive_timeout_alert(self, mocker):
    sm = SubMaster(['selfdriveState', 'selfdriveStateSP'])
    pm = PubMaster(['selfdriveState', 'selfdriveStateSP'])
@@ -12,6 +12,7 @@ from openpilot.common.swaglog import cloudlog
 from openpilot.selfdrive.ui.lib.prime_state import PrimeState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.common.hardware import HARDWARE, PC
+from openpilot.common.hardware.usb import TYPEC_CC_ORIENTATION_PATH, get_usb_state, is_chestnut_usb_id, read_int
 from openpilot.selfdrive.modeld.helpers import chestnut_compiled

 from openpilot.selfdrive.ui.sunnypilot.ui_state import UIStateSP, DeviceSP
@@ -95,6 +96,10 @@ class UIState(UIStateSP):
    self.chestnut_compiled: bool = chestnut_compiled()
    self.chestnut_active: bool | None = None
    self.chestnut_loading: bool = False
+    self.usb_connected: bool = False
+    self.usb_connected_ts: float | None = None
+    self.usb_disconnected_ts: float | None = None
+    self.usb_unknown: bool = False
    self.chestnut_state = ChestnutState.DISCONNECTED
    self.started: bool = False
    self.ignition: bool = False
@@ -254,6 +259,23 @@ class UIState(UIStateSP):
      self.chestnut_compiled = chestnut_compiled()
    self.chestnut_active = self.params.get("ChestnutActive")
    self.chestnut_loading = self.params.get_bool("ChestnutLoading")
+    now = time.monotonic()
+    if read_int(TYPEC_CC_ORIENTATION_PATH) != 0:
+      self.usb_disconnected_ts = None
+      if not self.usb_connected:
+        self.usb_connected = True
+        self.usb_connected_ts = now
+        self.usb_unknown = False
+      elif self.usb_connected_ts is not None and now - self.usb_connected_ts > 10.:
+        self.usb_unknown = not any(is_chestnut_usb_id(d["vendorId"], d["productId"], True) for d in get_usb_state())
+        self.usb_connected_ts = None
+    elif self.usb_connected:
+      if self.usb_disconnected_ts is None:
+        self.usb_disconnected_ts = now
+      elif now - self.usb_disconnected_ts > PARAM_UPDATE_TIME:
+        self.usb_connected = False
+        self.usb_connected_ts = None
+        self.usb_unknown = False

    UIStateSP.update_params(self)

@@ -41,7 +41,6 @@ from tinygrad.tensor import Tensor
 MODEL_TYPES = ('vision_policy', 'supercombo', 'vision_multi_policy')
 WARP_INPUTS = ['tfm', 'big_tfm']
 POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
-WARP_DEV = os.getenv('WARP_DEV')


 def _detect_desire_key(shapes: dict) -> str | None:
@@ -154,11 +153,10 @@ def make_warp_queues(device=Device.DEFAULT):

 def make_warp(nv12: NV12Frame, model_w: int, model_h: int):
  frame_prepare = make_frame_prepare(nv12, model_w, model_h)
-  WARP_DEV = os.getenv('WARP_DEV', Device.DEFAULT)

  def warp(tfm, big_tfm, frame, big_frame):
-    tfm = tfm.to(WARP_DEV)
-    big_tfm = big_tfm.to(WARP_DEV)
+    tfm = tfm.to(Device.DEFAULT)
+    big_tfm = big_tfm.to(Device.DEFAULT)
    Tensor.realize(tfm, big_tfm)

    warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
@@ -368,16 +366,18 @@ if __name__ == "__main__":
  run_policy_func = make_run_policy(vision_runner, policy_runners, features_slice, derived_frame_skip, all_shapes)
  run_policy_jit = TinyJit(run_policy_func, prune=True)
  make_policy_queues = partial(generate_queues_and_npy, all_shapes, derived_frame_skip, is_supercombo=is_supercombo)
-  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=WARP_DEV)
+  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=Device.DEFAULT)
  output_data['run_policy'] = compile_jit(run_policy_jit, make_random_model_inputs, POLICY_INPUTS, make_policy_queues)

  for cam_w, cam_h in args.camera_resolutions:
    print(f"Compiling warp JIT for {cam_w}x{cam_h}...")
    nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=WARP_DEV)
+    make_random_warp_inputs = partial(make_random_images, keys=['frame', 'big_frame'], shape=nv12.size, device=Device.DEFAULT)
    warp = TinyJit(make_warp(nv12, model_w, model_h), prune=True)
    output_data[(cam_w, cam_h)] = compile_jit(warp, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)

+  output_data['metadata']['warp_dev'] = Device.DEFAULT
+
  with open(args.output, "wb") as file:
    dump_oob(output_data, file)

@@ -6,6 +6,7 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """

+from collections.abc import Callable
 import os
 os.environ['GMMU'] = '0'
 import numpy as np
@@ -110,18 +111,12 @@ class ModelState(ModelStateBase):
    cloudlog.warning(f"loading combined pkl: {pkl_path}")
    jits = load_oob(open_file_chunked(pkl_path))

-    self.WARP_DEV = 'QCOM' if COMMA_HARDWARE else 'CPU'
-    self.DEV = 'AMD' if self.chestnut else self.WARP_DEV
-    self.QUEUE_DEV = self.DEV
    metadata = jits['metadata']
-
-    self.is_legacy_model = 'run_policy' not in jits  # remove after next recompile
-    if self.is_legacy_model:
-      self.warp = jits[(cam_w, cam_h)]['warp_enqueue']
-      self.run_policy = jits[(cam_w, cam_h)]['run_policy']
-    else:
-      self.run_policy = jits['run_policy']
-      self.warp = jits[(cam_w, cam_h)]
+    self.WARP_DEV = metadata.get('warp_dev', 'QCOM' if COMMA_HARDWARE else 'CPU')
+    self.DEV = 'AMD' if self.chestnut else ('QCOM' if COMMA_HARDWARE else 'CPU')
+    self.QUEUE_DEV = self.DEV
+    self.run_policy = jits['run_policy']
+    self.warp = jits[(cam_w, cam_h)]

