ref

simple

control: restore stock deceleration behavior

test

maybe better

tune

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

@@ -47,7 +47,6 @@ jobs:
           if [ "${{ inputs.target }}" = "big" ]; then
             NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
             HF_DEFAULTS_PATH="models/defaults/big"
-            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl"
           elif [ "${{ inputs.target }}" = "dm" ]; then
             ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
             HF_DEFAULTS_PATH="models/defaults/dm"
@@ -117,6 +116,20 @@ jobs:
             ${{ github.workspace }}/${{ env.SMALL_PKL }} \
             --device-input "*" --out-of-band --benchmark-runs 1
 
+      - name: Chunk small pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.SMALL_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
+
       - name: Prepare output
         env:
           MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
@@ -128,7 +141,8 @@ jobs:
           PKL_BASE="driving_tinygrad.pkl"
           mkdir -p "$OUTPUT_DIR"
 
-          cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
 
           ONNX_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.SMALL_ONNX }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
 
@@ -207,33 +221,19 @@ jobs:
               raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
           "
 
-      - name: Compile big warp
+      - name: Chunk big pkl
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          CHESTNUT_TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
-          COMPILER="${{ github.workspace }}/tinygrad_repo/examples/openpilot"
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
-          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
-
-          for res in $(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')"); do
-            CAM_W=$(echo $res | cut -d x -f1)
-            CAM_H=$(echo $res | cut -d x -f2)
-            STRIDE_INFO=$(python3 -c "
-          import sys
-          from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
-          s,y,u,sz = get_nv12_info(int(sys.argv[1]), int(sys.argv[2]))
-          print(f'{s},{y},{u},{sz}')
-          " $CAM_W $CAM_H)
-            WARP_PKL="${MODELS_DIR}/big_driving_warp_${res}_tinygrad.pkl"
-            env ${CHESTNUT_TG_FLAGS} python3 "${COMPILER}/compile_warp.py" \
-              --frame ${CAM_W},${CAM_H},${STRIDE_INFO} \
-              --warp-to ${MODEL_SIZE} \
-              --layout yuv420 \
-              --frames 2 \
-              --output "${WARP_PKL}"
-          done
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.BIG_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked into {len(targets)} files')
+          "
 
       - name: Prepare output
         env:
@@ -246,9 +246,10 @@ jobs:
           PKL_BASE="big_driving_tinygrad.pkl"
           mkdir -p "$OUTPUT_DIR"
 
-          cp "$MODELS_DIR/${PKL_BASE}" "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
+          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
 
-          PKL_LFS_SHA256=$(git cat-file blob "$(git ls-files -s "${{ github.workspace }}/${{ env.BIG_PKL }}" | awk '{print $2}')" | grep '^oid sha256:' | cut -d: -f2)
+          PKL_LFS_SHA256=$(sha256sum "$MODELS_DIR/${PKL_BASE}" | cut -d' ' -f1)
 
           python3 "${{ github.workspace }}/release/ci/model_generator.py" \
             --model-dir "$MODELS_DIR" \
@@ -257,8 +258,6 @@ jobs:
             --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}" \
             --onnx-sha256 "$PKL_LFS_SHA256"
 
-          cp "$MODELS_DIR"/big_driving_warp_* "$OUTPUT_DIR/" || true
-
           echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
 
       - name: Upload big model artifact
@@ -336,8 +335,6 @@ jobs:
             --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
             --artifact-name "$ARTIFACT_NAME" \
             --model-dir output \
-            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
-            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
             --model-name "${{ needs.resolve.outputs.model_name }}" \
             --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
             --run-number "${{ github.run_number }}"
@@ -361,14 +358,24 @@ jobs:
           from datetime import datetime, UTC
 
           dm_dir = Path('dm_output')
-          matches = sorted(dm_dir.glob('dmonitoring_*_tinygrad.pkl'))
-          assert len(matches) == 1, f'expected one DM pkl in {dm_dir}, found {matches}'
-          pkl_name = matches[0].name
+          manifest = list(dm_dir.glob('*.chunkmanifest'))
+          assert manifest, 'No chunkmanifest found'
+          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
+          num_chunks = int(manifest[0].read_text().strip())
+
+          chunks = []
+          for i in range(num_chunks):
+              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
+              chunks.append({
+                  'file_name': chunk.name,
+                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
+              })
 
           digest = hashlib.sha256()
-          with open(dm_dir / pkl_name, 'rb') as f:
-              while block := f.read(1024*1024):
-                  digest.update(block)
+          for c in chunks:
+              with open(dm_dir / c['file_name'], 'rb') as f:
+                  while block := f.read(1024*1024):
+                      digest.update(block)
 
           metadata = {
               'bundles': [{
@@ -382,7 +389,8 @@ jobs:
                       'type': 'chunked',
                       'artifact': {
                           'file_name': pkl_name,
-                          'download_uri': {'url': '', 'sha256': digest.hexdigest()}
+                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
+                          'chunks': chunks
                       }
                   }]
               }]
@@ -445,6 +453,20 @@ jobs:
             ${{ github.workspace }}/${{ env.DM_ONNX }} \
             ${{ github.workspace }}/${{ env.DM_PKL }}
 
+      - name: Chunk DM pkl
+        run: |
+          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
+          export PYTHONPATH=${{ github.workspace }}
+          python3 -c "
+          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+          import os
+          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
+          size = os.path.getsize(pkl)
+          targets = get_chunk_targets(pkl, size)
+          chunk_file(pkl, targets)
+          print(f'Chunked {pkl} into {len(targets)} chunks')
+          "
+
       - name: Compile DM warp
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
@@ -477,7 +499,8 @@ jobs:
       - name: Prepare DM output
         run: |
           mkdir -p dm_output
-          cp ${{ github.workspace }}/${{ env.DM_PKL }} 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
@@ -491,3 +514,4 @@ jobs:
         run: |
           source ${UV_PROJECT_ENVIRONMENT}/bin/activate
           PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
+

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

@@ -137,7 +137,6 @@ jobs:
     needs: build_model
     runs-on: ubuntu-latest
     permissions:
-      actions: read
       id-token: write
       contents: write
     steps:
@@ -180,21 +179,18 @@ jobs:
           echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
 
       - name: Download and extract model artifact
-        env:
-          GH_TOKEN: ${{ github.token }}
-          ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
-        run: |
-          id=$(gh api -X GET "repos/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID/artifacts" -f name="$ARTIFACT_NAME" --jq '.artifacts[0].id')
-          url=$(curl -sf -o /dev/null -w '%{redirect_url}' -H "Authorization: Bearer $GH_TOKEN" "https://api.github.com/repos/$GITHUB_REPOSITORY/actions/artifacts/$id/zip")
-          sudo apt-get install -y -qq aria2 > /dev/null
-          aria2c -q -x16 -s16 -k8M --max-tries=5 --file-allocation=none -o model.zip "$url" && unzip -q model.zip -d output && rm model.zip
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.read-artifact-name.outputs.artifact_name }}
+          path: output
 
       - name: Create models folder
         env:
           ARTIFACT_NAME: ${{ steps.read-artifact-name.outputs.artifact_name }}
         run: |
           mkdir -p "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}"
-          cp output/metadata.json "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/"
+          cp -r output/* "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/"
+          rm -f "local_models/${RECOMPILED_DIR}/${ARTIFACT_NAME}/artifact_name.txt"
 
       - name: Upload to Hugging Face
         env:

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

@@ -1,5 +1,5 @@
-name: Download HF model
-description: Resolve and download models from HuggingFace in parallel
+name: Download HF model chunks
+description: Resolve and download model chunks from HuggingFace in parallel
 
 inputs:
   hf_repo:
@@ -19,7 +19,7 @@ inputs:
 runs:
   using: composite
   steps:
-    - name: Download models
+    - name: Download model chunks
       shell: bash
       env:
         HF_REPO: ${{ inputs.hf_repo }}
@@ -33,7 +33,7 @@ runs:
         resolve_chunks() {
           local HF_PATH="$1" ONNX_HASH="$2" CANONICAL="$3" DEST_DIR="$4"
           local JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_PATH}/default_models.json"
-          local DEFAULTS BUNDLE ARTIFACT FILE_URL BASE_URL
+          local DEFAULTS BUNDLE ARTIFACT BASE_URL NUM_CHUNKS
           DEFAULTS=$(curl -fsSL "$JSON_URL")
           if [ -n "$TINYGRAD_REF" ]; then
             BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" --arg tg "$TINYGRAD_REF" '
@@ -51,23 +51,26 @@ runs:
           fi
 
           ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          FILE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url')
-          BASE_URL=$(echo "$FILE_URL" | sed 's|/[^/]*$||')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
 
           mkdir -p "$DEST_DIR"
-          ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${FILE_URL}', safe=':/'))")
-          printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}" >> "$DOWNLOAD_LIST"
+          while IFS= read -r CHUNK_NAME; do
+            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+' || true)
+            if [ -z "$CHUNK_IDX" ]; then
+              echo "::error::Failed to parse chunk index from: $CHUNK_NAME"
+              return 1
+            fi
+            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
+            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
-          elif [ "$CANONICAL" = "big_driving_tinygrad.pkl" ]; then
-            for warp in big_driving_warp_1928x1208_tinygrad.pkl big_driving_warp_1344x760_tinygrad.pkl; do
-              ENCODED_URL=$(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
         }
 
@@ -79,7 +82,7 @@ runs:
         done
 
         TOTAL=$(wc -l < "$DOWNLOAD_LIST")
-        echo "Downloading $TOTAL files with 8 parallel connections..."
+        echo "Downloading $TOTAL chunks with 8 parallel connections..."
         xargs -P8 -d'\n' -I{} bash -c '
           URL="${1%%	*}"
           DEST="${1#*	}"

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

@@ -149,17 +149,7 @@ jobs:
               git lfs pull -X "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/dmonitoring_*.onnx,**/selfdrive/modeld/models/big_*.pkl,**/selfdrive/modeld/models/dmonitoring_*.pkl"
               rm -f selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/dmonitoring_*.onnx selfdrive/modeld/models/big_*.pkl selfdrive/modeld/models/dmonitoring_*.pkl
             else
-              sudo apt-get install -y -qq aria2 > /dev/null # Parallel ranges because gh is flaky
-              LFS_URL=$(git config -f "$(git rev-parse --show-toplevel)/.lfsconfig" lfs.url)
-              for f in selfdrive/modeld/models/big_*.onnx selfdrive/modeld/models/big_*.pkl; do
-                grep -qs "^version https://git-lfs" "$f" || continue
-                OID=$(awk -F'sha256:' '/^oid/{print $2}' "$f"); SIZE=$(awk '/^size/{print $2}' "$f")
-                HREF=$(curl -fsSL --retry 3 -X POST -H "Accept: application/vnd.git-lfs+json" -H "Content-Type: application/vnd.git-lfs+json" "$LFS_URL/objects/batch" \
-                  -d "{\"operation\":\"download\",\"transfer\":[\"basic\"],\"objects\":[{\"oid\":\"$OID\",\"size\":$SIZE}]}" | jq -r '.objects[0].actions.download.href')
-                aria2c -x 16 -s 16 -k 16M --max-tries=5 --retry-wait=5 --file-allocation=none --summary-interval=30 --allow-overwrite=true \
-                  -d "$(dirname "$f")" -o "$(basename "$f")" "$HREF"
-                echo "$OID  $f" | sha256sum -c -
-              done
+              git lfs pull -I "**/selfdrive/modeld/models/big_*.onnx,**/selfdrive/modeld/models/big_*.pkl" -X ""
               find selfdrive/modeld/models -type f \( -name "*.onnx" -o -name "*.pkl" \) ! -name "big_*.onnx" ! -name "big_*.pkl" -delete
             fi
           fi
@@ -172,7 +162,6 @@ jobs:
         uses: actions/upload-artifact@v4
         with:
           name: models-${{ env.REF }}${{ inputs.artifact_suffix  }}
-          compression-level: 0
           path: |
             ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.onnx
             ${{ github.workspace }}/openpilot/openpilot/selfdrive/modeld/models/*.pkl
@@ -235,11 +224,11 @@ jobs:
           MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
           CAMERA_RES=$(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}')")
 
-          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 OPENPILOT_HACKS=1"
+          TG_FLAGS_QCOM="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
           if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
             echo "CHESTNUT build"
             export CHESTNUT=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
+            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM FRAME_DEV=CPU FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2 TC_MIN_GLOBALS=32"
             OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
           else
             echo "QCOM build"
@@ -251,15 +240,14 @@ jobs:
 
           if [ -f "${{ env.MODELS_DIR }}/new_arch.txt" ]; then
             echo "Detected new arch"
-            if [ "${{ inputs.target_hardware }}" == "chestnut" ]; then
-              DOWNLOADED_ONNX=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "big_*driving*.onnx" -print -quit)
-            else
-              DOWNLOADED_ONNX=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*driving*.onnx" ! -name "big_*" -print -quit)
-            fi
+            DOWNLOADED_ONNX=$(find "${{ env.MODELS_DIR }}" -maxdepth 1 -name "*driving*.onnx" -print -quit)
             if [ -n "$DOWNLOADED_ONNX" ]; then
               echo "Compiling ONNX: $DOWNLOADED_ONNX"
               env ${TG_FLAGS} taskset -c 7 python3 openpilot/sunnypilot/modeld_v2/compile_modeld_v2.py \
-                "$DOWNLOADED_ONNX" "$OUTPUT_PKL" --device-input "*" --benchmark-runs 1
+                "$DOWNLOADED_ONNX" "$OUTPUT_PKL" --device-input "*" --out-of-band --benchmark-runs 1
+
+              echo "Chunking pkl"
+              python3 -c "from openpilot.common.file_chunker import chunk_file, get_chunk_targets; import os; p='$OUTPUT_PKL'; chunk_file(p, get_chunk_targets(p, os.path.getsize(p)))"
             else
               echo "Failed to find downloaded ONNX."
               exit 1
@@ -329,7 +317,8 @@ jobs:
           # Copy the model files
           rsync -avm \
             --include='*.dlc' \
-            --include='/${{ inputs.target_hardware == 'chestnut' && 'big_' || '' }}driving_tinygrad.pkl' \
+            --include='*.chunk*' \
+            --include='*.chunkmanifest' \
             --exclude='*' \
             --delete-excluded \
             --chown=comma:comma \
@@ -351,7 +340,6 @@ jobs:
         with:
           name: model-${{ env.MODEL_NAME }}${{ inputs.artifact_suffix }}-${{ github.run_number }}
           path: ${{ env.OUTPUT_DIR }}
-          compression-level: 0
 
       - name: Upload artifact name file
         uses: actions/upload-artifact@v4

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

@@ -503,8 +503,8 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Download models from HF
-        uses: ./.github/workflows/download-hf-model
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
         with:
           hf_repo: sunnypilot/sunnypilot_models_v1
           dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
@@ -573,8 +573,8 @@ jobs:
           mkdir -p ${{ env.OUTPUT_DIR }}
           tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
 
-      - name: Download models from HF
-        uses: ./.github/workflows/download-hf-model
+      - name: Download model chunks from HF
+        uses: ./.github/workflows/download-hf-model-chunks
         with:
           hf_repo: sunnypilot/sunnypilot_models_v1
           dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models

