Ford: drive C2-free C0 from planned curvature

Encode the selected bounded curvature as C0 with an 8 m minimum preview while retaining full model-heading C1. Limit each channel independently so C1 transitions cannot delay C0 release, and validate the selected action source timestamp.

Add action, release, source-freshness, CAN and route regressions. Document the slow-turn reference disagreement and the limits of frozen-motion replay; physical centering remains unvalidated.

.gitattributes

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

.github/workflows/build-all-tinygrad-models.yaml

@@ -78,7 +78,6 @@ 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

.github/workflows/build-default-models.yaml

@@ -30,7 +30,6 @@ 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 }}
@@ -65,9 +64,7 @@ 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
@@ -138,7 +135,7 @@ jobs:
 
       - name: Prepare output
         env:
-          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH=${{ github.workspace }}
@@ -161,13 +158,13 @@ jobs:
       - name: Upload small model artifact
         uses: actions/upload-artifact@v4
         with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
           path: ${{ github.workspace }}/small_output/
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: ${{ github.workspace }}/small_output/artifact_name.txt
 
       - name: Re-enable powersave
@@ -257,7 +254,7 @@ jobs:
 
       - name: Prepare output
         env:
-          MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
+          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           export PYTHONPATH=${{ github.workspace }}
@@ -280,13 +277,13 @@ jobs:
       - name: Upload big model artifact
         uses: actions/upload-artifact@v4
         with:
-          name: model-${{ needs.resolve.outputs.safe_model_name }}-${{ github.run_number }}
+          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
           path: ${{ github.workspace }}/big_output/
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: ${{ github.workspace }}/big_output/artifact_name.txt
 
       - name: Re-enable powersave
@@ -321,7 +318,7 @@ jobs:
         if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
         uses: actions/download-artifact@v4
         with:
-          name: artifact-name-${{ needs.resolve.outputs.safe_model_name }}
+          name: artifact-name-${{ needs.resolve.outputs.model_name }}
           path: artifact_name
 
       - name: Read artifact name
@@ -341,7 +338,7 @@ jobs:
       - name: Upload model to HF
         if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
           ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
         run: |
           rm -f output/artifact_name.txt
@@ -367,7 +364,7 @@ jobs:
       - name: Generate DM metadata and upload to HF
         if: ${{ inputs.target == 'dm' }}
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
         run: |
           export PYTHONPATH=$(pwd)
           python3 -c "
@@ -484,29 +481,11 @@ 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

.github/workflows/build-single-tinygrad-model.yaml

@@ -146,7 +146,7 @@ jobs:
 
       - name: Validate hf_repo and JSON version
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
         run: |
           if [ ! -f "$JSON_FILE" ]; then
             echo "JSON file $JSON_FILE does not exist!"
@@ -155,8 +155,13 @@ jobs:
           python3 -c "
           import sys
           from huggingface_hub import HfApi
-          HfApi().repo_info(repo_id=sys.argv[1], repo_type='dataset')
-          print(f'Success: Repo {sys.argv[1]} exists.')
+          try:
+              api = HfApi()
+              api.repo_info(repo_id=sys.argv[1], repo_type='dataset')
+              print(f'Success: Repo {sys.argv[1]} exists.')
+          except Exception as e:
+              print('HF validation failed:', e)
+              sys.exit(1)
           " "${{ inputs.hf_repo }}"
 
       - name: Download artifact name file
@@ -187,7 +192,7 @@ jobs:
 
       - name: Upload to Hugging Face
         env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+          HF_OIDC_RESOURCE: datasets/${{ inputs.hf_repo }}
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
           hf upload ${{ inputs.hf_repo }} \

.github/workflows/download-hf-model-chunks/action.yml

@@ -46,13 +46,6 @@ 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

.github/workflows/sunnypilot-build-model.yaml

@@ -188,7 +188,7 @@ jobs:
           if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
             echo "CHESTNUT build"
             export CHESTNUT=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_OCCUPANCY_OPT=1"
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"

.github/workflows/sunnypilot-build-prebuilt.yaml

@@ -216,9 +216,6 @@ 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: ${{ steps.resolve.outputs.onnx_sha256 }}
     env:
@@ -231,10 +228,8 @@ jobs:
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
 
-          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)
+          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)
           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=${REF}" --jq '.sha')
@@ -243,7 +238,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -257,35 +252,18 @@ jobs:
 
           echo "No matching model on HF — dispatching build"
           gh workflow run build-default-models.yaml --ref "$REF" -f target=big
-          sleep 10
 
-          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..."
+          echo "Polling HF for big model availability..."
           for i in $(seq 1 90); do
             sleep 30
-            STATUS=$(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
+            if check_defaults; then
+              echo "Big model available on HF after $((i * 30))s"
+              exit 0
             fi
+            echo "Poll $i/90: not yet available"
           done
 
-          echo "::error::Build run did not complete within 45 minutes"
+          echo "::error::Big model not available on HF after 45 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -299,9 +277,6 @@ 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: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
     env:
@@ -314,10 +289,8 @@ jobs:
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
 
-          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)
+          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)
           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=${REF}" --jq '.sha')
@@ -326,7 +299,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -340,35 +313,18 @@ jobs:
 
           echo "No matching model on HF — dispatching build"
           gh workflow run build-default-models.yaml --ref "$REF" -f target=small
-          sleep 10
 
-          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..."
+          echo "Polling HF for model availability..."
           for i in $(seq 1 60); do
             sleep 30
-            STATUS=$(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
+            if check_defaults; then
+              echo "Model available on HF after $((i * 30))s"
+              exit 0
             fi
+            echo "Poll $i/60: not yet available"
           done
 
-          echo "::error::Small model build did not complete within 30 minutes"
+          echo "::error::Small driving model not available on HF after 30 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -382,9 +338,6 @@ 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: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
     env:
@@ -397,10 +350,8 @@ jobs:
         run: |
           REF="${{ github.head_ref || github.ref_name }}"
 
-          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)
+          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)
           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=${REF}" --jq '.sha')
@@ -409,7 +360,7 @@ jobs:
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
           check_defaults() {
-            DEFAULTS=$(curl -fsSL "${JSON_URL}?t=$(date +%s)" 2>/dev/null) || return 1
+            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
             TINYGRAD_MATCH=$(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)
@@ -423,35 +374,18 @@ jobs:
 
           echo "No matching DM model on HF — dispatching build"
           gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
-          sleep 10
 
-          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..."
+          echo "Polling HF for DM model availability..."
           for i in $(seq 1 60); do
             sleep 30
-            STATUS=$(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
+            if check_defaults; then
+              echo "DM model available on HF after $((i * 30))s"
+              exit 0
             fi
+            echo "Poll $i/60: not yet available"
           done
 
-          echo "::error::DM model build did not complete within 30 minutes"
+          echo "::error::DM model not available on HF after 30 minutes"
           exit 1
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