    if 'model' in metadata:
      model_metadata = metadata['model']
@@ -180,11 +175,7 @@ class ModelState(ModelStateBase):
    yuv_size = self.frame_buf_params[self._road_key][3]
    frame_tensor = Tensor(np.zeros(yuv_size, dtype=np.uint8), device=self.WARP_DEV).contiguous().realize()
    big_frame_tensor = Tensor(np.zeros(yuv_size, dtype=np.uint8), device=self.WARP_DEV).contiguous().realize()
-
-    if self.is_legacy_model: # Remove this conditional hack after recompile
-      self.warp(**self.input_queues, frame=frame_tensor, big_frame=big_frame_tensor)
-    else:
-      self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=frame_tensor, big_frame=big_frame_tensor)
+    self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=frame_tensor, big_frame=big_frame_tensor)

  def warmup(self) -> None:
    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], dtype=np.uint8) for k in self._vision_input_names}
@@ -217,7 +208,8 @@ class ModelState(ModelStateBase):
    return self._desire_key

  def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
-                inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None:
+          inputs: dict[str, np.ndarray], prepare_only: bool,
+          after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray] | None:
    for key in bufs.keys():
      ptr = np.frombuffer(bufs[key].data, dtype=np.uint8).ctypes.data
      yuv_size = self.frame_buf_params[key][3]
@@ -239,20 +231,18 @@ class ModelState(ModelStateBase):
    self.numpy_inputs['tfm'][:, :] = transforms[road_key].reshape(3, 3)
    self.numpy_inputs['big_tfm'][:, :] = transforms[wide_key].reshape(3, 3)

-    if self.is_legacy_model:  # remove after next recompile
-      if prepare_only:
-        self.warp(**self.input_queues, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-        return None
-      raw_outputs = self.run_policy(**self.input_queues, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-    else:
-      if prepare_only:
-        self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-        return None
-      warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
-      raw_outputs = self.run_policy(**{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped)
+    if prepare_only:
+      self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
+      return None
+    warped = self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=self.full_frames[road_key], big_frame=self.full_frames[wide_key])
+    raw_outputs = self.run_policy(**{k: self.input_queues[k] for k in POLICY_INPUTS if k in self.input_queues}, warped=warped)
+    if after_enqueue is not None:
+      after_enqueue()

    if self._combined_model_type == 'supercombo':
      model_output = raw_outputs.numpy().flatten()
+      if self.chestnut and not np.all(np.isfinite(model_output)):
+        raise RuntimeError("model output not finite")
      sliced = {k: model_output[np.newaxis, v] for k, v in self.vision_output_slices.items()}
      outputs = self.parser.parse_outputs(sliced)
      if 'prev_feat' in self.numpy_inputs:
@@ -285,9 +275,6 @@ class ModelState(ModelStateBase):
      buf[0, :-1] = buf[0, 1:]
      buf[0, -1, :] = outputs['desired_curvature'][0, :] if not self.mlsim else 0

-    if self.chestnut and not np.all(np.isfinite(outputs.get('plan', np.array([0.])))):
-      raise RuntimeError("model output not finite")
-
    return outputs

  def get_action_from_model(self, model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
@@ -512,7 +499,9 @@ def main(demo=False):

    mt1 = time.perf_counter()
    try:
-      model_output = model.run(bufs, transforms, inputs, prepare_only)
+      send_chestnut = (chestnut_state is not None and
+                       run_count % round(model.constants.MODEL_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0)
+      model_output = model.run(bufs, transforms, inputs, prepare_only, chestnut_state.send if send_chestnut else None)
    except Exception:
      if not params.get_bool("ChestnutActive"):
        raise
@@ -559,9 +548,6 @@ def main(demo=False):
      pm.send('modelDataV2SP', mdv2sp_send)
    last_vipc_frame_id = meta_main.frame_id

-    if chestnut_state is not None and run_count % round(model.constants.MODEL_FREQ / SERVICE_LIST['chestnutState'].frequency) == 0:
-      chestnut_state.send()
-
 if __name__ == "__main__":
  try:
    import argparse
@@ -75,11 +75,11 @@ class TestStockEquivalence(OpenpilotTestCase):

    frame_skip = derive_frame_skip(SPLIT_VISION_INPUT_SHAPES, SPLIT_POLICY_INPUT_SHAPES)
    stock_shapes = {**SPLIT_VISION_INPUT_SHAPES, **SPLIT_POLICY_INPUT_SHAPES, 'action_t': (1, 2)}
-    stock_queues, stock_npy = make_input_queues(stock_shapes, frame_skip, device='NPY')
+    stock_queues, stock_npy, _frame_views = make_input_queues(stock_shapes, frame_skip, device='NPY', frame_copy_size=49152)

-    assert set(state.input_queues.keys()) == set(stock_queues.keys())
+    # sunnypilot split pipeline has tfm/big_tfm as queues (stock has them in npy only)
+    assert set(stock_queues.keys()) <= set(state.input_queues.keys())
    assert {'desire', 'traffic_convention'} <= set(state.numpy_inputs.keys())
-    assert set(state.numpy_inputs.keys()) == set(stock_npy.keys()) - {'action_t', 'prev_feat'}

  def test_split_queue_keys_work_with_desire_key(self, model_state_factory):
    from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, make_split_input_queues
@@ -7,6 +7,7 @@ See the LICENSE.md file in the root directory for more details.

 import os
 import tempfile
+import unittest
 from pathlib import Path

 import numpy as np
@@ -248,23 +249,27 @@ class TestStockCompileModeldEquivalence(OpenpilotTestCase):
    input_shapes = {
      'img': (1, 12, 128, 256),
      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
+      'features_buffer': (1, 24, 32, 512),
      'traffic_convention': (1, 2),
      'action_t': (1, 2),
    }
    frame_skip = 4