.github/workflows/test_models.yml

@@ -47,22 +47,38 @@ jobs:
         with:
           submodules: true
 
-      - name: Download model
+      - name: Download Model Chunks in Parallel
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
-          MODEL_URL: ${{ matrix.artifact.download_uri.url }}
-          MODEL_FILE: ${{ matrix.artifact.file_name }}
-        shell: bash
         run: |
-          mkdir -p /tmp/models
-          AUTH=()
-          if [ -n "$HF_TOKEN" ]; then AUTH=(-H "Authorization: Bearer $HF_TOKEN"); fi
-          curl --retry 3 --retry-all-errors -s -S -f -L "${AUTH[@]}" -o "/tmp/models/$MODEL_FILE" "$MODEL_URL"
+          mkdir -p /tmp/model_chunks
+          echo '${{ toJson(matrix.artifact.chunks) }}' > chunks.json
+
+          BASE_URL="${{ matrix.artifact.download_uri.url }}"
+          export BASE_DIR=$(dirname "$BASE_URL")
+
+          python3 -c '
+          import json, os
+          with open("chunks.json") as f:
+            chunks = json.load(f)
+          manifest_path = f"/tmp/model_chunks/${{ matrix.artifact.file_name }}.chunkmanifest"
+          with open(manifest_path, "w") as f:
+            f.write(str(len(chunks)))
+          base_dir = os.environ["BASE_DIR"]
+          hf_token = os.environ.get("HF_TOKEN", "")
+          with open("/tmp/curl_config.txt", "w") as f:
+            for c in chunks:
+              fn = c["file_name"]
+              f.write(f"url = \"{base_dir}/{fn}\"\noutput = \"/tmp/model_chunks/{fn}\"\n")
+              if hf_token:
+                f.write(f"header = \"Authorization: Bearer {hf_token}\"\n")
+          '
+          curl -Z --parallel-immediate --parallel-max 12 --retry 3 --retry-all-errors -s -S -f -L -K /tmp/curl_config.txt
 
       - name: Run Model Compatibility Test
         env:
           MODEL_BASE_NAME: ${{ matrix.artifact.file_name }}
-          MODEL_DIR: "/tmp/models"
+          MODEL_CHUNK_DIR: "/tmp/model_chunks"
         run: |
           export PYTHONPATH="$GITHUB_WORKSPACE/tinygrad_repo:$GITHUB_WORKSPACE:$PYTHONPATH"
           python3 -m pip uninstall -y tinygrad || uv pip uninstall -y tinygrad --system || true

.gitmodules

@@ -4,6 +4,7 @@
 [submodule "opendbc"]
   path = opendbc_repo
   url = https://github.com/sunnypilot/opendbc.git
+  branch = tn
 [submodule "msgq"]
   path = msgq_repo
   url = https://github.com/sunnypilot/msgq.git

openpilot/cereal/custom.capnp

@@ -204,11 +204,16 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
   aTarget @5 :Float32;
   events @6 :List(OnroadEventSP.Event);
   e2eAlerts @7 :E2eAlerts;
+  accelController @8 :AccelController;
 
   struct DynamicExperimentalControl {
     state @0 :DynamicExperimentalControlState;
     enabled @1 :Bool;
     active @2 :Bool;
+    decelIntent @3 :Float32;
+    curveDetected @4 :Bool;
+    wantBlended @5 :Bool;
+    leadVeto @6 :Bool;
 
     enum DynamicExperimentalControlState {
       acc @0;
@@ -306,6 +311,17 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
     greenLightAlert @0 :Bool;
     leadDepartAlert @1 :Bool;
   }
+
+  struct AccelController {
+    enabled @0 :Bool;
+    active @1 :Bool;
+    profile @2 :Profile;
+    enum Profile {
+      eco @0;
+      normal @1;
+      sport @2;
+    }
+  }
 }
 
 struct OnroadEventSP @0xda96579883444c35 {
@@ -447,6 +463,8 @@ struct BackupManagerSP @0xf98d843bfd7004a3 {
 
 struct CarStateSP @0xb86e6369214c01c8 {
   speedLimit @0 :Float32;
+  engineOff @1 :Bool;
+  engineRpm @2 :Float32;
 }
 
 struct LiveMapDataSP @0xf416ec09499d9d19 {

openpilot/common/params_keys.h

@@ -192,8 +192,16 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"ShowAdvancedControls", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"ShowTurnSignals", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"SunnypilotStoppingController", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
 
+    // toyota specific params
+    {"ToyotaAutoHold", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaBrakeOnset", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaEnhancedBsm", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaTSS2Long", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"ToyotaDriveMode", {PERSISTENT | BACKUP, BOOL, "0"}},
+
     // MADS params
     {"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
     {"MadsMainCruiseAllowed", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -243,6 +251,10 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
 
+    // Accel Controller profiles (Eco / Normal / Sport)
+    {"AccelPersonalityEnabled", {PERSISTENT | BACKUP, BOOL, "0"}},
+    {"AccelPersonality", {PERSISTENT | BACKUP, INT, "1"}},
+
     // sunnypilot model params
     {"CameraOffset", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
     {"LagdToggle", {PERSISTENT | BACKUP, BOOL, "1"}},

openpilot/common/tests/test_params.py

@@ -117,12 +117,16 @@ class TestParams(OpenpilotTestCase):
   def test_params_default_value(self):
     self.params.remove("LanguageSetting")
     self.params.remove("LongitudinalPersonality")
+    self.params.remove("AccelPersonalityEnabled")
+    self.params.remove("AccelPersonality")
     self.params.remove("LiveParametersV2")
 
     assert self.params.get("LanguageSetting") is None
     assert self.params.get("LanguageSetting", return_default=False) is None
     assert isinstance(self.params.get("LanguageSetting", return_default=True), str)
     assert isinstance(self.params.get("LongitudinalPersonality", return_default=True), int)
+    assert self.params.get("AccelPersonalityEnabled", return_default=True) is False
+    assert self.params.get("AccelPersonality", return_default=True) == 1
     assert self.params.get("LiveParametersV2") is None
     assert self.params.get("LiveParametersV2", return_default=True) is None
 

openpilot/selfdrive/car/card.py

@@ -11,13 +11,13 @@ from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
 from openpilot.common.swaglog import cloudlog, ForwardingHandler
-
 from opendbc.car import DT_CTRL, structs
 from opendbc.car.can_definitions import CanData, CanRecvCallable, CanSendCallable
 from opendbc.car.carlog import carlog
 from opendbc.car.fw_versions import ObdCallback
 from opendbc.car.car_helpers import get_car, interfaces
 from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
+from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.helpers import convert_carControlSP, convert_to_capnp
@@ -123,6 +123,9 @@ class Car:
       self.RI = RI
 
     self.CP.alternativeExperience = 0
+    if self.params.get_bool("ToyotaAutoHold"):
+      self.CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.ALLOW_AEB
+
     # mads
     set_alternative_experience(self.CP, self.CP_SP, self.params)
     set_car_specific_params(self.CP, self.CP_SP, self.params)

openpilot/selfdrive/car/cruise.py

@@ -19,6 +19,7 @@ IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1)  # round here to avoid rounding err
 ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 CRUISE_LONG_PRESS = 50
+TOYOTA_VIRTUAL_CRUISE_LONG_PRESS = 65
 CRUISE_NEAREST_FUNC = {
   ButtonType.accelCruise: math.ceil,
   ButtonType.decelCruise: math.floor,
@@ -43,6 +44,30 @@ class VCruiseHelper(VCruiseHelperSP):
   def v_cruise_initialized(self):
     return self.v_cruise_kph != V_CRUISE_UNSET
 
+  @property
+  def software_pcm_cruise_speed(self) -> bool:
+    return self.CP.brand == "toyota" and self.CP.pcmCruise and self.CP.openpilotLongitudinalControl and not self.CP_SP.pcmCruiseSpeed
+
+  @property
+  def cruise_long_press_frames(self) -> int:
+    return TOYOTA_VIRTUAL_CRUISE_LONG_PRESS if self.software_pcm_cruise_speed else CRUISE_LONG_PRESS
+
+  @property
+  def software_pcm_cruise_initialized(self) -> bool:
+    return 0 < self.v_cruise_kph < V_CRUISE_UNSET and 0 < self.v_cruise_cluster_kph < V_CRUISE_UNSET
+
+  def _apply_software_pcm_cruise_delta(self, delta_kph: float, is_metric: bool) -> None:
+    """Move Toyota's planner/display targets together while respecting both targets' bounds."""
+    cluster_min_kph = self.v_cruise_min if is_metric else self.v_cruise_min * CV.MPH_TO_KPH
+    min_delta = max(V_CRUISE_MIN - self.v_cruise_kph, cluster_min_kph - self.v_cruise_cluster_kph)
+    max_delta = min(V_CRUISE_MAX - self.v_cruise_kph, V_CRUISE_MAX - self.v_cruise_cluster_kph)
+    if delta_kph > 0:
+      applied_delta = min(delta_kph, max(0., max_delta))
+    else:
+      applied_delta = max(delta_kph, min(0., min_delta))
+    self.v_cruise_kph = round(self.v_cruise_kph + applied_delta, 1)
+    self.v_cruise_cluster_kph = round(self.v_cruise_cluster_kph + applied_delta, 1)
+
   def update_v_cruise(self, CS, enabled, is_metric):
     self.v_cruise_kph_last = self.v_cruise_kph
 