docs/ford_virtual_angle_experiment.md

@@ -0,0 +1,184 @@
+# Ford C2-free path tracking
+
+Hypothesis `curvature-c0-v3` uses the planner's selected desired curvature for
+C0 centering and turn demand, while retaining v2's full model-path heading for
+C1. C2 and C3 remain zero. The historical `ford_virtual_angle.py` filename,
+controller class and setting key remain for compatibility; this is not an
+angle servo or an identified C0/C1-to-wheel conversion.
+
+## Evidence and reason for the change
+
+Route7a ran the weak v1 controller in `7d558c065` with the experiment selected.
+Before the steeringPressed flag in its first two turns, median measured to
+requested curvature ratios were 0.120 and 0.263. Median absolute C1 in the
+first window was only 0.0025 rad, versus roughly 0.08–0.25 rad in earlier
+large-maneuver examples. These were continuous mode-2 requests with full
+reported EPS capability, no reported limit or denial, matching wire commands
+and zero stall events. Full reported capability does not establish unlimited
+physical steering authority, and an unset steeringPressed flag does not rule
+out subthreshold driver torque.
+
+The v2 controller in `10e354d66` restored spatial turn demand, but its C0 came
+from lateral displacement in a short model-path preview. A real model path
+can start at the truck and gradually move toward center. That representation
+may contain little short-preview displacement even while the planner requests
+a correction. A synthetic path translated sideways did not reproduce this
+case, so that original centering test was insufficient.
+
+The supplied route7c was driven with the experiment **off** and is a default
+controller baseline. The user's subsequent enabled-v2 report describes better
+turns but drifting without centering; enabled logs are still pending. This
+supports investigating the reference choice, but does not identify a measured
+PSCM failure mechanism or validate this replacement on the vehicle.
+
+## C0: planner curvature expressed as lateral demand
+
+controlsd supplies its existing bounded `desired_curvature`: the
+`lateralManeuverPlan` request when that service is valid, otherwise the
+`modelV2.action` request, after the existing curvature limiter. This action
+already includes the planner's centering intent. v3 uses it directly rather
+than inferring centering from the near model path or building another
+lane-centering loop. The selected action already receives the upstream delay
+treatment; C0 does not add another response advance. C1 retains its existing
+model-geometry response alignment.
+
+The controller constructs C0 in its existing command coordinates as:
+
+```text
+L = max(8 m, speed × 1.0 s)
+C0_target = clip(0.5 × desired_curvature × L², -5.11 m, +5.11 m)
+```
+
+This is a small-angle arc-displacement construction, not a prediction of
+wheel response or a measurement of the truck's actual lane displacement.
+For example, desired curvature 0.02/m produces 0.64 m at the 8 m floor and
+1.00 m at 10 m. Curvature 0.04/m produces 1.28 m and 2.00 m respectively.
+The spatial floor prevents the preview from collapsing during slow maneuvers;
+it cannot restore turn intent absent from the desired-curvature reference.
+The formula is bounded rather than extrapolated into an unlimited request.
+
+The input is **absolute desired curvature**, not desired minus measured
+curvature. Matching the requested curvature therefore does not erase the
+turn command. This replaces v2's C0; it is not added to the previous lateral
+displacement calculation, and C1 overflow is not transferred into C0.
+
+## C1: retain full model-path heading
+
+C1 continues to use the full model heading at `max(7 m, speed × 1.0 s)`
+beyond a short predicted response interval, limited by available path
+coverage. The model's heading is expressed relative to the predicted ego
+heading, then bounded to ±0.5 rad. It is not reduced to a small curvature
+error term when the truck catches up with the turn.
+
+The retained model geometry is moved into the current vehicle frame every
+control cycle using traveled distance and measured CAN yaw rate. New model
+geometry is aligned to the same frame and arc station before its difference
+from the retained path is filtered. Measured ego motion is accounted for
+immediately; only model innovation is filtered. Publication age is compensated
+with the current speed and yaw rate. This is a planar motion approximation,
+not a PSCM model or reconstruction of camera latency.
+
+| Parameter | Value |
+|---|---:|
+| C0 preview | max(8 m, speed × 1.0 s) |
+| C1 preview | max(7 m, speed × 1.0 s), limited by model coverage |
+| Model-innovation filter time constant for C1 | 0.30 s |
+| C1 response interval | CarParams.steerActuatorDelay; 0.20 s in these routes |
+| Independent host C0 / C1 slew limits | 4 m/s / 0.5 rad/s |
+| C0 / C1 request bounds | ±5.11 m / ±0.5 rad |
+
+Each channel has its own slew limit, so a heading transition does not consume
+C0's centering rate allowance. Fractional wire-resolution increments accumulate
+internally; published values mirror the Float32 and sign-reversed Ford CAN
+packing. C0 does not pass through the model-innovation filter.
+
+Preview floors and time horizons are **effective gains**: they change command
+size and aggressiveness. Filtering and slew limits also change the response.
+This design minimizes separate tuning mechanisms, but it is not gain-free.
+There is no fitted EPS gain, external wheel-error PID, learned channel gain,
+integrator or stall latch. Geometry alone does not establish adequate PSCM
+authority or stability, particularly when C0 and C1 come from different
+planner representations.
+
+## Input validity, selection and rollback
+
+C0 requires a fresh timestamp from the selected action service; C1 separately
+requires a fresh valid model. controlsd checks both services plus carState,
+vehicleParameters and CAN validity. Model, action and measurement age must
+each be within the controller's 150 ms freshness window. The selected action
+source can switch between model and maneuver plan using the same validity
+choice as the existing desired-curvature calculation.
+
+Invalid services or geometry, nonfinite inputs, stale inputs, backward model
+or measurement timestamps, control intervals outside 2–100 ms, speed outside
+0.3–55 m/s, or yaw-rate magnitude above 3 rad/s invalidate the request and
+clear state. controlsd then clears latActive, producing inactive Ford lateral
+mode. Reengagement starts from zero slew state.
+
+While lateral control remains authorized, driver input leaves the path
+request present, as in the default allocator; the PSCM retains its existing
+driver arbitration. The diagnostic driver_override label records the flag,
+not a promise that lateral mode has been disabled.
+
+Vehicle → Ford → **C2-Free Path Tracking (Experimental)** uses the existing
+`FordVirtualAngleController` setting. An already-enabled setting selects the
+replacement after updating and restarting controlsd. New settings remain
+default off. Toggle changes require an offroad-to-onroad cycle.
+
+Selection remains limited to CAN FD, `FORD_F_150_LIGHTNING_MK1`, and EPS
+firmware `RL38-14D003-AA`. It takes priority over PSCM Coefficient Observer on
+that combination. Turning it off and cycling offroad/onroad restores the
+previous controller selection. The obsolete `FordSharedPathController`
+switch remains removed. No live device setting is changed by this commit.
+
+## Verification and remaining uncertainty
+
+Regression checks cover action-driven C0 even when the near model path has
+little centering displacement, command growth for slow turns, sustained
+steady-turn demand, retained C1 heading, motion-frame alignment, filtering,
+independent slew limits, bounds, fault resets and actual CAN packing. The
+controlsd tests exercise both action-source choices and independently stale
+or invalid model/action services. Selection, logging and settings-schema
+checks remain included.
+
+Recorded-route fixtures include earlier large left/right maneuvers, the
+oscillating experiment and v1's weak turns. Replaying these frozen inputs
+checks the commands the new code would request. It does **not** replay the
+vehicle's response to those changed commands. Historical v2 command-envelope
+tables and replay outputs are evidence for that version only, not new v3
+vehicle validation. Driver intervention also limits physical interpretation
+of several large-maneuver windows.
+
+Route7c exposes a material disagreement between action curvature and the
+far model geometry during a large left turn. These active, unpressed command
+windows use signed median values:
+
+| Route7c window | Speed range | Desired curvature | Recorded C0 / C1 | v3 replay C0 / C1 |
+|---|---:|---:|---:|---:|
+| 482–485 s, initial near-stop turn | 0.485–3.439 m/s | +0.00174/m | −4.123 m / −0.5 rad | +0.06 m / −0.5 rad |
+| 489–492 s, later in the turn | 2.213–4.777 m/s | −0.05821/m | −3.222 m / −0.5 rad | −1.86 m / −0.5 rad |
+
+The raw model action matches desired curvature in this case. The reference
+itself therefore disagrees with the far-path turn geometry; the curvature
+limiter and preview-distance collapse do not explain it. C1 retains the
+large turn heading, but the adequacy of the combined request is unknown.
+Earlier route77 large-maneuver command checks pass; that does not establish
+that v3 preserves every large maneuver, particularly this initial turn.
+
+**v3 has not been validated on the vehicle.** Neither geometric examples nor
+command replay prove centering, damping, physical steering authority or
+closed-loop stability. The next enabled logs need to show the selected action,
+C0/C1 requests, actual motion and interventions. They must establish whether
+centering improves without losing the recovered turn response.
+
+Startup logs retain the controller class name. The 5 Hz event
+`Ford C2-free path tracking` identifies hypothesis `curvature-c0-v3` and
+records the selected action service/time, input ages, desired/measured
+curvature, CAN yaw, C0/C1 targets, preview horizons and actual commands.
+
+Reproduce focused checks from the repository environment:
+
+```sh
+python -m pytest -q openpilot/selfdrive/controls/tests/test_ford_curvature_c0.py openpilot/selfdrive/controls/tests/test_ford_path_reference.py openpilot/selfdrive/controls/tests/test_ford_virtual_angle.py openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py openpilot/selfdrive/controls/tests/test_ford_path.py openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py
+python openpilot/sunnypilot/sunnylink/tools/compile_settings_ui.py --check
+```

launch_env.sh

@@ -16,7 +16,7 @@ export VECLIB_MAXIMUM_THREADS=1
 export QCOM_PRIORITY=12
 
 if [ -z "$AGNOS_VERSION" ]; then
-  export AGNOS_VERSION="19.7"
+  export AGNOS_VERSION="19.6"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

openpilot/cereal/custom.capnp

@@ -383,6 +383,7 @@ struct CarControlSP @0xa5cd762cd951a455 {
   leadOne @2 :LeadData;
   leadTwo @3 :LeadData;
   intelligentCruiseButtonManagement @4 :IntelligentCruiseButtonManagement;
+  fordLateralPath @5 :FordLateralPath;
 
   struct Param {
     key @0 :Text;
@@ -403,6 +404,14 @@ 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;
@@ -470,7 +479,30 @@ struct ModelDataV2SP @0xa1680744031fdb2d {
   }
 }
 
-struct CustomReserved10 @0xcb9fd56c7057593a {
+struct AssistedDrivingMilestoneState @0xcb9fd56c7057593a {
+  enabled @0 :Bool;
+  madsDistanceMeters @1 :Float64;
+  fullAssistDistanceMeters @2 :Float64;
+  event @3 :Event;
+
+  struct Event {
+    id @0 :UInt64;
+    category @1 :Category;
+    distanceMeters @2 :Float64;
+    previousDistanceMeters @3 :Float64;
+    unit @4 :Unit;
+  }
+
+  enum Category {
+    none @0;
+    mads @1;
+    fullAssist @2;
+  }
+
+  enum Unit {
+    imperial @0;
+    metric @1;
+  }
 }
 
 struct CustomReserved11 @0xc2243c65e0340384 {

openpilot/cereal/log.capnp

@@ -725,7 +725,6 @@ struct ChestnutState {
   pcieLtssm @7 :UInt8;
   supplyVoltage @8 :UInt16;  # mV
   supplyCurrent @9 :Int16;  # mA
-  supplyFault @10 :Bool;
 }
 
 struct RadarState @0x9a185389d6fdd05f {
@@ -1005,7 +1004,6 @@ struct DrivingModelData {
   frameIdExtra @1 :UInt32;
   frameDropPerc @6 :Float32;
   modelExecutionTime @7 :Float32;
-  big @8 :Bool;
 
   action @2 :ModelDataV2.Action;
 
@@ -2642,7 +2640,7 @@ struct Event {
     carStateSP @114 :Custom.CarStateSP;
     liveMapDataSP @115 :Custom.LiveMapDataSP;
     modelDataV2SP @116 :Custom.ModelDataV2SP;
-    customReserved10 @136 :Custom.CustomReserved10;
+    assistedDrivingMilestoneState @136 :Custom.AssistedDrivingMilestoneState;
     customReserved11 @137 :Custom.CustomReserved11;
     customReserved12 @138 :Custom.CustomReserved12;
     customReserved13 @139 :Custom.CustomReserved13;

openpilot/cereal/services.py

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

openpilot/common/hardware/comma/agnos.json

@@ -56,29 +56,29 @@
   },
   {
     "name": "boot",
-    "url": "https://commadist.azureedge.net/agnosupdate/boot-6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d.img.xz",
-    "hash": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
-    "hash_raw": "6ecf6f987cd11968104abcccabbe268485d329cdb73012dfd3c381a6b8deb27d",
+    "url": "https://commadist.azureedge.net/agnosupdate/boot-b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd.img.xz",
+    "hash": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
+    "hash_raw": "b30f5eef65ec3878f3aa3dcaf2cc95c09e2c1e661cd3a38e94da37dee76f68bd",
     "size": 46897152,
     "sparse": false,
     "full_check": true,
     "has_ab": true,
-    "ondevice_hash": "d12e1e5b9455b62a1464558716493b33e470d7a7e88da1c4105a3b21d0961808"
+    "ondevice_hash": "6650e4c46df99ae6dfd6ee895a34b8a2a3cc490a8ce18e16cc3c451c3f822b6e"
   },
   {
     "name": "system",
-    "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img.xz",
-    "hash": "74ffc9c551e1f29cda897ace8a69080fe644f8039977c6885f2b48362e39b744",
-    "hash_raw": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
+    "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img.xz",
+    "hash": "b134fd04e9da27fa1d359ea0f2742c216fa21a08b5c47e9be22ab3b0563d9b9b",
+    "hash_raw": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
     "size": 4718592000,
     "sparse": true,
     "full_check": false,
     "has_ab": true,
-    "ondevice_hash": "6a992680183685eea9db99d915219a37935f45989330d9b619e880450257f448",
+    "ondevice_hash": "91242772af771ae96fe2eebc105f2b80a7e1dbaaf6003c2574b62d51b806f468",
     "alt": {
-      "hash": "3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f",
-      "url": "https://commadist.azureedge.net/agnosupdate/system-3c271e2b3d20d2f0a8bf6555a1319f3efb12845490967d6151195174a01e912f.img",
+      "hash": "5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3",
+      "url": "https://commadist.azureedge.net/agnosupdate/system-5b6ce7965904a157fd3a134ccfcb854f9ca5c1cc2a26b7cb80a4fa4e1cc4aaa3.img",
       "size": 4718592000
     }
   }
-]
+]

openpilot/common/hardware/comma/modem.py

@@ -5,7 +5,6 @@ import logging
 import os
 import select
 import signal
-import string
 import struct
 import subprocess
 import tempfile
@@ -355,7 +354,7 @@ class Modem:
       imei = ""
 
     iccid = (self._atv("AT+QCCID", "+QCCID:") or "").rstrip("F")
-    if not all(c in string.hexdigits for c in iccid):
+    if not iccid.isdigit():
       iccid = ""
 
     imsi = first_line("AT+CIMI")

openpilot/common/hardware/usb.py

@@ -4,17 +4,11 @@ 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))
@@ -87,7 +81,7 @@ def set_usb_state(device_state, devices: list[dict]) -> None:
     entry.linkErrorCount = device["linkErrorCount"]
     entry.usb3Lane = device.get("usb3Lane", "unknown")
 