-    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
+    stock_queues, stock_npy, _frame_views = stock_make_input_queues(input_shapes, frame_skip, device='NPY', frame_copy_size=49152)
    sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
-    assert set(sunny_queues.keys()) == set(stock_queues.keys())
+    # sunnypilot split pipeline has tfm/big_tfm as queues; packed_npy_inputs size differs (different frame packing)
+    assert set(stock_queues.keys()) <= set(sunny_queues.keys())
    for key in stock_queues:
+      if key == 'packed_npy_inputs':
+        continue
      assert sunny_queues[key].shape == stock_queues[key].shape, \
        f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
-    assert set(sunny_npy.keys()) == set(stock_npy.keys())
+    assert set(stock_npy.keys()) <= set(sunny_npy.keys())
    for key in stock_npy:
      assert sunny_npy[key].shape == stock_npy[key].shape, \
        f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"

+  @unittest.skip("upstream removed make_warp_input_queues — warp merged into run_model")
  def test_make_warp_queues_stock_equivalence(self):
    from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues
@@ -20,18 +20,46 @@ def get_default_model() -> str:

 DEFAULT_MODEL_NAME_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "model_name.py")
 MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "model_hash")
+BIG_MODEL_HASH_PATH = os.path.join(BASEDIR, "openpilot", "sunnypilot", "models", "tests", "big_model_hash")
 SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "driving_supercombo.onnx")
+BIG_SUPERCOMBO_ONNX_PATH = os.path.join(BASEDIR, "openpilot", "selfdrive", "modeld", "models", "big_driving_supercombo.onnx")
+
+
+def _read_model_name_fields():
+  with open(DEFAULT_MODEL_NAME_PATH) as f:
+    content = f.read()
+  fields = {}
+  for line in content.splitlines():
+    if "=" in line:
+      key, val = line.split("=", 1)
+      fields[key.strip()] = val.strip().strip('"')
+  return fields


 def update_model_hash():
+  fields = _read_model_name_fields()
  supercombo_hash = get_file_hash(SUPERCOMBO_ONNX_PATH)
-  combined_hash = hashlib.sha256(supercombo_hash.encode()).hexdigest()
+  fingerprint = f"{supercombo_hash}:{fields.get('DEFAULT_MODEL', '')}:{fields.get('DEFAULT_MODEL_REF', '')}"
+  combined_hash = hashlib.sha256(fingerprint.encode()).hexdigest()

  with open(MODEL_HASH_PATH, "w") as f:
    f.write(combined_hash)

  print(f"Generated and updated new combined model hash to {MODEL_HASH_PATH}")

+  if os.path.exists(BIG_SUPERCOMBO_ONNX_PATH):
+    import subprocess
+    rel = os.path.relpath(BIG_SUPERCOMBO_ONNX_PATH, os.getcwd())
+    pointer = subprocess.check_output(["git", "show", f"HEAD:{rel}"], text=True)
+    oid = next(l.split(":", 1)[1] for l in pointer.splitlines() if l.startswith("oid sha256:"))
+    big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
+    big_combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()
+
+    with open(BIG_MODEL_HASH_PATH, "w") as f:
+      f.write(big_combined_hash)
+
+    print(f"Generated and updated new big model hash to {BIG_MODEL_HASH_PATH}")
+

 def get_ref_for_name(url: str, name: str) -> str:
  response = requests.get(url, timeout=10)
@@ -138,8 +138,8 @@ class ModelCache:

 class ModelFetcher:
  """Handles fetching and caching of model data from remote source"""
-  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v21.json"
-  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v22.json"
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v22.json"
+  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v24.json"

  MODEL_SOURCES = {
    "qcom": (MODEL_URL, ""),
@@ -19,7 +19,7 @@ from openpilot.common.hardware.hw import Paths
 from openpilot.selfdrive.modeld.helpers import chestnut_present

 # SET ME TO THE EXACT JSON VERSION WE SET IN SUNNYPILOT_MODELS REPO
-REQUIRED_JSON_VERSION = 18
+REQUIRED_JSON_VERSION = 19

 CUSTOM_MODEL_PATH = Paths.model_root()
 METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'
@@ -1,4 +1,4 @@
 DEFAULT_MODEL = "CD210"
 DEFAULT_MODEL_REF = "5b6436a90cf6902b8aaa71c2b6f3d7164d8ae391"
-DEFAULT_BIG_MODEL = "Lebowski"
-DEFAULT_BIG_MODEL_REF = "fa0c6876d3cf070e91e25e5353ceadc68a5b3285"
+DEFAULT_BIG_MODEL = "BMRLNAP Model v4"
+DEFAULT_BIG_MODEL_REF = "f877d7a0ccc3cce943c76e285214c020cd65c899"
@@ -0,0 +1 @@
+2c814f08a2c51323b87839fbf8d2c2a9853a2b5536271b3d67f7b7a2de7f9374
@@ -1 +1 @@
-49133798d9cd9cacf47085c7ef8122bfee88cd9c6192a8314c81bfb1b37f5809
+c5be11d2fb1115be953c541f30c50f7c71a00bc4a0e128e19aa11b60689317fc
@@ -5,19 +5,47 @@ 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 os
+import subprocess
+
 from openpilot.sunnypilot import get_file_hash
-from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, SUPERCOMBO_ONNX_PATH
+from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, SUPERCOMBO_ONNX_PATH, BIG_MODEL_HASH_PATH, \
+                                                      BIG_SUPERCOMBO_ONNX_PATH, _read_model_name_fields
 import hashlib
 from openpilot.common.test import OpenpilotTestCase