@@ -51,11 +76,21 @@ class VCruiseHelper(VCruiseHelperSP):
     _enabled = self.update_enabled_state(CS, enabled)
 
     if CS.cruiseState.available:
-      if not self.CP.pcmCruise or (not self.CP_SP.pcmCruiseSpeed and _enabled):
+      software_pcm_enabled = not self.CP_SP.pcmCruiseSpeed and _enabled
+      if self.software_pcm_cruise_speed:
+        software_pcm_enabled = software_pcm_enabled and self.software_pcm_cruise_initialized
+
+      if not self.CP.pcmCruise or software_pcm_enabled:
         # if stock cruise is completely disabled, then we can use our own set speed logic
         self._update_v_cruise_non_pcm(CS, _enabled, is_metric)
+        v_cruise_kph_before_sla = self.v_cruise_kph
         self.update_speed_limit_assist_v_cruise_non_pcm()
-        self.v_cruise_cluster_kph = self.v_cruise_kph
+        if self.software_pcm_cruise_speed:
+          sla_delta_kph = self.v_cruise_kph - v_cruise_kph_before_sla
+          self.v_cruise_kph = v_cruise_kph_before_sla
+          self._apply_software_pcm_cruise_delta(sla_delta_kph, is_metric)
+        else:
+          self.v_cruise_cluster_kph = self.v_cruise_kph
       else:
         self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH
         self.v_cruise_cluster_kph = CS.cruiseState.speedCluster * CV.MS_TO_KPH
@@ -85,13 +120,13 @@ class VCruiseHelper(VCruiseHelperSP):
 
     for b in CS.buttonEvents:
       if b.type.raw in self.button_timers and not b.pressed:
-        if self.button_timers[b.type.raw] > CRUISE_LONG_PRESS:
+        if self.button_timers[b.type.raw] > self.cruise_long_press_frames:
           return  # end long press
         button_type = b.type.raw
         break
     else:
       for k, timer in self.button_timers.items():
-        if timer and timer % CRUISE_LONG_PRESS == 0:
+        if timer and timer % self.cruise_long_press_frames == 0:
           button_type = k
           long_press = True
           break
@@ -115,10 +150,26 @@ class VCruiseHelper(VCruiseHelperSP):
       return
 
     long_press, v_cruise_delta = VCruiseHelperSP.update_v_cruise_delta(self, long_press, v_cruise_delta)
-    if long_press and self.v_cruise_kph % v_cruise_delta != 0:  # partial interval
-      self.v_cruise_kph = CRUISE_NEAREST_FUNC[button_type](self.v_cruise_kph / v_cruise_delta) * v_cruise_delta
+    # Toyota's canonical PCM set speed and displayed cluster set speed can differ. In
+    # software-owned PCM mode, round the value the driver sees and apply the same delta
+    # to both targets so the planner/cluster calibration offset remains intact.
+    v_cruise_reference = self.v_cruise_cluster_kph if self.software_pcm_cruise_speed else self.v_cruise_kph
+    if long_press and v_cruise_reference % v_cruise_delta != 0:  # partial interval
+      v_cruise_reference_new = CRUISE_NEAREST_FUNC[button_type](v_cruise_reference / v_cruise_delta) * v_cruise_delta
     else:
-      self.v_cruise_kph += v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
+      v_cruise_reference_new = v_cruise_reference + v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
+
+    if self.software_pcm_cruise_speed:
+      delta_kph = v_cruise_reference_new - v_cruise_reference
+
+      # If SET is pressed while overriding, do not lower the target below the current speed.
+      if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
+        delta_kph = max(delta_kph, CS.vEgo * CV.MS_TO_KPH - self.v_cruise_kph)
+
+      self._apply_software_pcm_cruise_delta(delta_kph, is_metric)
+      return
+
+    self.v_cruise_kph += v_cruise_reference_new - v_cruise_reference
 
     # If set is pressed while overriding, clip cruise speed to minimum of vEgo
     if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
@@ -127,6 +178,12 @@ class VCruiseHelper(VCruiseHelperSP):
     self.v_cruise_kph = np.clip(round(self.v_cruise_kph, 1), self.v_cruise_min, V_CRUISE_MAX)
 
   def update_button_timers(self, CS, enabled):
+    if self.software_pcm_cruise_speed and (not enabled or not CS.cruiseState.available or not self.software_pcm_cruise_initialized):
+      for k in self.button_timers:
+        self.button_timers[k] = 0
+        self.button_change_states[k] = {"standstill": False, "enabled": False}
+      return
+
     # increment timer for buttons still pressed
     for k in self.button_timers:
       if self.button_timers[k] > 0:

openpilot/selfdrive/controls/controlsd.py

@@ -136,6 +136,7 @@ class Controls(ControlsExt):
     # accel PID loop
     pid_accel_limits = self.CI.get_pid_accel_limits(self.CP, self.CP_SP, CS.vEgo, CS.vCruise * CV.KPH_TO_MS)
     actuators.accel = float(self.LoC.update(CC.longActive, CS, long_plan.aTarget, long_plan.shouldStop, pid_accel_limits))
+    self.long_accel_sp(actuators, CS, long_plan, pid_accel_limits)  # sunnypilot hook
 
     # Steering PID loop and lateral MPC
     # Reset desired curvature to current to avoid violating the limits on engage

openpilot/selfdrive/controls/lib/desire_helper.py

@@ -64,16 +64,19 @@ class DesireHelper:
                          ((carstate.steeringTorque > 0 and self.lane_change_direction == LaneChangeDirection.left) or
                           (carstate.steeringTorque < 0 and self.lane_change_direction == LaneChangeDirection.right))
 
-        blindspot_detected = (((carstate.leftBlindspot or left_edge_detected) and self.lane_change_direction == LaneChangeDirection.left) or
-                              ((carstate.rightBlindspot or right_edge_detected) and self.lane_change_direction == LaneChangeDirection.right))
+        blindspot_detected = ((carstate.leftBlindspot and self.lane_change_direction == LaneChangeDirection.left) or
+                              (carstate.rightBlindspot and self.lane_change_direction == LaneChangeDirection.right))
 
-        self.alc.update_lane_change(blindspot_detected, carstate.brakePressed)
+        edge_detected = ((left_edge_detected and self.lane_change_direction == LaneChangeDirection.left) or
+                         (right_edge_detected and self.lane_change_direction == LaneChangeDirection.right))
+
+        self.alc.update_lane_change(blindspot_detected, edge_detected, carstate.brakePressed, torque_applied)
 
         if not one_blinker or below_lane_change_speed:
           self.lane_change_state = LaneChangeState.off
           self.lane_change_direction = LaneChangeDirection.none
           self.lane_change_timer = 0.0
-        elif (torque_applied or self.alc.auto_lane_change_allowed) and not blindspot_detected:
+        elif (torque_applied or self.alc.auto_lane_change_allowed) and not self.alc.lane_change_blocked:
           self.lane_change_state = LaneChangeState.laneChangeStarting
           self.lane_change_timer = 0.0
 

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -35,9 +35,12 @@ def get_max_accel(v_ego):
 def get_coast_accel(pitch):
   return np.sin(pitch) * -5.65 - 0.3  # fitted from data using xx/projects/allow_throttle/compute_coast_accel.py
 