-    if is_chestnut_usb_id(entry.vendorId, entry.productId):
+    if (entry.vendorId, entry.productId) in CHESTNUT_USB_IDS:
       chestnut_present = True
 
   device_state.chestnutPresent = chestnut_present

openpilot/common/params.cc

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

openpilot/common/params.h

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

openpilot/common/params.py

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

openpilot/common/params_c.cc

@@ -133,6 +133,12 @@ int params_put_bool(ParamsHandle *handle, const char *key, bool value, bool bloc
   });
 }
 
+void params_flush(ParamsHandle *handle) noexcept {
+  translate_exceptions([&]() {
+    handle->params.flushNonBlockingWrites();
+  });
+}
+
 int params_remove(ParamsHandle *handle, const char *key) noexcept {
   return translate_exceptions(-1, [&]() {
     return handle->params.remove(key);

openpilot/common/params_keys.h

@@ -92,12 +92,6 @@ 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}},
@@ -138,11 +132,12 @@ 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
@@ -163,6 +158,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DevUIInfo", {PERSISTENT | BACKUP, INT, "0"}},
     {"EnableCopyparty", {PERSISTENT | BACKUP, BOOL}},
     {"EnableGithubRunner", {PERSISTENT | BACKUP, BOOL}},
+    {"FullAssistDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
     {"GreenLightAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"GithubRunnerSufficientVoltage", {CLEAR_ON_MANAGER_START , BOOL}},
     {"HasAcceptedTermsSP", {PERSISTENT, STRING, "0"}},
@@ -172,7 +168,9 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"IsDevelopmentBranch", {CLEAR_ON_MANAGER_START, BOOL}},
     {"IsReleaseSpBranch", {CLEAR_ON_MANAGER_START, BOOL}},
     {"LastGPSPositionLLK", {PERSISTENT, STRING}},
+    {"LastDriveAssistedDrivingSummary", {PERSISTENT, JSON, "{}"}},
     {"LeadDepartAlert", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"MadsDrivenDistanceMeters", {PERSISTENT, FLOAT, "0.0"}},
     {"MaxTimeOffroad", {PERSISTENT | BACKUP, INT, "1800"}},
     {"ModelRunnerTypeCache", {CLEAR_ON_ONROAD_TRANSITION, INT}},
     {"OffroadMode", {CLEAR_ON_MANAGER_START, BOOL}},
@@ -232,6 +230,8 @@ 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"}},

openpilot/common/prefix.h

@@ -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 -rf %s", real_path.c_str()));
+      util::check_system(util::string_format("rm %s -rf", real_path.c_str()));
       unlink(param_path.c_str());
     }
     if (getenv("COMMA_CACHE") == nullptr) {
-      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::download_cache_root().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()));
+    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()));
     unsetenv("OPENPILOT_PREFIX");
   }
 

openpilot/common/tests/test_params.py

@@ -106,6 +106,13 @@ class TestParams(OpenpilotTestCase):
     assert q.get("CarParams") is None
     assert q.get("CarParams", True) == b"1"
 
+  def test_flush_non_blocking_writes(self):
+    self.params.put("DongleId", "first")
+    self.params.put("DongleId", "last")
+    self.params.flush()
+
+    assert self.params.get("DongleId") == "last"
+
   def test_params_all_keys(self):
     keys = Params().all_keys()
 

openpilot/selfdrive/assets/icons_mici/usb.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:07bda2fe5d6be0b2854044053c384fe002e96406da119863a443b9344258b500
-size 1544

openpilot/selfdrive/car/helpers.py

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

openpilot/selfdrive/controls/controlsd.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 import math
+import time
 from numbers import Number
 
 from openpilot.cereal import log
@@ -11,8 +12,11 @@ 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, 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
@@ -52,6 +56,15 @@ 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
@@ -155,6 +168,35 @@ 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'
+        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,
+        )
+        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)

openpilot/selfdrive/controls/lib/ford_path.py

@@ -0,0 +1,348 @@
+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)

openpilot/selfdrive/controls/lib/ford_virtual_angle.py

@@ -0,0 +1,173 @@
+"""C2-free action offset and spatial heading 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 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 FordFlags
+
+
+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
+
+
+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 planned curvature as C0 and retain model heading as C1.
+
+  Measured CAN yaw rate is used only to move the reference between ego frames
+  and align its preview with the response interval. No 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.reset()
+
+  def reset(self):
+    self.reference.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-v3', 'command': (0., 0., 0., 0.)}
+
+  def update(self, model, desired_curvature, *, yaw_rate, speed, now, measurement_time, model_time, reference_time,
+             active, valid=True, steering_pressed=False):
+    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 = min(max(speed * self.tuning.heading_time, self.tuning.heading_horizon), max(path[0][-1] - advance, 0.0))
+    ego = _predicted_pose(advance, current_curvature, 0.)
+    _, heading = _relative_pose(advance + 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))
+    target_heading = float(np.clip(heading, -.5, .5))
+    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 steering_pressed else 'active', 'hypothesis': 'curvature-c0-v3',
+                        'desired_curvature': desired_curvature, 'offset_target': target_offset, 'heading_target': target_heading,
+                        '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 source route analysis covers only this vehicle/firmware.
+  compatible = CP.brand == 'ford' and CP.flags & FordFlags.CANFD and CP.carFingerprint == 'FORD_F_150_LIGHTNING_MK1'
+  firmware = compatible and any(str(fw.ecu) == 'eps' and bytes(fw.fwVersion).rstrip(b'\0') == b'RL38-14D003-AA' for fw in CP.carFw)
+  if enabled and firmware:
+    return FordVirtualAngleController(CP.steerActuatorDelay)
+  return previous_controller

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

@@ -0,0 +1,229 @@
+{
+  "description": "Curvature-driven C0 and full-heading C1 command regression; does not predict counterfactual wheel response. Contains geometry and control signals only, no GPS.",
+  "fixture_sha256": "12782ac1b0d0637945f729a46ad03af16cd58188872b6a65f104e32c4db70e9b",
+  "episodes": [
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+        814.0
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+      "route": "84865544361f55cb_00000077--4b55791ce6",
+      "range_seconds": [
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+        872.0
+      ],
+      "evidence_seconds": [
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+        871.0
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+      "samples": 547
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+    {
+      "name": "left_very_large",
+      "route": "84865544361f55cb_00000077--4b55791ce6",
+      "range_seconds": [
+        880.0,
+        884.0
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+      "evidence_seconds": [
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+        883.32
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+      "route": "84865544361f55cb_00000077--4b55791ce6",
+      "range_seconds": [
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+        970.0
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+      "range_seconds": [
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+        37.0
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+      "route": "84865544361f55cb_0000007a--5a95fc717e",
+      "range_seconds": [
+        90.5,
+        95.2
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+      "evidence_seconds": [
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+        95.08
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+    {
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+      "route": "84865544361f55cb_0000007a--5a95fc717e",
+      "range_seconds": [
+        119.5,
+        125.3
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+    "84865544361f55cb_00000078--349f5b8695": [
+      {
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+    "84865544361f55cb_0000007a--5a95fc717e": [
+      {
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+      },
+      {
+        "name": "84865544361f55cb_0000007a--5a95fc717e--1--rlog.zst",
+        "bytes": 12567837,
+        "sha256": "ab9eb05c5805e286a6ec639bbbbc1cf086bfcf1b440801ad000713db95dfa7fc"
+      },
+      {
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+        "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."
+}

openpilot/selfdrive/controls/tests/test_ford_controlsd_logging.py

@@ -0,0 +1,149 @@
+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.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
+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['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.assertTrue(all(key in record for key in ('offset_target', 'heading_target', '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}
+      logMonoTime = {'carState': 995_000_000, 'modelV2': 980_000_000, 'lateralManeuverPlan': 990_000_000}
+      failed_checks = set()
+
+      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)
+      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)}
+      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.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)
+
+
+if __name__ == '__main__':
+  unittest.main()

openpilot/selfdrive/controls/tests/test_ford_curvature_c0.py

@@ -0,0 +1,83 @@
+"""Action-to-C0 regressions; these do not simulate PSCM/vehicle response."""
+from dataclasses import replace
+import math
+import unittest
+
+from openpilot.selfdrive.controls.lib.ford_path import FordPath
+from openpilot.selfdrive.controls.lib.ford_virtual_angle import FordVirtualAngleController, PathTuning
+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, 0., delta=.00025)
+      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_c0_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.assertGreater(sign * path.path_angle, .4)
+
+  def test_c1_reversal_cannot_delay_action_c0_release(self):
+    controller = FordVirtualAngleController(tuning=replace(PathTuning(), filter_time=0.))
+    for i in range(200):
+      path = step(controller, i * .01, .003125, circle(.12), speed=5.)
+    self.assertAlmostEqual(path.path_offset, .1)
+    self.assertAlmostEqual(path.path_angle, .5)
+    for i in range(200, 203):
+      path = step(controller, i * .01, 0., circle(-.12), speed=5.)
+    self.assertAlmostEqual(path.path_offset, 0., delta=.0051)
+    self.assertGreater(path.path_angle, .45)  # C1 is still in its own limited transition.
+
+  def test_c0_can_reverse_while_model_heading_still_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.assertGreater(path.path_angle, .2)
+
+  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()

openpilot/selfdrive/controls/tests/test_ford_path.py

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

openpilot/selfdrive/controls/tests/test_ford_path_reference.py

@@ -0,0 +1,194 @@
+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_without_losing_heading_demand(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)
+      values.append(path.path_angle)
+    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()

openpilot/selfdrive/controls/tests/test_ford_virtual_angle.py

@@ -0,0 +1,47 @@
+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_firmware_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'},
+                        {'carFw': []}, {'carFw': [SimpleNamespace(ecu='eps', fwVersion=b'ML3V')]}):
+        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_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()
+      self.assertIs(select_virtual_angle_controller(car_params(), params.get_bool('FordVirtualAngleController'), previous), previous)
+      params.put_bool('FordVirtualAngleController', True, block=True)
+      chosen = select_virtual_angle_controller(car_params(), params.get_bool('FordVirtualAngleController'), previous)
+      params.put_bool('FordVirtualAngleController', False, block=True)
+      self.assertIsInstance(chosen, FordVirtualAngleController)  # only selected at startup
+
+
+if __name__ == '__main__':
+  unittest.main()

openpilot/selfdrive/modeld/SConscript

@@ -10,6 +10,11 @@ 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()
@@ -19,22 +24,20 @@ 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):
-  # 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
+  return 1.2 * onnx_size  + 10 * 1024 * 1024  # 20% + 10MB is plenty
 