+def _get_lfs_oid(path: str) -> str:
+  """Extract the LFS OID (SHA256 of actual content) from git, works whether the file is smudged or not."""
+  pointer = subprocess.check_output(["git", "show", f"HEAD:{path}"], text=True)
+  for line in pointer.splitlines():
+    if line.startswith("oid sha256:"):
+      return line.split(":", 1)[1]
+  raise ValueError(f"No LFS OID found for {path}")
+
+
 class TestDefaultModel(OpenpilotTestCase):
  def test_compare_onnx_hashes(self):
+    fields = _read_model_name_fields()
    supercombo_hash = get_file_hash(SUPERCOMBO_ONNX_PATH)
-
-    combined_hash = hashlib.sha256(supercombo_hash.encode()).hexdigest()
+    fingerprint = f"{supercombo_hash}:{fields.get('DEFAULT_MODEL', '')}:{fields.get('DEFAULT_MODEL_REF', '')}"
+    combined_hash = hashlib.sha256(fingerprint.encode()).hexdigest()

    with open(MODEL_HASH_PATH) as f:
      current_hash = f.read().strip()

    assert combined_hash == current_hash, "Run openpilot/sunnypilot/models/default_model.py to update the default model name and hash"
+
+  def test_compare_big_onnx_hashes(self):
+    if not os.path.exists(BIG_SUPERCOMBO_ONNX_PATH):
+      self.skipTest("big_driving_supercombo.onnx not present")
+
+    fields = _read_model_name_fields()
+    oid = _get_lfs_oid(os.path.relpath(BIG_SUPERCOMBO_ONNX_PATH, os.getcwd()))
+    big_fingerprint = f"{oid}:{fields.get('DEFAULT_BIG_MODEL', '')}:{fields.get('DEFAULT_BIG_MODEL_REF', '')}"
+    combined_hash = hashlib.sha256(big_fingerprint.encode()).hexdigest()
+
+    with open(BIG_MODEL_HASH_PATH) as f:
+      current_hash = f.read().strip()
+
+    assert combined_hash == current_hash, "Run openpilot/sunnypilot/models/default_model.py to update the default model name and hash"
@@ -386,7 +386,7 @@ class TestManagerDownload(ManagerDownloadTestBase):
    def body():
      artifact = self.make_artifact(chunked=True)
      self._bundle.ref = "test-ref"
-      self._bundle.minimumSelectorVersion = 18
+      self._bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
      params, store = self._make_params_with_store()
      self.manager.params = params
      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "qcom"))
@@ -406,7 +406,7 @@ class TestManagerDownload(ManagerDownloadTestBase):
    def body():
      self.make_artifact(chunked=True)
      self._bundle.ref = "big-ref"
-      self._bundle.minimumSelectorVersion = 18
+      self._bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
      params, store = self._make_params_with_store()
      self.manager.params = params
      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "chestnut"))
@@ -469,7 +469,7 @@ def manifest_bundle(short_name: str, ref: str, index: int = 0, is_big: bool = Fa
    "environment": "release",
    "runner": "tinygrad",
    "is_big": is_big,
-    "minimum_selector_version": "18",
+    "minimum_selector_version": str(helpers.REQUIRED_JSON_VERSION),
    "ref": ref,
    "models": [{
      "type": "supercombo",
@@ -655,7 +655,7 @@ class TestActiveBundleValidation(OpenpilotTestCase):
  def _raw_bundle(ref: str, runner: int | None = None) -> dict:
    bundle = custom.ModelManagerSP.ModelBundle.new_message()
    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
+    bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
    if runner is not None:
      bundle.runner = runner
    return bundle.to_dict()
@@ -697,7 +697,7 @@ class TestActiveBundleSelection(OpenpilotTestCase):
  def _raw_bundle(ref: str) -> dict:
    bundle = custom.ModelManagerSP.ModelBundle.new_message()
    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
+    bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
    return bundle.to_dict()

  def _params(self, qcom=None, chestnut=None):
@@ -744,7 +744,7 @@ class TestEffectiveSource(OpenpilotTestCase):
  def _raw_bundle(ref: str) -> dict:
    bundle = custom.ModelManagerSP.ModelBundle.new_message()
    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
+    bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
    return bundle.to_dict()

  def test_runtime_no_gpu(self):
@@ -104,14 +104,6 @@ class ControlsExt(ModelStateBase):
    CC_SP.intelligentCruiseButtonManagement.sendButton = icbm_src.sendButton
    CC_SP.intelligentCruiseButtonManagement.vTarget = icbm_src.vTarget

-    ford_path = getattr(self, 'ford_path', None)
-    if ford_path is not None:
-      CC_SP.fordLateralPath.valid = ford_path.valid
-      CC_SP.fordLateralPath.pathOffset = ford_path.path_offset
-      CC_SP.fordLateralPath.pathAngle = ford_path.path_angle
-      CC_SP.fordLateralPath.curvature = ford_path.curvature
-      CC_SP.fordLateralPath.curvatureRate = ford_path.curvature_rate
-
    return CC_SP