-def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle):
-  max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
-
+def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle,
+                      max_accel_override=None):
+  if max_accel_override is not None:
+    max_accel = max_accel_override
+  else:
+    max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
   if not e2e:
     a_total_max = np.interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
     a_y = v_ego ** 2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
@@ -84,7 +87,8 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     v_ego = sm['carState'].vEgo
     v_cruise_kph = min(sm['carState'].vCruise, V_CRUISE_MAX)
     v_cruise = v_cruise_kph * CV.KPH_TO_MS
-    if sm['controlsState'].forceDecel:
+    force_decel = sm['controlsState'].forceDecel
+    if force_decel:
       v_cruise = 0.0
 
     long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
@@ -118,6 +122,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
     self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
+    self.update_dec(sm)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
     self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
@@ -140,9 +145,17 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     is_e2e = self.is_e2e(sm)
 
-    self.a_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego,
-                                     self.a_cruise, steer_angle_without_offset, self.CP, self.dt,
-                                     accel_coast, self.allow_throttle)
+    max_accel_override = self.get_max_accel_override(v_ego, sm['carStateSP'].engineOff)
+    v_cruise = self.get_cruise_target_override(v_ego, v_cruise, force_decel, accel_coast if accel_coast < 0.0 else None)
+    a_cruise_prev = self.a_cruise
+    gated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
+                                    self.CP, self.dt, accel_coast, self.allow_throttle, max_accel_override)
+    ungated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
+                                      self.CP, self.dt, accel_coast, True, max_accel_override)
+    self.a_cruise = self.arbitrate_cruise_candidate(
+      sm, gated_cruise, ungated_cruise, output_a_target_mpc, self.mpc.source,
+      allow_throttle=self.allow_throttle, e2e=is_e2e, force_decel=force_decel,
+    )
     cruise_should_stop = should_stop(v_ego, self.a_cruise)
 
     candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
@@ -153,6 +166,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
     self.output_should_stop = any(should_stop for _, _, should_stop in candidates)
     self.output_a_target = np.clip(output_a_target, ACCEL_MIN, ACCEL_MAX)
+    self.accel_controller_active = self.is_accel_controller_active(force_decel)
 
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.output_a_target + a_prev) / 2.0
 

openpilot/selfdrive/modeld/SConscript

@@ -55,7 +55,7 @@ def chestnut_action(command):
 def compile_model(onnx_path, pkl_path):
   onnx_path, target_pkl_path = File(onnx_path).abspath, File(pkl_path).abspath
   cmd = (f'{tg_flags} {mac_brew_string} {taskset}python3 "{compiler}/compile_onnx.py" '
-         f'"{onnx_path}" "{target_pkl_path}" --out-of-band --benchmark-runs 1')
+         f'"{onnx_path}" "{target_pkl_path}" --device-input "*" --out-of-band --benchmark-runs 1')
   lenv.Command(
     target_pkl_path,
     tinygrad_files + [onnx_path, Value(cmd)],

openpilot/selfdrive/modeld/helpers.py

@@ -1,11 +1,9 @@
 import io
 import pickle
 import struct
-import sys
 from pathlib import Path
 
 from openpilot.common.file_chunker import get_manifest_path
-from openpilot.common.hardware import AGNOS
 from openpilot.common.hardware.usb import CHESTNUT_USB_PRODUCT, USB_DEVICES_PATH, is_chestnut_usb_id
 
 MODELS_DIR = Path(__file__).resolve().parent / 'models'
@@ -15,14 +13,15 @@ def modeld_pkl_path(chestnut: bool):
   prefix = 'big_' if chestnut else ''
   return MODELS_DIR / f'{prefix}driving_tinygrad.pkl'
 
-def load_oob(f, chestnut=False):
-  import numpy as np
-  from tinygrad import Context, Tensor
-  device = 'USB+AMD:LLVM' if chestnut else 'QCOM' if AGNOS else 'METAL' if sys.platform == 'darwin' else 'CPU:LLVM'
-  with Context(DEV=device):
-    opcodes = f.read(struct.unpack('<q', f.read(8))[0])
-    buffers = Tensor(np.frombuffer(f.read(), np.uint8)).realize().uop.buffer
-    return type("_Unpickler", (pickle.Unpickler,), {"persistent_load": lambda self, pid: buffers.view(*pid)})(io.BytesIO(opcodes)).load()
+def load_oob(f):
+  opcodes = f.read(struct.unpack('<q', f.read(8))[0])
+  def buffers():
+    while (h := f.read(8)):
+      pb = pickle.PickleBuffer(bytearray(struct.unpack('<q', h)[0]))
+      if f.readinto(pb) != pb.raw().nbytes:
+        raise EOFError("incomplete model buffer")
+      yield pb
+  return pickle.load(io.BytesIO(opcodes), buffers=buffers())
 
 def chestnut_present() -> bool:
   for d in USB_DEVICES_PATH.glob("*"):

openpilot/selfdrive/modeld/modeld.py

@@ -134,8 +134,8 @@ class FrameMeta:
 
 
 def input_view(buffer: Buffer, shape: tuple[int, ...], dtype: DType, offset: int) -> Tensor:
-  view = buffer.view(math.prod(shape) * dtype.itemsize, offset).ensure_allocated()
-  return Tensor(UOp.from_buffer(view, dtype)).reshape(shape)
+  view = buffer.view(math.prod(shape), dtype, offset).ensure_allocated()
+  return Tensor(UOp.from_buffer(view)).reshape(shape)
 
 
 class ModelState(ModelStateBase):
@@ -143,7 +143,7 @@ class ModelState(ModelStateBase):
 
   def __init__(self, cam_w: int, cam_h: int, chestnut: bool):
     ModelStateBase.__init__(self)
-    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)), chestnut)
+    jits = load_oob(open_file_chunked(modeld_pkl_path(chestnut)))
     self.model_device = jits['input_specs']['new_img'][2]
     self.input_shapes = {name: (shape, np.dtype(dtype)) for name, (shape, dtype, _) in jits['input_specs'].items()}
     self.state_pairs = {name: f'next_{name}' for name in self.input_shapes if f'next_{name}' in jits['metadata']['output_shapes']}
@@ -230,8 +230,7 @@ def main(demo=False):
 
   CHESTNUT = chestnut_present() and chestnut_compiled()
   if CHESTNUT:
-    from tinygrad.runtime.ops_amd import AMDDevice
-    AMDDevice.wait_timeout_ms = 3000
+    os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
   params = Params()
   params.put_bool("ChestnutLoading", CHESTNUT)
   params.remove("ChestnutActive")

openpilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -11,6 +11,15 @@ from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPl
 from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
 
 
+class PlannerSM(dict):
+  def __init__(self, radar_frame: int, services: dict):
+    super().__init__(services)
+    self.frame = radar_frame
+    self.logMonoTime = {"radarState": radar_frame}
+    self.valid = {"radarState": True}
+    self.alive = {"radarState": True}
+
+
 class Plant:
   messaging_initialized = False
 
@@ -132,7 +141,7 @@ class Plant:
     car_control.carControl.orientationNED = [0., float(pitch), 0.]
 