 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}
   },
@@ -42,7 +45,7 @@ tg_devices = { # which device to put jit inputs to at runtime
 
 CHESTNUT = chestnut_present()
 if CHESTNUT:
-  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'
+  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'
   # the USB+AMD GPU takes an exclusive flock; serialize all targets that touch it
   chestnut_lock = File("models/.chestnut.lock").abspath
 
@@ -73,9 +76,10 @@ 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
-    file_prefix, cmd_flags = ('big_', chestnut_tg_flags) if chestnut else ('', tg_flags)
+    # 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)
     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 '
@@ -103,7 +107,7 @@ 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(camera_res_args), Value(chunk_targets), chunker_file],
+      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
       actions,
     )
     if chestnut:
@@ -117,7 +121,7 @@ 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} '
@@ -139,4 +143,5 @@ def tg_compile(flags, model_name):
      Action(do_chunk, "  [CHUNK] $TARGET")],
   )
 
-tg_compile(tg_flags, 'dmonitoring_model')
+if not os.getenv('SKIP_TINYGRAD_COMPILE'):
+  tg_compile(tg_flags, 'dmonitoring_model')

openpilot/selfdrive/modeld/compile_modeld.py

@@ -37,12 +37,17 @@ from tinygrad.engine.jit import TinyJit
 
 
 NV12Frame = namedtuple("NV12Frame", ['width', 'height', 'stride', 'y_height', 'uv_height', 'size'])
-MODELD_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs']
+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')
 
 
-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 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 warp_perspective_tinygrad(src_flat, M_inv, dst_shape, src_shape, stride_pad, border_fill_val=None):
@@ -94,7 +99,7 @@ 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=Device.DEFAULT)
+    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)
     # 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):
@@ -113,43 +118,49 @@ 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, T-1, ...) e.g. (1, 24, 32, 512) with spatial features
-  feat_dim = math.prod(fb[2:])
+  fb = input_shapes['features_buffer']  # (1, 24, 512)
   # 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], feat_dim)}
+  shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
   return shapes, [math.prod(s) for s in shapes.values()]
 
 
-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])
+def make_input_queues(input_shapes, frame_skip, device):
+  input_queues, npy = make_warp_input_queues(input_shapes, frame_skip, device)
 
-  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:]}
+  fb = input_shapes['features_buffer']  # (1, 24, 512), past features only; the model appends the current frame's feature
+  dp = input_shapes['desire_pulse']  # (1, 25, 8)
+
+  shapes, sizes = get_policy_npy_shapes(input_shapes)
+  packed_npy_inputs = np.zeros(sum(sizes), dtype=np.float32)
   # views into the packed inputs, to be refilled at runtime
-  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(),
+  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(),
     '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_input, device='NPY').realize(),
-  }
-  return input_queues, npy, frame_views
+    'packed_npy_inputs': Tensor(packed_npy_inputs, device='NPY').realize(),
+  })
+  return input_queues, npy
 
 
 def shift_and_sample(buf, new_val, sample_fn):
@@ -165,15 +176,13 @@ 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):
+def make_warp(nv12, model_w, model_h, frame_skip):
   frame_prepare = make_frame_prepare(nv12, model_w, model_h)
 
   def warp(tfm, big_tfm, frame, big_frame):
-    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)
+    tfm = tfm.to(WARP_DEV)
+    big_tfm = big_tfm.to(WARP_DEV)
+    Tensor.realize(tfm, big_tfm)
 
     warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
     warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
@@ -186,10 +195,10 @@ 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)
@@ -202,50 +211,33 @@ def make_run_policy(model_runner, model_metadata, frame_skip):
     inputs = {
       'img': img,
       'big_img': big_img,
-      'features_buffer': feat_buf.reshape(model_metadata['input_shapes']['features_buffer']),
+      'features_buffer': feat_buf,
       '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 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
-
-  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")
-
+def compile_jit(jit, make_random_inputs, input_keys, make_queues):
   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)
+  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)
+
+    testing = test_val is not None or test_buffers is not None
+    n_runs = 1 if testing else 3
 
     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})
+      outs = fn(**{k: input_queues[k] for k in input_keys}, **random_inputs)
       mt = time.perf_counter()
       Device.default.synchronize()
       et = time.perf_counter()
@@ -264,15 +256,14 @@ def compile_jit(jit, input_keys, make_queues, benchmark_runs):
     return val, buffers
 
   print('capture + replay')
-  test_val, test_buffers = random_inputs_run(jit, SEED, 3)
-  print(f'pickle round trip ({benchmark_runs} runs per seed)')
+  test_val, test_buffers = random_inputs_run(jit, SEED)
+  print('pickle round trip')
   with tempfile.TemporaryFile(dir=".") as f:
     dump_oob(jit, f)
     f.seek(0)
-    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.
+    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)
   return jit
 
 
@@ -301,31 +292,27 @@ 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),
-    'input_devices': {'model': Device.DEFAULT},
-    'run_model': {},
-  }
+  out = {'metadata': make_metadata_dict(model_path)}
 
-  run_policy = make_run_policy(model_runner, out['metadata'], args.frame_skip)
+  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)
 
   for cam_w, cam_h in args.camera_resolutions:
     nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
-    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)
+    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)
 
   with open(args.output, "wb") as f:
     dump_oob(out, f)

openpilot/selfdrive/modeld/fill_model_msg.py

@@ -64,7 +64,6 @@ 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

openpilot/selfdrive/modeld/helpers.py

@@ -7,12 +7,10 @@ import tempfile
 from pathlib import Path
 
 from openpilot.common.file_chunker import get_manifest_path
-from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, USB_DEVICES_PATH, is_chestnut_usb_id
+from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_USB_IDS, USB_DEVICES_PATH
 
 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):
@@ -52,7 +50,7 @@ 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 is_chestnut_usb_id(*usb_id) and product == CHESTNUT_USB_PRODUCT:
+      if usb_id in CHESTNUT_USB_IDS and product == f"custom {CHESTNUT_FW_VERSION}-CLEAN":
         return True
     except Exception:
       pass
@@ -60,7 +58,3 @@ 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

openpilot/selfdrive/modeld/modeld.py

@@ -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, nv12_copy_size, MODELD_INPUTS
+from openpilot.selfdrive.modeld.compile_modeld import make_input_queues, WARP_INPUTS, POLICY_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, chestnut_ready, modeld_pkl_path, load_oob
+from openpilot.selfdrive.modeld.helpers import chestnut_present, chestnut_compiled, modeld_pkl_path, get_tg_input_devices, 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
@@ -83,37 +83,6 @@ 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:
@@ -149,15 +118,13 @@ 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:
-        state.pcieLtssm = Device["AMD"].iface.pci_dev.usb.read(0xB450, 1)[0]
+        # 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
       except Exception:
         pass
 
@@ -180,9 +147,9 @@ 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]
@@ -192,11 +159,13 @@ class ModelState(ModelStateBase):
     self.chestnut = chestnut
 
     self.frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ
-    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.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.parser = Parser()
-    self.run_model = jits['run_model'][(cam_w,cam_h)]
+    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)]
 
   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()}
@@ -204,8 +173,14 @@ 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, buf in bufs.items():
-      np.copyto(self.frame_views[key], np.frombuffer(buf.data, dtype=np.uint8, count=self.frame_copy_size))
+    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]
 
     # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
     inputs['desire_pulse'][0] = 0
@@ -216,7 +191,11 @@ class ModelState(ModelStateBase):
     self.npy['tfm'][:,:] = transforms['img'][:,:]
     self.npy['big_tfm'][:,:] = transforms['big_img'][:,:]
 
-    outs, = self.run_model(**{k: self.input_queues[k] for k in MODELD_INPUTS})
+    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
+    )
     if after_enqueue is not None:
       after_enqueue()
     model_output = outs.numpy()[0]
@@ -230,37 +209,25 @@ class ModelState(ModelStateBase):
     return outputs_dict
 
   def warmup(self) -> None:
-    dummy_frames = {k: np.zeros(self.frame_copy_size, dtype=np.uint8) for k in self.vision_input_names}
+    dummy_frames = {k: np.zeros(self.frame_buf_params[k][3], 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, self.frame_views = make_input_queues(
-      self.input_shapes, self.frame_skip, device=self.model_device, frame_copy_size=self.frame_copy_size)
+    self.input_queues, self.npy = make_input_queues(self.input_shapes, self.frame_skip, device=self.QUEUE_DEV)
     self.prev_desire[:] = 0
+    self.full_frames.clear()
+    self._blob_cache.clear()
 
 
 def main(demo=False):
   cloudlog.warning("modeld init")
 
-  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)
+  CHESTNUT = chestnut_present() and chestnut_compiled()
   if CHESTNUT:
     os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
   params = Params()
   params.put_bool("ChestnutLoading", CHESTNUT)
-  if chestnut_available and not CHESTNUT:
-    params.put_bool("ChestnutActive", False)
-  else:
-    params.remove("ChestnutActive")
+  params.remove("ChestnutActive")
 
   config_realtime_process(7, 54)
 
@@ -304,11 +271,7 @@ 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:
@@ -442,7 +405,6 @@ 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
@@ -469,11 +431,12 @@ 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
-      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)
+      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)
       mdv2sp_send.modelDataV2SP.laneTurnDirection = DH.lane_turn_direction
 
       fill_driving_model_data(drivingdata_send, modelv2_send)

openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1791d5940b2c048d0639813426dd2cf1d6f2a6727ed51e17c8bcea8bbe754123
-size 765950064
+oid sha256:a501760a9d1d5fef0eab2b8c5d122d06124fc26dc8e0782e0aa94b82a208f0ff
+size 1757355221

openpilot/selfdrive/pandad/pandad.cc

@@ -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.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.setIgnitionLine(health.ignition_line_pkt);
+  ps.setIgnitionCan(health.ignition_can_pkt);
+  ps.setControlsAllowed(health.controls_allowed_pkt);
   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((health.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U);
-  ps.setHeartbeatLost((health.flags_pkt & HEALTH_FLAG_HEARTBEAT_LOST) != 0U);
+  ps.setPowerSaveEnabled((bool)(health.power_save_enabled_pkt));
+  ps.setHeartbeatLost((bool)(health.heartbeat_lost_pkt));
   ps.setAlternativeExperience(health.alternative_experience_pkt);
   ps.setHarnessStatus(cereal::PandaState::HarnessStatus(health.car_harness_status_pkt));
-  ps.setInterruptLoad(health.interrupt_load_pkt / 255.0f);
+  ps.setInterruptLoad(health.interrupt_load_pkt);
   ps.setFanPower(health.fan_power);
-  ps.setSafetyRxChecksInvalid((health.flags_pkt & HEALTH_FLAG_SAFETY_RX_CHECKS_INVALID) != 0U);
+  ps.setSafetyRxChecksInvalid((bool)(health.safety_rx_checks_invalid_pkt));
   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.flags_pkt |= HEALTH_FLAG_IGNITION_LINE;
+    health.ignition_line_pkt = 1;
   }
 