  @staticmethod
@@ -1,260 +0,0 @@
-"""Authoritative assisted-driving distance and milestone tracking."""
-
-import math
-from collections.abc import Mapping
-from dataclasses import dataclass
-from enum import StrEnum
-
-from openpilot.common.params import Params
-
-
-METERS_PER_MILE = 1609.344
-METERS_PER_KILOMETER = 1000.0
-MAX_SAMPLE_INTERVAL_SECONDS = 0.5
-PERSIST_INTERVAL_NS = 10_000_000_000
-STATE_VERSION = 1
-STATE_PARAM = "AssistedDrivingMilestoneState"
-LAST_DRIVE_SUMMARY_PARAM = "LastDriveAssistedDrivingSummary"
-
-
-class AssistCategory(StrEnum):
-  MADS = "mads"
-  FULL_ASSIST = "fullAssist"
-
-
-class MilestoneUnit(StrEnum):
-  IMPERIAL = "imperial"
-  METRIC = "metric"
-
-
-@dataclass(frozen=True)
-class MilestoneEvent:
-  event_id: int
-  category: AssistCategory
-  distance_meters: float
-  previous_distance_meters: float
-  unit: MilestoneUnit
-
-
-@dataclass(frozen=True)
-class MilestoneSnapshot:
-  distances_meters: dict[AssistCategory, float]
-  drive_start_distances_meters: dict[AssistCategory, float]
-  next_event_id: int
-  next_summary_id: int
-  unit: MilestoneUnit
-  active_drive_id: str
-
-
-def assist_category(lat_active: bool, long_active: bool) -> AssistCategory | None:
-  if not lat_active:
-    return None
-  return AssistCategory.FULL_ASSIST if long_active else AssistCategory.MADS
-
-
-def _meters_per_unit(unit: MilestoneUnit) -> float:
-  return METERS_PER_KILOMETER if unit == MilestoneUnit.METRIC else METERS_PER_MILE
-
-
-def _next_ladder_value(value: float) -> float:
-  value = max(0.0, value)
-  magnitude = 10.0 ** math.floor(math.log10(max(1.0, value)))
-  for multiplier in (1.0, 2.0, 5.0):
-    candidate = multiplier * magnitude
-    if candidate > value + 1e-9:
-      return candidate
-  return 10.0 * magnitude
-
-
-def _previous_ladder_value(value: float) -> float:
-  if value <= 1.0:
-    return 0.0
-  magnitude = 10.0 ** math.floor(math.log10(value))
-  normalized = value / magnitude
-  if normalized <= 1.0 + 1e-9:
-    return 5.0 * magnitude / 10.0
-  if normalized <= 2.0 + 1e-9:
-    return magnitude
-  return 2.0 * magnitude
-
-
-def next_milestone_meters(distance_meters: float, unit: MilestoneUnit) -> float:
-  meters_per_unit = _meters_per_unit(unit)
-  return _next_ladder_value(distance_meters / meters_per_unit) * meters_per_unit
-
-
-class MilestoneStore:
-  def __init__(self, params: Params | None = None):
-    self._params = params or Params()
-
-  def load(self) -> MilestoneSnapshot:
-    raw = self._params.get(STATE_PARAM, return_default=True)
-    raw = raw if isinstance(raw, dict) else {}
-    raw_distances = raw.get("distancesMeters", {})
-    raw_distances = raw_distances if isinstance(raw_distances, dict) else {}
-    try:
-      unit = MilestoneUnit(raw.get("unit", MilestoneUnit.IMPERIAL))
-    except ValueError:
-      unit = MilestoneUnit.IMPERIAL
-
-    def distance(category: AssistCategory) -> float:
-      try:
-        return max(0.0, float(raw_distances.get(category.value, 0.0)))
-      except (TypeError, ValueError):
-        return 0.0
-
-    distances = {category: distance(category) for category in AssistCategory}
-    raw_drive_start = raw.get("driveStartDistancesMeters", {})
-    raw_drive_start = raw_drive_start if isinstance(raw_drive_start, dict) else {}
-
-    def drive_start_distance(category: AssistCategory) -> float:
-      try:
-        return max(0.0, min(float(raw_drive_start.get(category.value, distances[category])), distances[category]))
-      except (TypeError, ValueError):
-        return distances[category]
-
-    try:
-      next_event_id = max(1, int(raw.get("nextEventId", 1)))
-    except (TypeError, ValueError):
-      next_event_id = 1
-    try:
-      next_summary_id = max(1, int(raw.get("nextSummaryId", 1)))
-    except (TypeError, ValueError):
-      next_summary_id = 1
-
-    return MilestoneSnapshot(
-      distances_meters=distances,
-      drive_start_distances_meters={category: drive_start_distance(category) for category in AssistCategory},
-      next_event_id=next_event_id,
-      next_summary_id=next_summary_id,
-      unit=unit,
-      active_drive_id=str(raw.get("activeDriveId", "")),
-    )
-
-  def save(self, snapshot: MilestoneSnapshot, block: bool = False) -> None:
-    if block:
-      self._params.flush()
-    self._params.put(STATE_PARAM, {
-      "version": STATE_VERSION,
-      "distancesMeters": {category.value: max(0.0, snapshot.distances_meters.get(category, 0.0)) for category in AssistCategory},
-      "driveStartDistancesMeters": {
-        category.value: max(0.0, snapshot.drive_start_distances_meters.get(category, 0.0)) for category in AssistCategory
-      },
-      "nextEventId": max(1, snapshot.next_event_id),
-      "nextSummaryId": max(1, snapshot.next_summary_id),
-      "unit": snapshot.unit.value,
-      "activeDriveId": snapshot.active_drive_id,
-    }, block=block)
-
-  def save_drive_summary(self, summary_id: int, distances_meters: Mapping[AssistCategory, float], unit: MilestoneUnit) -> None:
-    self._params.put(LAST_DRIVE_SUMMARY_PARAM, {
-      "version": STATE_VERSION,
-      "id": summary_id,
-      "distancesMeters": {category.value: max(0.0, distances_meters.get(category, 0.0)) for category in AssistCategory},
-      "unit": unit.value,
-    }, block=True)
-
-
-class AssistedDrivingMilestones:
-  """Tracks, persists, and emits milestones through one small interface."""
-
-  def __init__(self, store: MilestoneStore | None = None):
-    self._store = store or MilestoneStore()