     # ******** get controlsState messages for plotting ***
-    sm = {'radarState': radar.radarState,
+    sm = PlannerSM(self.rk.frame, {'radarState': radar.radarState,
           'carState': car_state.carState,
           'carControl': car_control.carControl,
           'controlsState': control.controlsState,
@@ -141,7 +150,7 @@ class Plant:
           'modelV2': model.modelV2,
           'carStateSP': car_state_sp.carStateSP,
           'liveMapDataSP': live_map_data_sp.liveMapDataSP,
-          'gpsLocation': gps_data.gpsLocation}
+          'gpsLocation': gps_data.gpsLocation})
     self.planner.update(sm)
     self.acceleration = self.planner.output_a_target
     if self.planner.output_should_stop:

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

@@ -27,6 +27,12 @@ DESCRIPTIONS = {
     "In relaxed mode sunnypilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with " +
     "your steering wheel distance button."
   ),
+  "AccelPersonalityEnabled": tr_noop(
+    "Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are unchanged."
+  ),
+  "AccelPersonality": tr_noop(
+    "Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive."
+  ),
   "IsLdwEnabled": tr_noop(
     "Receive alerts to steer back into the lane when your vehicle drifts over a detected lane line " +
     "without a turn signal activated while driving over 31 mph (50 km/h)."
@@ -106,6 +112,24 @@ class TogglesLayout(Widget):
       icon="speed_limit.png"
     )
 
+    self._accel_controller_enabled = toggle_item(
+      lambda: tr("Enable Accel Controller"),
+      lambda: tr(DESCRIPTIONS["AccelPersonalityEnabled"]),
+      self._params.get_bool("AccelPersonalityEnabled"),
+      callback=self._set_accel_controller_enabled,
+      icon="speed_limit.png",
+    )
+
+    self._accel_personality_setting = multiple_button_item(
+      lambda: tr("Acceleration Profile"),
+      lambda: tr(DESCRIPTIONS["AccelPersonality"]),
+      buttons=[lambda: tr("Eco"), lambda: tr("Normal"), lambda: tr("Sport")],
+      button_width=300,
+      callback=self._set_accel_personality,
+      selected_index=self._params.get("AccelPersonality", return_default=True),
+      icon="speed_limit.png"
+    )
+
     self._toggles = {}
     self._locked_toggles = set()
     for param, (title, desc, icon, needs_restart) in self._toggle_defs.items():
@@ -135,9 +159,11 @@ class TogglesLayout(Widget):
 
       self._toggles[param] = toggle
 
-      # insert longitudinal personality after NDOG toggle
+      # insert longitudinal personality and Accel Controller settings after NDOG toggle
       if param == "DisengageOnAccelerator":
         self._toggles["LongitudinalPersonality"] = self._long_personality_setting
+        self._toggles["AccelPersonalityEnabled"] = self._accel_controller_enabled
+        self._toggles["AccelPersonality"] = self._accel_personality_setting
 
     self._update_experimental_mode_icon()
     self._scroller = Scroller(list(self._toggles.values()), line_separator=True, spacing=0)
@@ -158,6 +184,7 @@ class TogglesLayout(Widget):
 
   def _update_toggles(self):
     ui_state.update_params()
+    accel_controller_enabled = self._params.get_bool("AccelPersonalityEnabled")
 
     e2e_description = tr(
       "sunnypilot defaults to driving in chill mode. Experimental mode enables alpha-level features that aren't ready for chill mode. " +
@@ -176,11 +203,15 @@ class TogglesLayout(Widget):
         self._toggles["ExperimentalMode"].action_item.set_enabled(True)
         self._toggles["ExperimentalMode"].set_description(e2e_description)
         self._long_personality_setting.action_item.set_enabled(True)
+        self._accel_controller_enabled.action_item.set_enabled(True)
+        self._accel_personality_setting.action_item.set_enabled(True)
       else:
         # no long for now
         self._toggles["ExperimentalMode"].action_item.set_enabled(False)
         self._toggles["ExperimentalMode"].action_item.set_state(False)
         self._long_personality_setting.action_item.set_enabled(False)
+        self._accel_controller_enabled.action_item.set_enabled(False)
+        self._accel_personality_setting.action_item.set_enabled(False)
         self._params.remove("ExperimentalMode")
 
         unavailable = tr("Experimental mode is currently unavailable on this car since the car's stock ACC is used for longitudinal control.")
@@ -203,6 +234,8 @@ class TogglesLayout(Widget):
     # refresh toggles from params to mirror external changes
     for param in self._toggle_defs:
       self._toggles[param].action_item.set_state(self._params.get_bool(param))
+    self._accel_controller_enabled.action_item.set_state(accel_controller_enabled)
+    self._accel_personality_setting.action_item.set_selected_button(self._params.get("AccelPersonality", return_default=True))
 
     # these toggles need restart, block while engaged
     for toggle_def in self._toggle_defs:
@@ -247,3 +280,9 @@ class TogglesLayout(Widget):
 
   def _set_longitudinal_personality(self, button_index: int):
     self._params.put("LongitudinalPersonality", button_index, block=True)
+
+  def _set_accel_personality(self, button_index: int):
+    self._params.put("AccelPersonality", button_index, block=True)
+
+  def _set_accel_controller_enabled(self, state: bool):
+    self._params.put_bool("AccelPersonalityEnabled", state, block=True)

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

@@ -14,6 +14,7 @@ from openpilot.system.ui.lib.application import gui_app
 if gui_app.sunnypilot_ui():
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.settings import SettingsLayoutSP as SettingsLayout
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.home import MiciHomeLayoutSP as MiciHomeLayout
+  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad import OnroadViewContainerSP as AugmentedRoadView
 
 ONROAD_DELAY = 2.5  # seconds
 
@@ -72,6 +73,9 @@ class MiciMainLayout(Scroller):
     # For scroll_to
     return self._body_onroad_layout if ui_state.is_body else self._car_onroad_layout
 
+  def _should_auto_scroll_to_onroad(self) -> bool:
+    return True
+
   def _setup_callbacks(self):
     self._home_layout.set_callbacks(
       on_settings=lambda: gui_app.push_widget(self._settings_layout),
@@ -122,13 +126,15 @@ class MiciMainLayout(Scroller):
 
     # FIXME: these two pops can interrupt user interacting in the settings
     if self._onroad_time_delay is not None and rl.get_time() - self._onroad_time_delay >= ONROAD_DELAY:
-      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
+        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
       self._onroad_time_delay = None
 
     # When car leaves standstill, pop nav stack and scroll to onroad
     CS = ui_state.sm["carState"]
     if not CS.standstill and self._prev_standstill:
-      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
+        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
     self._prev_standstill = CS.standstill
 
   def _on_interactive_timeout(self):

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

@@ -53,6 +53,8 @@ class TogglesLayoutMici(NavScroller):
                                                    "Set speed is a maximum, not a target.\n" +
                                                    "These are alpha features. Expect mistakes.\n" +
                                                    "The path colors show acceleration and braking.")
+    self._accel_controller_enabled = BigParamControl("enable accel controller", "AccelPersonalityEnabled")
+    self._accel_personality_toggle = BigMultiParamToggle("acceleration profile", "AccelPersonality", ["eco", "normal", "sport"])
     is_metric_toggle = BigParamControl("use metric units", "IsMetric")
     ldw_toggle = BigParamControl("lane departure warnings", "IsLdwEnabled",
                                  description="Warn when you drift across a detected lane line.\n" +
@@ -72,6 +74,8 @@ class TogglesLayoutMici(NavScroller):
 
     self._scroller.add_widgets([
       self._personality_toggle,
+      self._accel_controller_enabled,
+      self._accel_personality_toggle,
       self._experimental_btn,
       is_metric_toggle,
       ldw_toggle,
@@ -84,6 +88,7 @@ class TogglesLayoutMici(NavScroller):
     # Toggle lists
     self._refresh_toggles = (
       ("ExperimentalMode", self._experimental_btn),
+      ("AccelPersonalityEnabled", self._accel_controller_enabled),
       ("IsMetric", is_metric_toggle),
       ("IsLdwEnabled", ldw_toggle),
       ("AlwaysOnDM", always_on_dm_toggle),
@@ -123,17 +128,23 @@ class TogglesLayoutMici(NavScroller):
       if ui_state.has_longitudinal_control:
         self._experimental_btn.set_visible(True)
         self._personality_toggle.set_visible(True)
+        self._accel_controller_enabled.set_visible(True)
+        self._accel_personality_toggle.set_visible(True)
       else:
         # no long for now
         self._experimental_btn.set_visible(False)
         self._experimental_btn.set_checked(False)
         self._personality_toggle.set_visible(False)
+        self._accel_controller_enabled.set_visible(False)
+        self._accel_personality_toggle.set_visible(False)
         ui_state.params.remove("ExperimentalMode")
 