-  bool ignition_local = ((health.flags_pkt & (HEALTH_FLAG_IGNITION_LINE | HEALTH_FLAG_IGNITION_CAN)) != 0U) && !always_offroad;
+  bool ignition_local = ((health.ignition_line_pkt != 0) || (health.ignition_can_pkt != 0)) && !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.flags_pkt & HEALTH_FLAG_POWER_SAVE_ENABLED) != 0U) != power_save_desired) {
+  if (health.power_save_enabled_pkt != power_save_desired) {
     panda->set_power_saving(power_save_desired);
   }
 

openpilot/selfdrive/selfdrived/alerts_offroad.json

@@ -19,30 +19,6 @@
   },
   "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": {

openpilot/selfdrive/selfdrived/selfdrived.py

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

openpilot/selfdrive/test/process_replay/migration.py

@@ -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", "big", "action"]:
+    for field in ["frameId", "frameIdExtra", "frameDropPerc", "modelExecutionTime", "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))

openpilot/selfdrive/test/process_replay/model_replay.py

@@ -33,9 +33,9 @@ MODEL_REPLAY_BUCKET="model_replay_master"
 GITHUB = GithubUtils(API_TOKEN, DATA_TOKEN)
 
 EXEC_TIMINGS = [
-  # model, instant max, average max, chestnut average max
-  ("modelV2", 0.05, 0.03, 0.05),
-  ("driverStateV2", 0.05, 0.018, 0.018),
+  # model, instant max, average max
+  ("modelV2", 0.05, 0.028),
+  ("driverStateV2", 0.05, 0.018),
 ]
 
 def get_log_fn(test_route, ref="master"):
@@ -169,13 +169,11 @@ 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, chestnut_avg_max) in EXEC_TIMINGS:
-    avg_max = chestnut_avg_max if chestnut else avg_max
+  for (s, instant_max, avg_max) in EXEC_TIMINGS:
     ts = [getattr(m, s).modelExecutionTime for m in msgs if m.which() == s]
     # TODO some init can happen in first iteration
     ts = ts[1:]

openpilot/selfdrive/ui/body/layouts/onroad.py

@@ -1,7 +1,7 @@
 import time
 import pyray as rl
 
-from openpilot.system.ui.lib.application import gui_app, FontWeight, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.CENTER,
-                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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)

openpilot/selfdrive/ui/layouts/home.py

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
 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=TextAlignment.RIGHT)
+    gui_label(version_rect, self._version_text, 48, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
 
   def _render_home_content(self):
     self._render_left_column()

openpilot/selfdrive/ui/layouts/onboarding.py

@@ -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, TextAlignment, gui_app
+from openpilot.system.ui.lib.application import FontWeight, 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=TextAlignment.LEFT)
+    self._title = Label(tr("Welcome to sunnypilot"), font_size=90, font_weight=FontWeight.BOLD, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.LEFT)
+                       font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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)

openpilot/selfdrive/ui/layouts/settings/software.py

@@ -199,9 +199,6 @@ 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
 

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

@@ -1,5 +1,4 @@
 import datetime
-import math
 import time
 
 from openpilot.cereal import log
@@ -9,7 +8,7 @@ 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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
 from openpilot.selfdrive.ui.ui_state import ui_state, ChestnutState
 from openpilot.common.version import RELEASE_BRANCHES
 
@@ -70,8 +69,8 @@ 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=TextAlignment.CENTER,
-                alignment_vertical=TextAlignmentVertical.MIDDLE)
+                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
 
 
 class NetworkIcon(Widget):
@@ -140,9 +139,7 @@ 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))
@@ -153,15 +150,13 @@ 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("openpilot", font_size=96, font_weight=FontWeight.DISPLAY, max_width=480, wrap_text=False)
+    self._openpilot_label = UnifiedLabel("sunnypilot", 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)
@@ -252,20 +247,12 @@ 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._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._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._mic_icon.set_visible(ui_state.recording_audio)
     self._body_icon.set_visible(bool(ui_state.is_body))
 

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

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

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

@@ -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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.LEFT,
-                                     alignment_vertical=TextAlignmentVertical.TOP, line_height=0.95)
+                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP, line_height=0.95)
 
     self._body_label = UnifiedLabel(text="", font_size=28, font_weight=FontWeight.ROMAN, text_color=self.TEXT_COLOR,
-                                    alignment=TextAlignment.LEFT,
-                                    alignment_vertical=TextAlignmentVertical.BOTTOM, line_height=0.95)
+                                    alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+                                    alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignment.CENTER,
-                                     alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                     alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
 
     # Build initial alert list
     self._build_alerts()

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

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import FontWeight, gui_app
 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=TextAlignment.CENTER)
+                alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER)
       rl.end_scissor_mode()
       return
 

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

@@ -74,10 +74,6 @@ 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)
@@ -101,20 +97,15 @@ 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():
-      subprocess.run(f"pkill -{sig} -f {self.UPDATER_PROC}", shell=True)
+      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)
 
     threading.Thread(target=run, daemon=True).start()
 
@@ -193,7 +184,7 @@ class CheckUpdateButton(BigButton):
 
 class InstallUpdateButton(BigButton):
   def __init__(self):
-    super().__init__("install now", "", gui_app.texture("icons_mici/settings/device/reboot.png", 64, 70))
+    super().__init__("install update", "", 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):
@@ -241,9 +232,8 @@ class BranchSelectPage(NavScroller):
 
 
 class TargetBranchButton(BigButton):
-  def __init__(self, check_update_btn: CheckUpdateButton):
+  def __init__(self):
     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())
@@ -256,15 +246,12 @@ 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)
-    self._check_update_btn.check_for_update()
+    subprocess.run("pkill -SIGUSR1 -f openpilot.system.updated.updated", shell=True)
 
 
 class SoftwareLayoutMici(NavScroller):
@@ -278,11 +265,10 @@ 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(),
-      check_update_btn,
+      CheckUpdateButton(),
       InstallUpdateButton(),
-      TargetBranchButton(check_update_btn),
+      TargetBranchButton(),
       uninstall_openpilot_btn,
     ])

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

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

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

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 from openpilot.system.ui.widgets import Widget
 from openpilot.system.ui.widgets.label import UnifiedLabel
 
@@ -20,6 +20,7 @@ AlertSize = log.SelfdriveState.AlertSize
 AlertStatus = log.SelfdriveState.AlertStatus
 
 ALERT_MARGIN = 18
+ALERT_BACKGROUND_OPACITY = 0.90
 
 ALERT_FONT_SMALL = 66 - 50
 ALERT_FONT_BIG = 88 - 40
@@ -279,7 +280,7 @@ class AlertRenderer(Widget, SpeedLimitAlertRenderer):
   def _draw_background(self, alert: Alert) -> None:
     # draw top gradient for alert text at top
     color = ALERT_COLORS.get(alert.status, ALERT_COLORS[AlertStatus.normal])
-    color = rl.Color(color.r, color.g, color.b, int(255 * 0.90 * self._alpha_filter.x))
+    color = rl.Color(color.r, color.g, color.b, int(255 * ALERT_BACKGROUND_OPACITY * self._alpha_filter.x))
     translucent_color = rl.Color(color.r, color.g, color.b, int(0 * self._alpha_filter.x))
 
     small_alert_height = round(self._rect.height * 0.583) # 140px at mici height
@@ -333,7 +334,7 @@ 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(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
+    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.render(text_rect1)
 
     alert_text2 = alert.text2.lower()
@@ -365,5 +366,5 @@ 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(TextAlignment.LEFT if icon_side != 'left' else TextAlignment.RIGHT)
+      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.render(text_rect2)

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

@@ -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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import FontWeight, gui_app, MousePos, MouseEvent
 from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets import Widget
 from openpilot.common.filter_simple import BounceFilter
@@ -19,10 +19,15 @@ from openpilot.common.transformations.camera import DEVICE_CAMERAS, DeviceCamera
 from openpilot.common.transformations.orientation import rot_from_euler
 from enum import IntEnum
 
+MILESTONE_CELEBRATION_ENABLED = gui_app.sunnypilot_ui()
+
 if gui_app.sunnypilot_ui():
   from openpilot.selfdrive.ui.sunnypilot.mici.onroad.hud_renderer import HudRendererSP as HudRenderer
   from openpilot.selfdrive.ui.sunnypilot.ui_state import OnroadTimerStatus
 
+  if MILESTONE_CELEBRATION_ENABLED:
+    from openpilot.selfdrive.ui.sunnypilot.onroad.milestone_celebration import MilestoneCelebration
+
 OpState = log.SelfdriveState.OpenpilotState
 CALIBRATED = log.ExtrinsicsCalibration.Status.calibrated
 NARROW_ROAD_CAM = VisionStreamType.VISION_STREAM_NARROW_ROAD
@@ -156,10 +161,11 @@ class AugmentedRoadView(CameraView):
     self._alert_renderer = AlertRenderer()
     self._driver_state_renderer = DriverStateRenderer()
     self._confidence_ball = ConfidenceBall()
+    self._milestone_celebration = self._child(MilestoneCelebration()) if MILESTONE_CELEBRATION_ENABLED else None
     self._offroad_label = UnifiedLabel("start the car to\nuse sunnypilot", 54, FontWeight.DISPLAY,
                                        text_color=rl.Color(255, 255, 255, int(255 * 0.9)),
-                                       alignment=TextAlignment.CENTER,
-                                       alignment_vertical=TextAlignmentVertical.MIDDLE)
+                                       alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
 
     self._fade_texture = gui_app.texture("icons_mici/onroad/onroad_fade.png")
 
@@ -223,6 +229,12 @@ class AugmentedRoadView(CameraView):
 
     alert_to_render, not_animating_out = self._alert_renderer.will_render()
 