-    snapshot = self._store.load()
-    self._distances_meters = snapshot.distances_meters
-    self._drive_start_distances_meters = snapshot.drive_start_distances_meters
-    self._next_event_id = snapshot.next_event_id
-    self._next_summary_id = snapshot.next_summary_id
-    self._unit = snapshot.unit
-    self._active_drive_id = snapshot.active_drive_id
-    self._next_milestone_meters = {
-      category: next_milestone_meters(distance, self._unit)
-      for category, distance in self._distances_meters.items()
-    }
-    self._last_timestamp_ns: int | None = None
-    self._last_persist_timestamp_ns: int | None = None
-    self._last_speed_mps = 0.0
-    self._last_category: AssistCategory | None = None
-    self._enabled = False
-    self._closed = False
-
-  def snapshot(self) -> MilestoneSnapshot:
-    return MilestoneSnapshot(
-      self._distances_meters.copy(),
-      self._drive_start_distances_meters.copy(),
-      self._next_event_id,
-      self._next_summary_id,
-      self._unit,
-      self._active_drive_id,
-    )
-
-  def set_drive_id(self, drive_id: str) -> None:
-    if not drive_id or drive_id == self._active_drive_id:
-      return
-    self._active_drive_id = drive_id
-    self._drive_start_distances_meters = self._distances_meters.copy()
-    self._persist()
-
-  def update(self, timestamp_ns: int, speed_mps: float, *, lat_active: bool, long_active: bool,
-             is_metric: bool, enabled: bool) -> MilestoneEvent | None:
-    self._enabled = enabled
-    unit = MilestoneUnit.METRIC if is_metric else MilestoneUnit.IMPERIAL
-    if unit != self._unit:
-      self._unit = unit
-      self._next_milestone_meters = {
-        category: next_milestone_meters(distance, unit)
-        for category, distance in self._distances_meters.items()
-      }
-
-    speed_mps = max(0.0, speed_mps)
-    category = assist_category(lat_active, long_active) if enabled else None
-    event = None
-
-    if self._last_timestamp_ns is not None and timestamp_ns != self._last_timestamp_ns:
-      dt = (timestamp_ns - self._last_timestamp_ns) / 1e9
-      if 0 < dt <= MAX_SAMPLE_INTERVAL_SECONDS and self._last_category is not None:
-        active_category = self._last_category
-        self._distances_meters[active_category] += (self._last_speed_mps + speed_mps) / 2.0 * dt
-        threshold_meters = self._next_milestone_meters[active_category]
-        if self._distances_meters[active_category] >= threshold_meters:
-          meters_per_unit = _meters_per_unit(self._unit)
-          threshold_units = threshold_meters / meters_per_unit
-          event = MilestoneEvent(
-            event_id=self._next_event_id,
-            category=active_category,
-            distance_meters=threshold_meters,
-            previous_distance_meters=_previous_ladder_value(threshold_units) * meters_per_unit,
-            unit=self._unit,
-          )
-          self._next_event_id += 1
-          self._next_milestone_meters[active_category] = next_milestone_meters(threshold_meters, self._unit)
-          self._persist(timestamp_ns=timestamp_ns)
-
-    self._last_timestamp_ns = timestamp_ns
-    self._last_speed_mps = speed_mps
-    self._last_category = category
-
-    if self._last_persist_timestamp_ns is None:
-      self._last_persist_timestamp_ns = timestamp_ns
-    elif timestamp_ns - self._last_persist_timestamp_ns >= PERSIST_INTERVAL_NS:
-      self._persist(timestamp_ns=timestamp_ns)
-
-    return event
-
-  def close(self) -> None:
-    if self._closed:
-      return
-    self._closed = True
-    drive_distances = {
-      category: self._distances_meters[category] - self._drive_start_distances_meters[category]
-      for category in AssistCategory
-    }
-    summary_id = self._next_summary_id
-    self._next_summary_id += 1
-    self._persist(block=True)
-    if self._enabled:
-      self._store.save_drive_summary(summary_id, drive_distances, self._unit)
-
-  def _persist(self, block: bool = False, timestamp_ns: int | None = None) -> None:
-    self._store.save(self.snapshot(), block=block)
-    self._last_persist_timestamp_ns = self._last_timestamp_ns if timestamp_ns is None else timestamp_ns
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
discountchubbs	da18292c3d	remove realized frame	2026-09-05 09:53:04 -07:00
discountchubbs	63c99de298	models: remove tg_occupancy_opt	2026-09-05 07:28:37 -07:00
James Vecellio-Grant	047ae41c0d	modeld_v2: one dev warp and enqueue (#1990 )	2026-09-04 21:15:00 -07:00
Nayan	7eb457f6c4	chaos (#1991 ) burn it all	2026-09-05 10:50:12 +08:00
James Vecellio-Grant	302f3ad892	ci: compile dm warp (#1989 )	2026-09-04 16:52:09 -07:00
Jason Wen	132b31f4cf	ci: poll GH API in prepare model jobs (#1987 )	2026-09-03 10:10:21 -04:00
James Vecellio-Grant	752c07f9e4	ci: Replace hf oath with token (#1986 ) replace oauth with token	2026-09-03 08:22:43 -04:00
Jason Wen	e87dbbaba7	models: sanitize default model name for HF (#1984 )	2026-09-02 14:53:31 -04:00