     # Refresh toggles from params to mirror external changes
     for key, item in self._refresh_toggles:
       item.set_checked(ui_state.params.get_bool(key))
 
+    self._accel_personality_toggle.refresh()
+
   def _on_experimental_mode(self, state: bool):
     if state and not ui_state.params.get_bool("ExperimentalModeConfirmed"):
       # Don't show enabled state until confirm

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

@@ -154,8 +154,8 @@ class ModelRenderer(Widget, ModelRendererSP):
       self._draw_lane_lines()
       self._draw_path(sm)
 
-    # if render_lead_indicator and radar_state:
-    #   self._draw_lead_indicator()
+    if render_lead_indicator and radar_state:
+      self._draw_lead_indicator()
 
   def _update_raw_points(self, model):
     """Update raw 3D points from model data"""

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

@@ -400,13 +400,18 @@ class BigMultiParamToggle(BigMultiToggle):
     self._load_value()
 
   def _load_value(self):
-    self.set_value(self._options[self._params.get(self._param) or 0])
+    value = self._params.get(self._param, return_default=True)
+    index = value if isinstance(value, int) else 0
+    self.set_value(self._options[max(0, min(index, len(self._options) - 1))])
 
   def _handle_mouse_release(self, mouse_pos: MousePos):
     super()._handle_mouse_release(mouse_pos)
     new_idx = self._options.index(self.value)
     self._params.put(self._param, new_idx)
 
+  def refresh(self):
+    self._load_value()
+
 
 class BigParamControl(BigToggle):
   def __init__(self, text: str, param: str, toggle_callback: Callable | None = None, *, description: str = "",

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

@@ -143,7 +143,8 @@ class CruiseLayout(Widget):
           self.icbm_toggle.show_description(True)
 
       if has_long or has_icbm:
-        self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
+        software_cruise_speed = has_long and (not ui_state.CP.pcmCruise or not ui_state.CP_SP.pcmCruiseSpeed)
+        self.custom_acc_toggle.action_item.set_enabled((software_cruise_speed or has_icbm) and ui_state.is_offroad())
         self.dec_toggle.action_item.set_enabled(has_long)
         self.scc_v_toggle.action_item.set_enabled(True)
         self.scc_m_toggle.action_item.set_enabled(True)
@@ -169,7 +170,7 @@ class CruiseLayout(Widget):
       show_custom_acc_desc = True
     else:
       if has_long or has_icbm:
-        if has_long and ui_state.CP.pcmCruise:
+        if has_long and ui_state.CP.pcmCruise and ui_state.CP_SP.pcmCruiseSpeed:
           new_custom_acc_desc = tr(ACC_PCMCRUISE_DISABLED_DESCRIPTION)
           show_custom_acc_desc = True
         else:

openpilot/selfdrive/ui/sunnypilot/layouts/settings/vehicle/brands/toyota.py

@@ -23,7 +23,7 @@ DESCRIPTIONS = {
   'stop_and_go_hack': tr_noop(
     'sunnypilot will allow some Toyota/Lexus cars to auto resume during stop and go traffic. ' +
     'This feature is only applicable to certain models that are able to use longitudinal control. This is an alpha feature. Use at your own risk.'
-  )
+  ),
 }
 
 

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

@@ -0,0 +1,19 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class MiciMainLayoutSP(MiciMainLayout):
+  def __init__(self):
+    super().__init__()
+    scroller = self._scroller
+    scroller.scroll_panel = GuiScrollPanel2SP(scroller._horizontal, handle_out_of_bounds=not scroller._snap_items)
+
+  def _should_auto_scroll_to_onroad(self) -> bool:
+    return not self._onroad_layout.is_on_info_panel()

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

@@ -0,0 +1,64 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+from collections.abc import Callable
+import pyray as rl
+from openpilot.system.ui.lib.application import gui_app
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroller_sp import ScrollerSP
+from openpilot.selfdrive.ui.sunnypilot.mici.onroad.augmented_road_view import AugmentedRoadViewSP
+from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad_info_panel import OnroadInfoPanel
+
+CONFIDENCE_BALL_VISIBLE_RATIO = 0.4
+HORIZONTAL_SETTLE_PX = 5
+HORIZONTAL_RESET_RATIO = 0.5
+
+
+class OnroadViewContainerSP(ScrollerSP):
+  def __init__(self, bookmark_callback=None):
+    super().__init__(horizontal=False, snap_items=True, spacing=0, pad=0, scroll_indicator=False, edge_shadows=False)
+    self.road_view = AugmentedRoadViewSP(bookmark_callback=bookmark_callback)
+    self.onroad_info_panel = OnroadInfoPanel(bookmark_callback=bookmark_callback)
+
+    self._scroller.add_widgets([
+      self.road_view,
+      self.onroad_info_panel,
+    ])
+    self._scroller.set_reset_scroll_at_show(False)
+    self._scroller.set_scrolling_enabled(lambda: abs(self.rect.x) < HORIZONTAL_SETTLE_PX)
+
+    for child in (self.road_view, self.onroad_info_panel):
+      inner_touch_valid = child._touch_valid_callback
+      child.set_touch_valid_callback(
+        lambda inner=inner_touch_valid: self._touch_valid() and (inner() if inner else True)
+      )
+
+  def set_rect(self, rect: rl.Rectangle):
+    super().set_rect(rect)
+    self.road_view.set_rect(rect)
+    self.onroad_info_panel.set_rect(rect)
+    return self
+
+  def is_swiping_left(self) -> bool:
+    return self.road_view.is_swiping_left() or self.onroad_info_panel.is_swiping_left()
+
+  def set_click_callback(self, click_callback: Callable[[], None] | None) -> None:
+    self.road_view.set_click_callback(click_callback)
+    self.onroad_info_panel.set_click_callback(click_callback)
+
+  def is_on_info_panel(self) -> bool:
+    """True when scrolled past halfway toward onroad_info_panel (used by main layout
+    to skip auto-pop-back-to-camera while user is reading the info panel)."""
+    return abs(self._scroller.scroll_panel.get_offset()) > self._rect.height / 2
+
+  def _render(self, rect: rl.Rectangle):
+    if abs(self.rect.x) > gui_app.width * HORIZONTAL_RESET_RATIO:
+      self._scroller.scroll_panel.set_offset(0)
+
+    vertical_offset = self._scroller.scroll_panel.get_offset()
+    show_ball = abs(vertical_offset) < rect.height * CONFIDENCE_BALL_VISIBLE_RATIO
+    self.road_view.set_show_confidence_ball(show_ball)
+
+    super()._render(rect)