+    if self._milestone_celebration is not None:
+      if alert_to_render is not None:
+        self._milestone_celebration.cancel_for_alert()
+      else:
+        self._milestone_celebration.render(self._content_rect)
+
     # Hide DMoji when disengaged unless AlwaysOnDM is enabled
     should_draw_dmoji = (not self._hud_renderer.drawing_top_icons() and
                          (ui_state.status != UIStatus.DISENGAGED or ui_state.always_on_dm))
@@ -247,7 +259,6 @@ class AugmentedRoadView(CameraView):
     self._confidence_ball.render(self.rect)
 
     self._bookmark_icon.render(self.rect)
-
   def _switch_stream_if_needed(self, sm):
     if sm['selfdriveState'].experimentalMode and WIDE_CAM in self.available_streams:
       v_ego = sm['carState'].vEgo
@@ -355,10 +366,12 @@ class AugmentedRoadView(CameraView):
     return self._cached_matrix
 
   def show_event(self):
+    super().show_event()
     if gui_app.sunnypilot_ui():
       ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.RESUME)
 
   def hide_event(self):
+    super().hide_event()
     if gui_app.sunnypilot_ui():
       ui_state.reset_onroad_sleep_timer(OnroadTimerStatus.PAUSE)
 

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

@@ -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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.CENTER)
+                alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.RIGHT,
-              alignment_vertical=TextAlignmentVertical.TOP,
+              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
+              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
               color=rl.Color(0, 0, 0, 180))
     gui_label(rect, f"Awareness: {awareness_pct:.0f}%", font_size=44, font_weight=FontWeight.MEDIUM,
-              alignment=TextAlignment.RIGHT,
-              alignment_vertical=TextAlignmentVertical.TOP,
+              alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT,
+              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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 = TextAlignment.RIGHT if self.driver_state_renderer.is_rhd else TextAlignment.LEFT
+    alignment = rl.GuiTextAlignment.TEXT_ALIGN_RIGHT if self.driver_state_renderer.is_rhd else rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignmentVertical.BOTTOM,
+              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignmentVertical.BOTTOM,
+              alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_BOTTOM,
               color=rl.Color(255, 255, 255, int(255 * 0.9)))
 
   def _load_eye_textures(self):

openpilot/selfdrive/ui/mici/widgets/button.py

@@ -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, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
 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=TextAlignmentVertical.BOTTOM, scroll=scroll,
+                               text_color=LABEL_COLOR, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignmentVertical.BOTTOM)
+                                   text_color=COMPLICATION_GREY, alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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(TextAlignmentVertical.TOP)
+      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP)
     else:
-      self._label.set_alignment_vertical(TextAlignmentVertical.BOTTOM)
+      self._label.set_alignment_vertical(rl.GuiTextAlignmentVertical.TEXT_ALIGN_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(TextAlignmentVertical.MIDDLE if not self._label.text else
-                                           TextAlignmentVertical.BOTTOM)
+    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_line_height(0.95)
 
   @property

openpilot/selfdrive/ui/onroad/alert_renderer.py

@@ -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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=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)
+    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)
 
   def get_alert(self, sm: messaging.SubMaster) -> Alert | None:
     """Generate the current alert based on selfdrive state."""

openpilot/selfdrive/ui/onroad/cabin_camera_dialog.py

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.CENTER,
+        alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
       )
       return -1
 

openpilot/selfdrive/ui/soundd.py

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

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

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.RIGHT)
+      gui_label(desc_rect, description, BRAND_FONT_SIZE, rl.WHITE, alignment=rl.GuiTextAlignment.TEXT_ALIGN_RIGHT)
 
     brand_size = measure_text_cached(gui_app.font(FontWeight.AUDIOWIDE), brand, BRAND_FONT_SIZE)
     spacing = BRAND_DESC_SPACING if description else 0

openpilot/selfdrive/ui/sunnypilot/layouts/onboarding.py

@@ -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, TextAlignment
+from openpilot.system.ui.lib.application import FontWeight
 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=TextAlignment.LEFT))
+    self._title = self._child(Label(tr("sunnylink"), font_size=90, font_weight=FontWeight.AUDIOWIDE, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_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=TextAlignment.LEFT))
+    self._desc = self._child(Label("", font_size=90, font_weight=FontWeight.MEDIUM, text_alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT))
 
   def _handle_choice(self, choice):
     if choice == "enable":

openpilot/selfdrive/ui/sunnypilot/layouts/settings/sunnylink.py

@@ -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, TextAlignment, TextAlignmentVertical
+from openpilot.system.ui.lib.application import gui_app, FontWeight
 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=TextAlignment.CENTER,
-      alignment_vertical=TextAlignmentVertical.TOP,
+      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignment.CENTER,
-      alignment_vertical=TextAlignmentVertical.TOP,
+      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignment.CENTER,
-      alignment_vertical=TextAlignmentVertical.TOP,
+      alignment=rl.GuiTextAlignment.TEXT_ALIGN_CENTER,
+      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_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=TextAlignment.LEFT,
-      alignment_vertical=TextAlignmentVertical.TOP,
+      alignment=rl.GuiTextAlignment.TEXT_ALIGN_LEFT,
+      alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_TOP,
       wrap_text=True,
       elide=False,
     )

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

@@ -5,29 +5,90 @@ 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.widgets.label import UnifiedLabel
+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
 
 
 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):
-    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))
+    # 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))

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

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

openpilot/selfdrive/ui/sunnypilot/ui_state.py

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

openpilot/selfdrive/ui/tests/generate_milestone_sound.py

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

openpilot/selfdrive/ui/tests/milestone_preview.py

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

openpilot/selfdrive/ui/tests/run_milestone_celebration.sh

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

openpilot/selfdrive/ui/tests/test_soundd.py

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

openpilot/selfdrive/ui/ui_state.py

@@ -12,7 +12,6 @@ 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
@@ -96,10 +95,6 @@ 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
@@ -259,23 +254,6 @@ 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)
 

openpilot/sunnypilot/modeld_v2/compile_modeld.py

@@ -41,6 +41,7 @@ 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:
@@ -153,13 +154,12 @@ 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(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)
+    tfm = tfm.to(WARP_DEV)
+    big_tfm = big_tfm.to(WARP_DEV)
+    Tensor.realize(tfm, big_tfm)
 
     warped_frame = frame_prepare(frame, tfm).unsqueeze(0)
     warped_big_frame = frame_prepare(big_frame, big_tfm).unsqueeze(0)
@@ -368,18 +368,16 @@ 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=Device.DEFAULT)
+  make_random_model_inputs = partial(make_random_images, keys=['warped'], shape=(2, 6, model_h // 2, model_w // 2), device=WARP_DEV)
   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=Device.DEFAULT)
+    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), 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)
 

openpilot/sunnypilot/modeld_v2/modeld.py

@@ -6,7 +6,6 @@ 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
@@ -111,12 +110,18 @@ class ModelState(ModelStateBase):
     cloudlog.warning(f"loading combined pkl: {pkl_path}")
     jits = load_oob(open_file_chunked(pkl_path))
 
-    metadata = jits['metadata']
-    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.WARP_DEV = 'QCOM' if COMMA_HARDWARE else 'CPU'
+    self.DEV = 'AMD' if self.chestnut else self.WARP_DEV
     self.QUEUE_DEV = self.DEV
-    self.run_policy = jits['run_policy']
-    self.warp = jits[(cam_w, cam_h)]
+    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)]
 
     if 'model' in metadata:
       model_metadata = metadata['model']
@@ -175,7 +180,11 @@ 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()
-    self.warp(**{k: self.input_queues[k] for k in WARP_INPUTS}, frame=frame_tensor, big_frame=big_frame_tensor)
+
+    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)
 
   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}
@@ -208,8 +217,7 @@ 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,
-          after_enqueue: Callable[[], None] | None = None) -> dict[str, np.ndarray] | None:
+                inputs: dict[str, np.ndarray], prepare_only: bool) -> 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]
@@ -231,18 +239,20 @@ 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 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.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 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:
@@ -275,6 +285,9 @@ 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,
@@ -499,9 +512,7 @@ def main(demo=False):
 
     mt1 = time.perf_counter()
     try:
-      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)
+      model_output = model.run(bufs, transforms, inputs, prepare_only)
     except Exception:
       if not params.get_bool("ChestnutActive"):
         raise
@@ -548,6 +559,9 @@ 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

openpilot/sunnypilot/modeld_v2/tests/test_combined_pkl_loader.py

@@ -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, _frame_views = make_input_queues(stock_shapes, frame_skip, device='NPY', frame_copy_size=49152)
+    stock_queues, stock_npy = make_input_queues(stock_shapes, frame_skip, device='NPY')
 
-    # 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 set(state.input_queues.keys()) == set(stock_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

openpilot/sunnypilot/modeld_v2/tests/test_compile_modeld.py

@@ -7,7 +7,6 @@ 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
@@ -249,27 +248,23 @@ class TestStockCompileModeldEquivalence(OpenpilotTestCase):
     input_shapes = {
       'img': (1, 12, 128, 256),
       'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 32, 512),
+      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
       'traffic_convention': (1, 2),
       'action_t': (1, 2),
     }
     frame_skip = 4
 
-    stock_queues, stock_npy, _frame_views = stock_make_input_queues(input_shapes, frame_skip, device='NPY', frame_copy_size=49152)
+    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
     sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
-    # 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())
+    assert set(sunny_queues.keys()) == set(stock_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(stock_npy.keys()) <= set(sunny_npy.keys())
+    assert set(sunny_npy.keys()) == set(stock_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

openpilot/sunnypilot/models/default_model.py

@@ -20,46 +20,18 @@ 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)
-  fingerprint = f"{supercombo_hash}:{fields.get('DEFAULT_MODEL', '')}:{fields.get('DEFAULT_MODEL_REF', '')}"
-  combined_hash = hashlib.sha256(fingerprint.encode()).hexdigest()
+  combined_hash = hashlib.sha256(supercombo_hash.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)

openpilot/sunnypilot/models/fetcher.py

@@ -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_v22.json"
-  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v24.json"
+  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_SOURCES = {
     "qcom": (MODEL_URL, ""),

openpilot/sunnypilot/models/helpers.py

@@ -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 = 19
+REQUIRED_JSON_VERSION = 18
 