Jason Wen	15efdb392f	Sync: `commaai/openpilot:master` → `sunnypilot/sunnypilot:master` (#1983 ) * ui: remove raygui usage (#38708) * ui: remove raygui usage * match previous gui_text_box line spacing * Revert "match previous gui_text_box line spacing" This reverts commit ffd2fe31725c6d50bffaebc621c1e170d0926c66. * Reapply "match previous gui_text_box line spacing" This reverts commit d41404f09607e225f43868f7747f22dc0bb2cf16. * log chestnut supply fault (#38711) * log chestnut INA supply fault * ci * bump raylib (#38712) * cabana: replace custom non-view Qt signals w/ plain observer (#38713) * cabana: move RoutesDialog out of streams/ (#38716) * cabana: string helpers in utils return std::string (#38720) * cabana: use std::string in RoutesDialog API results (#38717) * cabana: move stream open widgets into streamselector (#38715) * cabana: remove Qt from livestream (#38722) * cabana: split SettingsDialog out of settings (#38719) cabana: split SettingsDialog out of settings.{h,cc} * cabana: split comma API route fetching out of RoutesDialog (#38721) * cabana: de-QT streams (#38718) * ui: fix install update button overflow (#38696) * cabana: split utils/util into Qt-free util and qtutil (#38723) * ui: guard branch switcher before internet connected (#38692) * ui: check for update on target branch switch (#38693) * ui: sync gpu loading to offroad (#38727) ui: sync gpu loading state * add chestnut offroad alerts (#38706) * system: add chestnut offroad alerts * system: refine chestnut offroad alerts * system: refine chestnut power alerts * system: confirm chestnut power recovery from PCIe * system: detect missing chestnut power from INA voltage * common: fix OpenpilotPrefix cleanup on macOS (#38728) The destructor built its cleanup commands as "rm %s -rf", with the flags after the operand. GNU rm permutes arguments so this works on device and in CI, but BSD rm on macOS stops option parsing at the first operand and treats "-rf" as a second filename: $ mkdir -p /tmp/rmtest/sub && rm /tmp/rmtest -rf rm: /tmp/rmtest: is a directory rm: -rf: No such file or directory exit=1 So nothing is removed, and each of the four calls prints two errors plus "system command failed (256)" from check_system. Every run of a tool that owns an OpenpilotPrefix (replay, cabana) leaks its params dir, its comma_home and its /tmp/msgq_ dir; 33 of each had accumulated on my machine. Pass the flags first. * replay: capture downloader's stderr so download progress is reported again (#38734) * bump panda (new health packet) (#38736) pandad: support compact health packet * BMRLNAP (#38681) * ui: clarify branch switcher error message (#38732) * ui(mici): name updater signal constants (#38731) * mici: name updater signal constants * drop SIGNAL_ prefix * self contained --------- Co-authored-by: Shane Smiskol <shane@smiskol.com> * modem.py: accept hex chars in ICCID (#38735) E.118 specifies decimal digits, but many real SIMs carry hex characters in EF_ICCID (e.g. China Mobile's 898600B5... range, some MVNO/IoT SIMs). AT+QCCID returns them verbatim, and the strict isdigit() check blanked the ICCID, leaving the modem daemon stuck in INITIALIZING forever and cellular dead. ModemManager parses ICCID as hex for the same reason. Verified on a comma four with a China Mobile SIM (EG916Q-GL): previously stuck retrying 'identity read incomplete', now dials and passes traffic. * TGC (#38739) * 23e6a04e-e6e5-462b-a0bb-e4088275ee43/12864 tgc * here * monitor chestnut USB in hardwared (#38741) hardwared: monitor chestnut USB independently * modeld: wait for stable chestnut (#38742) modeld: wait for stable chestnut * Revert "monitor chestnut USB in hardwared (#38741)" (#38744) This reverts commit `7d5596d5c3`. * amd warp (#38684) * modeld: fuse warp and policy TinyJit * bump tg * fix? * this simple trick... * debug 1 * bump tg * pack all * wips * fix * BIG_INTO_SMALL remove * slower * ui: show usb connection (#38745) * ui: show USB status * ui: resize USB icon * ui: classify USB device once * ui: debounce USB disconnect * cereal: log big model in drivingModelData (#38747) * ui: show one GPU status (#38748) ui: show one GPU status icon * AGNOS 19.7 (#38750) --------- Co-authored-by: Trey Moen <50057480+greatgitsby@users.noreply.github.com> Co-authored-by: Daniel Koepping <elkoled@gmail.com> Co-authored-by: Robbe Derks <robbe.derks@gmail.com> Co-authored-by: Harald Schäfer <harald.the.engineer@gmail.com> Co-authored-by: Shane Smiskol <shane@smiskol.com> Co-authored-by: XiaoXX <xiaoxx97@outlook.com> Co-authored-by: YassineYousfi <yyousfi1@binghamton.edu>	2026-09-02 13:57:07 -04:00
Jason Wen	f5bb855477	Merge commit '6249f4d5b0e63c05f08bce12ca3afebda9f764a3' into sync-20260902 # Conflicts: # openpilot/selfdrive/modeld/SConscript # openpilot/selfdrive/modeld/modeld.py # openpilot/selfdrive/pandad/pandad.cc # openpilot/selfdrive/selfdrived/alerts_offroad.json # openpilot/selfdrive/ui/layouts/onboarding.py # openpilot/selfdrive/ui/mici/layouts/home.py # openpilot/system/hardware/hardwared.py # panda # tinygrad_repo	2026-09-02 13:47:27 -04:00
Jason Wen	47db84ebfb	models: add big model ONNX hash tracking (#1982 )	2026-09-02 01:28:43 -04:00
Jason Wen	68be777395	bump tg	2026-09-01 22:14:43 -04:00
github-actions[bot]	ab389498a8	[bot] Update Python packages (#1950 ) * Update Python packages * bump tg * bump * ci: route build_model runner by target_hardware instead of hardcoding chestnut * hack, remove before merge * Revert build-model runner hack and uv.lock update * why were they hard coded --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Jason Wen <haibin.wen3@gmail.com>	2026-09-01 22:12:54 -04:00
Daniel Koepping	6249f4d5b0	AGNOS 19.7 (#38750 )	2026-09-01 18:32:59 -07:00
Daniel Koepping	8b88f7dd6e	ui: show one GPU status (#38748 ) ui: show one GPU status icon	2026-09-01 18:32:39 -07:00
Harald Schäfer	79658800ce	cereal: log big model in drivingModelData (#38747 )	2026-09-01 17:15:13 -07:00