 CUSTOM_MODEL_PATH = Paths.model_root()
 METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'

openpilot/sunnypilot/models/model_name.py

@@ -1,4 +1,4 @@
 DEFAULT_MODEL = "CD210"
 DEFAULT_MODEL_REF = "5b6436a90cf6902b8aaa71c2b6f3d7164d8ae391"
-DEFAULT_BIG_MODEL = "BMRLNAP Model v4"
-DEFAULT_BIG_MODEL_REF = "f877d7a0ccc3cce943c76e285214c020cd65c899"
+DEFAULT_BIG_MODEL = "Lebowski"
+DEFAULT_BIG_MODEL_REF = "fa0c6876d3cf070e91e25e5353ceadc68a5b3285"

openpilot/sunnypilot/models/tests/big_model_hash

@@ -1 +0,0 @@
-2c814f08a2c51323b87839fbf8d2c2a9853a2b5536271b3d67f7b7a2de7f9374

openpilot/sunnypilot/models/tests/model_hash

@@ -1 +1 @@
-c5be11d2fb1115be953c541f30c50f7c71a00bc4a0e128e19aa11b60689317fc
+49133798d9cd9cacf47085c7ef8122bfee88cd9c6192a8314c81bfb1b37f5809

openpilot/sunnypilot/models/tests/test_default_model.py

@@ -5,47 +5,19 @@ 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, BIG_MODEL_HASH_PATH, \
-                                                      BIG_SUPERCOMBO_ONNX_PATH, _read_model_name_fields
+from openpilot.sunnypilot.models.default_model import MODEL_HASH_PATH, SUPERCOMBO_ONNX_PATH
 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)
-    fingerprint = f"{supercombo_hash}:{fields.get('DEFAULT_MODEL', '')}:{fields.get('DEFAULT_MODEL_REF', '')}"
-    combined_hash = hashlib.sha256(fingerprint.encode()).hexdigest()
+
+    combined_hash = hashlib.sha256(supercombo_hash.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"

openpilot/sunnypilot/models/tests/test_manager_download.py

@@ -386,7 +386,7 @@ class TestManagerDownload(ManagerDownloadTestBase):
     def body():
       artifact = self.make_artifact(chunked=True)
       self._bundle.ref = "test-ref"
-      self._bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
+      self._bundle.minimumSelectorVersion = 18
       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 = helpers.REQUIRED_JSON_VERSION
+      self._bundle.minimumSelectorVersion = 18
       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": str(helpers.REQUIRED_JSON_VERSION),
+    "minimum_selector_version": "18",
     "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 = helpers.REQUIRED_JSON_VERSION
+    bundle.minimumSelectorVersion = 18
     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 = helpers.REQUIRED_JSON_VERSION
+    bundle.minimumSelectorVersion = 18
     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 = helpers.REQUIRED_JSON_VERSION
+    bundle.minimumSelectorVersion = 18
     return bundle.to_dict()
 
   def test_runtime_no_gpu(self):

openpilot/sunnypilot/selfdrive/controls/controlsd_ext.py

@@ -104,6 +104,14 @@ 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

openpilot/sunnypilot/selfdrive/selfdrived/assisted_driving_milestones.py

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

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

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

openpilot/sunnypilot/sunnylink/settings_ui.json

@@ -1383,6 +1383,12 @@
               "title": "Steering Arc",
               "description": "Display steering arc on the driving screen when lateral control is enabled."
             },
+            {
+              "key": "AssistedDrivingMilestonesEnabled",
+              "widget": "toggle",
+              "title": "Assisted Driving Milestones",
+              "description": "Celebrate cumulative MADS and full-assist distance milestones while driving."
+            },
             {
               "key": "ShowTurnSignals",
               "widget": "toggle",
@@ -2168,6 +2174,43 @@
     }
   ],
   "vehicle_settings": {
+    "ford": {
+      "title": "Ford Settings",
+      "description": "",
+      "items": [
+        {
+          "key": "FordVirtualAngleController",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "C2-Free Path Tracking (Experimental)",
+          "description": "Use the planner's centering correction and retain full turn heading on the F-150 Lightning with C2 off.",
+          "details": "Updates the centering request while retaining turn heading. Default off and this version is not road-validated. Available only on the F-150 Lightning with RL38-14D003-AA steering firmware; other vehicles retain their existing controller. Enable only for controlled testing. Takes priority over PSCM Coefficient Observer while enabled. Turning it off restores the previous controller selection. Changes apply after a real offroad-to-onroad cycle, not immediately or on disengagement alone.",
+          "enablement": [
+            {
+              "type": "offroad_only"
+            }
+          ]
+        },
+        {
+          "key": "FordPscmObserver",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "PSCM Coefficient Observer (Experimental)",
+          "description": "Track the Ford steering controller's internal polynomial states and use fast path terms only for the response that slow curvature cannot provide.",
+          "details": "This changes live steering behavior on Ford CAN FD vehicles. Use only for supervised testing and be ready to take over immediately. This strategy is bypassed when C2-Free Path Tracking is selected on a supported vehicle; its selection is retained when that experiment is turned off.",
+          "enablement": [
+            {
+              "type": "offroad_only"
+            },
+            {
+              "type": "param",
+              "key": "FordVirtualAngleController",
+              "equals": false
+            }
+          ]
+        }
+      ]
+    },
     "hyundai": {
       "title": "Hyundai / Kia / Genesis Settings",
       "description": "",

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

@@ -6,6 +6,29 @@ icon: vehicle
 order: 99
 kind: vehicle
 sections:
+- id: ford
+  title: Ford Settings
+  description: ''
+  items:
+  - key: FordVirtualAngleController
+    widget: toggle
+    needs_onroad_cycle: true
+    title: C2-Free Path Tracking (Experimental)
+    description: Use the planner's centering correction and retain full turn heading on the F-150 Lightning with C2 off.
+    details: Updates the centering request while retaining turn heading. Default off and this version is not road-validated. Available only on the F-150 Lightning with RL38-14D003-AA steering firmware; other vehicles retain their existing controller. Enable only for controlled testing. Takes priority over PSCM Coefficient Observer while enabled. Turning it off restores the previous controller selection. Changes apply after a real offroad-to-onroad cycle, not immediately or on disengagement alone.
+    enablement:
+    - $ref: '#/macros/offroad'
+  - key: FordPscmObserver
+    widget: toggle
+    needs_onroad_cycle: true
+    title: PSCM Coefficient Observer (Experimental)
+    description: Track the Ford steering controller's internal polynomial states and use fast path terms only for the response that slow curvature cannot provide.
+    details: This changes live steering behavior on Ford CAN FD vehicles. Use only for supervised testing and be ready to take over immediately. This strategy is bypassed when C2-Free Path Tracking is selected on a supported vehicle; its selection is retained when that experiment is turned off.
+    enablement:
+    - $ref: '#/macros/offroad'
+    - type: param
+      key: FordVirtualAngleController
+      equals: false
 - id: hyundai
   title: Hyundai / Kia / Genesis Settings
   description: ''

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

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

openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py

@@ -5,6 +5,7 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 import json
+import tempfile
 
 from openpilot.common.params import Params
 from openpilot.sunnypilot.sunnylink.tools.generate_settings_schema import (
@@ -278,6 +279,35 @@ class TestKnownPanels(OpenpilotTestCase):
 
 
 class TestKnownVehicleSettings(OpenpilotTestCase):
+  def test_ford_virtual_angle_replaces_shared_path_and_is_cycle_only(self, schema):
+    items = _brand_items(schema["vehicle_settings"].get("ford"))
+    assert "FordSharedPathController" not in {item["key"] for item in items}
+    servo = next(item for item in items if item["key"] == "FordVirtualAngleController")
+    assert servo["title"] == "C2-Free Path Tracking (Experimental)"
+    assert servo["widget"] == "toggle"
+    assert servo["needs_onroad_cycle"] is True
+    # No other toggle can prevent disabling this experiment while offroad.
+    assert servo["enablement"] == [{"type": "offroad_only"}]
+    assert "F-150 Lightning" in servo["description"]
+    assert "RL38-14D003-AA" in servo["details"]
+    assert "not road-validated" in servo["details"]
+    assert "offroad" in servo["details"] and "onroad" in servo["details"]
+
+  def test_ford_virtual_angle_defaults_off(self):
+    with tempfile.TemporaryDirectory() as path:
+      params = Params(path)
+      assert params.get_default_value("FordVirtualAngleController") is False
+      assert b"FordSharedPathController" not in params.all_keys()
+
+  def test_ford_has_pscm_observer(self, schema):
+    items = _brand_items(schema["vehicle_settings"].get("ford"))
+    observer = next(item for item in items if item["key"] == "FordPscmObserver")
+    assert observer["needs_onroad_cycle"] is True
+    assert observer["enablement"] == [
+      {"type": "offroad_only"},
+      {"type": "param", "key": "FordVirtualAngleController", "equals": False},
+    ]
+
   def test_hyundai_has_longitudinal_tuning(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("hyundai"))}
     assert "HyundaiLongitudinalTuning" in keys