Daniel Koepping	36561258fa	ui: show usb connection (#38745 ) * ui: show USB status * ui: resize USB icon * ui: classify USB device once * ui: debounce USB disconnect	2026-09-01 15:45:57 -07:00
YassineYousfi	cb85ac1f0e	amd warp (#38684 ) * modeld: fuse warp and policy TinyJit * bump tg * fix? * this simple trick... * debug 1 * bump tg * pack all * wips * fix * BIG_INTO_SMALL remove * slower	2026-09-01 13:59:55 -07:00
Daniel Koepping	c9f1602040	Revert "monitor chestnut USB in hardwared (#38741 )" (#38744 ) This reverts commit `7d5596d5c3`.	2026-09-01 11:13:30 -07:00
Daniel Koepping	06af2abe67	modeld: wait for stable chestnut (#38742 ) modeld: wait for stable chestnut	2026-09-01 07:20:56 -07:00
Daniel Koepping	7d5596d5c3	monitor chestnut USB in hardwared (#38741 ) hardwared: monitor chestnut USB independently	2026-09-01 05:59:02 -07:00
YassineYousfi	a2e422eee0	TGC (#38739 ) * 23e6a04e-e6e5-462b-a0bb-e4088275ee43/12864 tgc * here	2026-08-31 22:30:28 -07:00
XiaoXX	e10c0fd960	modem.py: accept hex chars in ICCID (#38735 ) E.118 specifies decimal digits, but many real SIMs carry hex characters in EF_ICCID (e.g. China Mobile's 898600B5... range, some MVNO/IoT SIMs). AT+QCCID returns them verbatim, and the strict isdigit() check blanked the ICCID, leaving the modem daemon stuck in INITIALIZING forever and cellular dead. ModemManager parses ICCID as hex for the same reason. Verified on a comma four with a China Mobile SIM (EG916Q-GL): previously stuck retrying 'identity read incomplete', now dials and passes traffic.	2026-08-31 21:35:56 -07:00
Trey Moen	da8ce858ec	ui(mici): name updater signal constants (#38731 ) * mici: name updater signal constants * drop SIGNAL_ prefix * self contained --------- Co-authored-by: Shane Smiskol <shane@smiskol.com>	2026-08-31 15:55:16 -07:00
Trey Moen	9fa7ef3d17	ui: clarify branch switcher error message (#38732 )	2026-08-31 15:46:52 -07:00
Harald Schäfer	4adbb85742	BMRLNAP (#38681 )	2026-08-31 09:25:32 -07:00
Robbe Derks	70df7f227b	bump panda (new health packet) (#38736 ) pandad: support compact health packet	2026-08-31 14:01:20 +02:00
Trey Moen	0e32059484	replay: capture downloader's stderr so download progress is reported again (#38734 )	2026-08-30 09:32:36 -07:00
Trey Moen	7cf55c3b7a	common: fix OpenpilotPrefix cleanup on macOS (#38728 ) The destructor built its cleanup commands as "rm %s -rf", with the flags after the operand. GNU rm permutes arguments so this works on device and in CI, but BSD rm on macOS stops option parsing at the first operand and treats "-rf" as a second filename: $ mkdir -p /tmp/rmtest/sub && rm /tmp/rmtest -rf rm: /tmp/rmtest: is a directory rm: -rf: No such file or directory exit=1 So nothing is removed, and each of the four calls prints two errors plus "system command failed (256)" from check_system. Every run of a tool that owns an OpenpilotPrefix (replay, cabana) leaks its params dir, its comma_home and its /tmp/msgq_ dir; 33 of each had accumulated on my machine. Pass the flags first.	2026-08-28 22:11:52 -07:00
Daniel Koepping	682b6a20df	add chestnut offroad alerts (#38706 ) * system: add chestnut offroad alerts * system: refine chestnut offroad alerts * system: refine chestnut power alerts * system: confirm chestnut power recovery from PCIe * system: detect missing chestnut power from INA voltage	2026-08-28 15:46:56 -07:00
Daniel Koepping	a67cdf9a51	ui: sync gpu loading to offroad (#38727 ) ui: sync gpu loading state	2026-08-28 15:08:18 -07:00
Trey Moen	e571e21d14	ui: check for update on target branch switch (#38693 )	2026-08-28 12:07:15 -07:00
Trey Moen	839d3f5004	ui: guard branch switcher before internet connected (#38692 )	2026-08-28 12:06:33 -07:00
Trey Moen	5645370f84	cabana: split utils/util into Qt-free util and qtutil (#38723 )	2026-08-28 11:37:09 -07:00
Trey Moen	633d17cd12	ui: fix install update button overflow (#38696 )	2026-08-28 11:30:13 -07:00
Trey Moen	5419f57b3a	cabana: de-QT streams (#38718 )	2026-08-28 10:18:10 -07:00
Trey Moen	46f612224c	cabana: split comma API route fetching out of RoutesDialog (#38721 )	2026-08-28 09:57:47 -07:00
Trey Moen	6e0f4f4630	cabana: split SettingsDialog out of settings (#38719 ) cabana: split SettingsDialog out of settings.{h,cc}	2026-08-28 09:55:28 -07:00
Trey Moen	0f9c753e6e	cabana: remove Qt from livestream (#38722 )	2026-08-28 09:46:45 -07:00
Trey Moen	131e473f37	cabana: move stream open widgets into streamselector (#38715 )	2026-08-28 09:36:26 -07:00
Trey Moen	30f358eb59	cabana: use std::string in RoutesDialog API results (#38717 )	2026-08-28 07:25:34 -07:00
Trey Moen	9b9e3ea604	cabana: string helpers in utils return std::string (#38720 )	2026-08-28 07:25:11 -07:00
Trey Moen	7cc48b5bc9	cabana: move RoutesDialog out of streams/ (#38716 )	2026-08-27 22:00:24 -07:00
Trey Moen	cbf750de20	cabana: replace custom non-view Qt signals w/ plain observer (#38713 )	2026-08-27 18:54:06 -07:00
Trey Moen	318257fa3b	bump raylib (#38712 )	2026-08-27 11:38:53 -07:00
Daniel Koepping	4cdc16031f	log chestnut supply fault (#38711 ) * log chestnut INA supply fault * ci	2026-08-27 11:21:56 -07:00
Trey Moen	31ea1850f7	ui: remove raygui usage (#38708 ) * ui: remove raygui usage * match previous gui_text_box line spacing * Revert "match previous gui_text_box line spacing" This reverts commit ffd2fe31725c6d50bffaebc621c1e170d0926c66. * Reapply "match previous gui_text_box line spacing" This reverts commit d41404f09607e225f43868f7747f22dc0bb2cf16.	2026-08-27 10:54:52 -07:00
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				`2c814f08a2c51323b87839fbf8d2c2a9853a2b5536271b3d67f7b7a2de7f9374`