openpilot/sunnypilot/system/params_migration.py

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

openpilot/sunnypilot/system/tests/test_params_migration.py

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

openpilot/system/hardware/chestnut/status.py

@@ -1,101 +0,0 @@
-import time
-
-from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, is_chestnut_usb_id
-from openpilot.common.version import get_build_metadata, CHESTNUT_BRANCHES
-from openpilot.selfdrive.modeld.helpers import MODELS_DIR, chestnut_compiled
-
-
-CHESTNUT_RELEASE_BRANCHES = ("release-chestnut", "release-chestnut-staging")
-CHESTNUT_POWERED_VOLTAGE = 5000
-GPU_TEMP_LIMIT = 100.
-MEMORY_TEMP_LIMIT = 95.
-TEMP_HYSTERESIS = 5.
-
-
-class ChestnutStatus:
-  def __init__(self):
-    self.started = time.monotonic()
-    self.offroad = True
-    self.pcie_failed = False
-    self.power_seen = False
-    self.power_unavailable = False
-    self.power_lost = False
-    self.power_restored = False
-    self.link_failures = 0
-    self.model_loading_seen = False
-    self.model_attempted = False
-    self.overheated = False
-    self.usb_seen = False
-    self.usb_failed = False
-
-  def update(self, offroad: bool, branch: str, usb_state: list[dict], firmware_failed: bool,
-             model_loading: bool, model_active: bool | None, state, set_alert) -> None:
-    detected = [d for d in usb_state if is_chestnut_usb_id(d["vendorId"], d["productId"], include_bootloader=True)]
-    devices = [d for d in detected if is_chestnut_usb_id(d["vendorId"], d["productId"])]
-    firmware_ok = len(devices) == 1 and devices[0]["product"] == CHESTNUT_USB_PRODUCT
-
-    if self.offroad and not offroad:
-      self.pcie_failed = False
-      self.power_seen = False
-      self.power_unavailable = False
-      self.power_lost = False
-      self.power_restored = False
-      self.link_failures = 0
-      self.model_loading_seen = False
-      self.model_attempted = False
-      self.usb_seen = firmware_ok
-      self.usb_failed = False
-
-    self.model_loading_seen |= model_loading
-    self.model_attempted |= self.model_loading_seen and not model_loading and model_active is not None
-
-    if not offroad and self.usb_seen and not firmware_ok:
-      self.usb_failed = True
-
-    if not offroad and state is not None:
-      powered = state.supplyVoltage >= CHESTNUT_POWERED_VOLTAGE
-      power_lost = state.supplyFault or not powered
-      if self.model_attempted and power_lost and not self.power_lost:
-        self.power_unavailable = not self.power_seen
-      self.power_seen |= powered
-
-    if not offroad and self.model_attempted and state is not None:
-      self.link_failures = self.link_failures + 1 if state.pcieLtssm != 0x78 else 0
-      self.pcie_failed |= self.link_failures >= 2 or power_lost
-      self.power_lost |= power_lost
-
-    if self.pcie_failed and self.power_lost and state is not None:
-      self.power_restored |= not state.supplyFault and state.supplyVoltage >= CHESTNUT_POWERED_VOLTAGE
-    if self.usb_failed:
-      self.pcie_failed = False
-      self.power_seen = False
-      self.power_unavailable = False
-      self.power_lost = False
-      self.power_restored = False
-
-    if state is not None:
-      gpu_limit = GPU_TEMP_LIMIT - (TEMP_HYSTERESIS if self.overheated else 0.)
-      memory_limit = MEMORY_TEMP_LIMIT - (TEMP_HYSTERESIS if self.overheated else 0.)
-      self.overheated = state.tempC >= gpu_limit or state.memoryTempC >= memory_limit
-
-    release = branch in CHESTNUT_RELEASE_BRANCHES
-    missing = self.usb_failed or (offroad and release and time.monotonic() - self.started > 10. and len(detected) != 1)
-    slow_usb = offroad and len(devices) == 1 and devices[0]["speedMbps"] < 5000
-    big_model_available = (MODELS_DIR / 'big_driving_supercombo.onnx').is_file() or chestnut_compiled()
-    current_channel = get_build_metadata().channel
-    chestnut_target = CHESTNUT_BRANCHES.get(current_channel)
-    chestnut_needs_switch = len(devices) == 1 and not big_model_available and chestnut_target is not None
-    set_alert("Offroad_ChestnutBranch", chestnut_needs_switch, chestnut_target if chestnut_needs_switch else None)
-    set_alert("Offroad_ChestnutNotDetected", missing)
-    set_alert("Offroad_ChestnutOverheated", self.overheated, f"{state.tempC:.0f} °C" if state is not None else None)
-    set_alert("Offroad_ChestnutUsbSlow", slow_usb, f"{devices[0]['speedMbps']} Mbps" if slow_usb else None)
-    if self.power_lost:
-      pcie_alert = ("Chestnut power restored. 12V is stable again, cycle ignition." if self.power_restored else
-                    "Chestnut power disconnected. Check 12V connection, then cycle ignition." if self.power_unavailable else
-                    "Chestnut power lost. Possibly caused by an engine-crank voltage drop. Check 12V connection, then cycle ignition.")
-    else:
-      pcie_alert = "Chestnut GPU unavailable. PCIe link is not up. Check the GPU is securely seated."
-    set_alert("Offroad_ChestnutPcieUnavailable", self.pcie_failed, pcie_alert)
-    set_alert("Offroad_ChestnutUncompiled", offroad and firmware_ok and not chestnut_compiled())
-    set_alert("Offroad_ChestnutUpdateFailed", offroad and firmware_failed)
-    self.offroad = offroad

openpilot/system/hardware/hardwared.py

@@ -16,19 +16,19 @@ from openpilot.common.utils import strip_deprecated_keys
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.params import Params
 from openpilot.common.realtime import DT_HW
+from openpilot.selfdrive.modeld.helpers import MODELS_DIR, chestnut_compiled
 from openpilot.selfdrive.selfdrived.alertmanager import set_offroad_alert
 from openpilot.common.hardware import HARDWARE, COMMA_HARDWARE
 from openpilot.common.basedir import BASEDIR
-from openpilot.common.git import get_short_branch
-from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_USB_PRODUCT, get_usb_state, get_usb_topology, is_chestnut_usb_id, set_usb_state
+from openpilot.common.hardware.usb import CHESTNUT_FW_VERSION, CHESTNUT_ROM_USB_IDS, CHESTNUT_USB_IDS, get_usb_state, get_usb_topology, set_usb_state
 from openpilot.common.linux import LinuxSystemStats
 from openpilot.system.loggerd.config import get_available_percent
 from openpilot.common.swaglog import cloudlog
 from openpilot.sunnypilot.system.statsd import statlog
 from openpilot.system.hardware.power_monitoring import PowerMonitoring
 from openpilot.system.hardware.fan_controller import FanController
-from openpilot.system.hardware.chestnut.status import ChestnutStatus
-from openpilot.common.version import terms_version, training_version, get_build_metadata, terms_version_sp
+from openpilot.common.version import terms_version, training_version, get_build_metadata, terms_version_sp, CHESTNUT_BRANCHES
+
 
 ThermalStatus = log.DeviceState.ThermalStatus
 NetworkType = log.DeviceState.NetworkType
@@ -49,11 +49,6 @@ class Chestnut:
     self.attempts = 0
     self.last_attempt = 0.
     self.flashed = False
-    self.mismatch = False
-
-  @property
-  def failed(self) -> bool:
-    return self.mismatch and self.attempts >= self.MAX_ATTEMPTS and self.thread is not None and not self.thread.is_alive() and not self.flashed
 
   def flash(self) -> None:
     ret = subprocess.run(["sudo", sys.executable, os.path.join(BASEDIR, "openpilot/system/hardware/chestnut/flash.py"), CHESTNUT_FW_VERSION],
@@ -62,9 +57,9 @@ class Chestnut:
     self.flashed = ret.returncode == 0
 
   def update(self, offroad: bool, usb_state: list[dict]) -> None:
-    self.mismatch = any(is_chestnut_usb_id(d["vendorId"], d["productId"], include_bootloader=True) and
-                        d["product"] != CHESTNUT_USB_PRODUCT for d in usb_state)
-    if not self.mismatch:
+    mismatch = any((d["vendorId"], d["productId"]) in CHESTNUT_USB_IDS + CHESTNUT_ROM_USB_IDS and
+                   d["product"] != f"custom {CHESTNUT_FW_VERSION}-CLEAN" for d in usb_state)
+    if not mismatch:
       self.flashed = False
       return
 
@@ -196,7 +191,7 @@ def hw_state_thread(end_event, hw_queue):
 def hardware_thread(end_event, hw_queue) -> None:
   system_stats = LinuxSystemStats()
   pm = messaging.PubMaster(['deviceState'])
-  sm = messaging.SubMaster(["peripheralState", "gpsLocationExternal", "selfdriveState", "pandaStates", "chestnutState"], poll="pandaStates")
+  sm = messaging.SubMaster(["peripheralState", "gpsLocationExternal", "selfdriveState", "pandaStates"], poll="pandaStates")
 
   count = 0
 
@@ -244,8 +239,7 @@ def hardware_thread(end_event, hw_queue) -> None:
 
   fan_controller = FanController(int(1./DT_HW))
   chestnut = Chestnut()
-  chestnut_status = ChestnutStatus()
-  branch = get_short_branch()
+  big_model_available = (MODELS_DIR / 'big_driving_supercombo.onnx').is_file() or chestnut_compiled()
 
   while not end_event.is_set():
     sm.update(PANDA_STATES_TIMEOUT)
@@ -307,11 +301,12 @@ def hardware_thread(end_event, hw_queue) -> None:
 
     set_usb_state(msg.deviceState, last_hw_state.usb_state)
     chestnut.update(started_ts is None, last_hw_state.usb_state)
-    chestnut_state = sm["chestnutState"]
-    chestnut_valid = sm.alive["chestnutState"] and sm.valid["chestnutState"]
-    chestnut_status.update(started_ts is None, branch, last_hw_state.usb_state, chestnut.failed,
-                           params.get_bool("ChestnutLoading"), params.get("ChestnutActive"),
-                           chestnut_state if chestnut_valid else None, set_offroad_alert_if_changed)
+    current_channel = get_build_metadata().channel
+    chestnut_target = CHESTNUT_BRANCHES.get(current_channel)
+    chestnut_needs_switch = msg.deviceState.chestnutPresent and not big_model_available and chestnut_target is not None
+    set_offroad_alert_if_changed("Offroad_ChestnutBranch", chestnut_needs_switch,
+                                 extra_text=chestnut_target if chestnut_needs_switch else None)
+
     # this subset is only used for offroad
     temp_sources = [
       msg.deviceState.memoryTempC,

openpilot/system/ui/lib/application.py

@@ -13,7 +13,7 @@ import subprocess
 from contextlib import contextmanager
 from collections.abc import Callable
 from collections import deque
-from enum import IntEnum, StrEnum
+from enum import StrEnum
 from pathlib import Path
 from typing import NamedTuple
 from importlib.resources import as_file, files
@@ -118,18 +118,6 @@ class FontWeight(StrEnum):
   DISPLAY = "Inter-Bold.ttf"
 
 
-class TextAlignment(IntEnum):
-  LEFT = 0
-  CENTER = 1
-  RIGHT = 2
-
-
-class TextAlignmentVertical(IntEnum):
-  TOP = 0
-  MIDDLE = 1
-  BOTTOM = 2
-
-
 def font_fallback(font: rl.Font) -> rl.Font:
   """Use a Noto fallback for languages not covered by Inter."""
   if multilang.requires_font_fallback():
@@ -347,6 +335,7 @@ class GuiApplication(GuiApplicationExt):
       rl.set_target_fps(0 if OFFSCREEN or vblank_control else fps)
 
       self._target_fps = fps
+      self._set_styles()
       self._load_fonts()
       self._patch_text_functions()
       self._patch_scissor_mode()
@@ -750,6 +739,14 @@ class GuiApplication(GuiApplicationExt):
         self._fonts[font_weight_file] = font
     if multilang.requires_font_fallback():
       self.fallback_font()
+    rl.gui_set_font(self._fonts[FontWeight.NORMAL])
+
+  def _set_styles(self):
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.BORDER_WIDTH, 0)
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_SIZE, DEFAULT_TEXT_SIZE)
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.BACKGROUND_COLOR, rl.color_to_int(rl.BLACK))
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_COLOR_NORMAL, rl.color_to_int(DEFAULT_TEXT_COLOR))
+    rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.BASE_COLOR_NORMAL, rl.color_to_int(rl.Color(50, 50, 50, 255)))
 
   def _patch_text_functions(self):
     # Wrap pyray text APIs to apply a global text size scale so our px sizes match Qt

openpilot/system/ui/lib/utils.py

@@ -0,0 +1,19 @@
+import pyray as rl
+from collections.abc import Sequence
+
+
+class GuiStyleContext:
+  def __init__(self, styles: Sequence[tuple[int, int, int]]):
+    """styles is a list of tuples (control, prop, new_value)"""
+    self.styles = styles
+    self.prev_styles: list[tuple[int, int, int]] = []
+
+  def __enter__(self):
+    for control, prop, new_value in self.styles:
+      prev_value = rl.gui_get_style(control, prop)
+      self.prev_styles.append((control, prop, prev_value))
+      rl.gui_set_style(control, prop, new_value)
+
+  def __exit__(self, exc_type, exc_value, traceback):
+    for control, prop, prev_value in self.prev_styles:
+      rl.gui_set_style(control, prop, prev_value)