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

@@ -0,0 +1,403 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import pyray as rl
+from dataclasses import dataclass, field
+from openpilot.common.constants import CV
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.selfdrive.ui.ui_state import ui_state
+from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
+from openpilot.system.ui.lib.multilang import tr
+from openpilot.system.ui.lib.text_measure import measure_text_cached
+from openpilot.system.ui.widgets import Widget
+from openpilot.selfdrive.ui.mici.onroad.alert_renderer import AlertRenderer
+from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import BookmarkIcon
+
+METER_TO_KM = 0.001
+METER_TO_MILE = 0.000621371
+
+CONTENT_MARGIN = 16
+SPEED_LIMIT_SIGN_WIDTH = 146
+VIENNA_SIGN_SIZE = 146
+MUTCD_SIGN_HEIGHT = 178
+OFFSET_BADGE_SIZE = 50
+OFFSET_BADGE_PANEL_PADDING = 4
+MUTCD_OFFSET_SIGN_Y_SHIFT = 6
+VIENNA_BADGE_X_RATIO = 0.80
+VIENNA_BADGE_UPCOMING_X_RATIO = 0.70
+VIENNA_BADGE_Y_RATIO = -0.82
+UPCOMING_SIGN_SIZE_RATIO = 0.76
+UPCOMING_SIGN_OVERLAP_RATIO = 0.05
+UNIT_FONT_SIZE = 40
+SPEED_FONT_SIZE = 114
+ROAD_FONT_SIZE = 32
+SCC_TAG_WIDTH = 78
+SCC_TAG_HEIGHT = 30
+SCC_TAG_GAP = 5
+COLUMN_GAP = 12
+
+
+@dataclass(frozen=True)
+class OnroadInfoPanelColors:
+  white: rl.Color = rl.WHITE
+  black: rl.Color = rl.BLACK
+  red: rl.Color = field(default_factory=lambda: rl.Color(255, 0, 0, 255))
+  green: rl.Color = field(default_factory=lambda: rl.Color(0, 255, 0, 255))
+  grey: rl.Color = field(default_factory=lambda: rl.Color(190, 195, 190, 255))
+  light_grey: rl.Color = field(default_factory=lambda: rl.Color(200, 200, 200, 255))
+  dark_grey: rl.Color = field(default_factory=lambda: rl.Color(100, 100, 100, 255))
+  bg_dark: rl.Color = field(default_factory=lambda: rl.Color(0, 0, 0, 255))
+  card_bg: rl.Color = field(default_factory=lambda: rl.Color(50, 50, 50, 200))
+  badge_bg: rl.Color = field(default_factory=lambda: rl.Color(60, 60, 60, 255))
+
+
+COLORS = OnroadInfoPanelColors()
+
+
+class OnroadInfoPanel(Widget):
+  def __init__(self, bookmark_callback=None):
+    super().__init__()
+    self.speed_limit: float = 0.0
+    self.speed_limit_valid: bool = False
+    self.speed_limit_offset: float = 0.0
+    self.next_speed_limit: float = 0.0
+    self.next_speed_limit_distance: float = 0.0
+    self.road_name: str = ""
+    self.current_speed: float = 0.0
+    self.set_speed: float = 0.0
+    self.cruise_enabled: bool = False
+
+    self._sign_slide: float = 0.0
+
+    self._font_bold: rl.Font = gui_app.font(FontWeight.BOLD)
+    self._font_semi_bold: rl.Font = gui_app.font(FontWeight.SEMI_BOLD)
+    self._font_medium: rl.Font = gui_app.font(FontWeight.MEDIUM)
+
+    self._marquee_offset: float = 0.0
+    self._marquee_direction: int = 1
+    self._marquee_pause_timer: float = 0.0
+    self._marquee_speed: float = 40.0
+    self._marquee_pause_duration: float = 1.5
+
+    self._alert_renderer = AlertRenderer()
+    self._alert_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
+
+    self._bookmark_icon = BookmarkIcon(bookmark_callback)
+
+  def is_swiping_left(self) -> bool:
+    return self._bookmark_icon.is_swiping_left()
+
+  def _handle_mouse_release(self, mouse_pos: MousePos) -> None:
+    # Mirror stock AugmentedRoadView: suppress click while bookmark gesture active
+    if not self._bookmark_icon.interacting():
+      super()._handle_mouse_release(mouse_pos)
+
+  def _update_state(self) -> None:
+    sm = ui_state.sm
+    speed_conv = CV.MS_TO_KPH if ui_state.is_metric else CV.MS_TO_MPH
+
+    if sm.valid["longitudinalPlanSP"]:
+      lp_sp = sm["longitudinalPlanSP"]
+      resolver = lp_sp.speedLimit.resolver
+      self.speed_limit = resolver.speedLimit * speed_conv
+      self.speed_limit_valid = resolver.speedLimitValid
+      self.speed_limit_offset = resolver.speedLimitOffset * speed_conv
+
+    if sm.valid["liveMapDataSP"]:
+      lmd = sm["liveMapDataSP"]
+      self.next_speed_limit = lmd.speedLimitAhead * speed_conv
+      self.next_speed_limit_distance = lmd.speedLimitAheadDistance
+      self.road_name = lmd.roadName
+
+    if sm.updated["carState"]:
+      self.current_speed = sm["carState"].vEgo * speed_conv
+
+    if sm.valid["carState"] and sm.valid["controlsState"]:
+      self.cruise_enabled = sm["carState"].cruiseState.enabled
+      v_cruise_cluster = sm["carState"].vCruiseCluster
+      set_speed_kph = sm["controlsState"].vCruiseDEPRECATED if v_cruise_cluster == 0.0 else v_cruise_cluster
+      self.set_speed = set_speed_kph * (METER_TO_MILE / METER_TO_KM) if not ui_state.is_metric else set_speed_kph
+
+  def _render(self, rect: rl.Rectangle) -> None:
+    self._update_state()
+
+    rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), COLORS.bg_dark)
+
+    left_x = rect.x + CONTENT_MARGIN
+
+    if self.cruise_enabled:
+      unit = tr("MAX")
+      display_speed = self.set_speed
+    else:
+      unit = tr("km/h") if ui_state.is_metric else tr("MPH")
+      display_speed = self.current_speed
+
+    display_speed_text = str(round(display_speed))
+    if self.speed_limit_valid and display_speed > self.speed_limit:
+      speed_color = COLORS.red
+    else:
+      speed_color = COLORS.white
+
+    sign_width = min(SPEED_LIMIT_SIGN_WIDTH, rect.width * 0.30)
+    sign_height = VIENNA_SIGN_SIZE if ui_state.is_metric else MUTCD_SIGN_HEIGHT
+
+    has_upcoming_limit = self.next_speed_limit > 0 and self.next_speed_limit != self.speed_limit
+    target_sign_slide = 1.0 if has_upcoming_limit else 0.0
+    slide_speed = 3.0 * rl.get_frame_time()
+    if self._sign_slide < target_sign_slide:
+      self._sign_slide = min(self._sign_slide + slide_speed, target_sign_slide)
+    elif self._sign_slide > target_sign_slide:
+      self._sign_slide = max(self._sign_slide - slide_speed, target_sign_slide)
+
+    upcoming_width = int(sign_width * UPCOMING_SIGN_SIZE_RATIO)
+    upcoming_height = int(sign_height * UPCOMING_SIGN_SIZE_RATIO)
+    upcoming_reserved_width = int(upcoming_width * 0.85) + 5
+    sign_x_without_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN
+    sign_x_with_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN - upcoming_reserved_width
+    sign_x = sign_x_without_upcoming + (sign_x_with_upcoming - sign_x_without_upcoming) * self._sign_slide
+    sign_y = rect.y + (rect.height - sign_height) / 2
+    if not ui_state.is_metric and self.speed_limit_offset != 0 and self.speed_limit_valid:
+      sign_y += MUTCD_OFFSET_SIGN_Y_SHIFT
+
+    readout_right = sign_x - COLUMN_GAP
+    readout_width = max(1, readout_right - left_x)
+    road_y = rect.y + rect.height - 44
+
+    unit_font_size = self._fit_font_size(self._font_semi_bold, unit, readout_width, 46, UNIT_FONT_SIZE, 28)
+    speed_font_size = self._fit_font_size(self._font_bold, display_speed_text, readout_width, road_y - (rect.y + 54) - 8,
+                                          SPEED_FONT_SIZE, 76)
+    speed_size = measure_text_cached(self._font_bold, display_speed_text, speed_font_size)
+    speed_y = min(rect.y + 54, road_y - speed_size.y - 8)
+    unit_y = max(rect.y + 14, speed_y - unit_font_size - 6)
+
+    rl.draw_text_ex(self._font_semi_bold, unit, rl.Vector2(left_x, unit_y), unit_font_size, 0, COLORS.grey)
+    rl.draw_text_ex(self._font_bold, display_speed_text, rl.Vector2(left_x, speed_y), speed_font_size, 0, speed_color)
+    self._draw_road_name(left_x, road_y, readout_width)
+
+    if has_upcoming_limit and self._sign_slide > 0.01:
+      upcoming_speed_text = str(round(self.next_speed_limit))
+      distance_text = self._format_distance(self.next_speed_limit_distance)
+      upcoming_x = sign_x + sign_width - int(upcoming_width * UPCOMING_SIGN_OVERLAP_RATIO)
+      upcoming_y = sign_y + (sign_height - upcoming_height) / 2
+
+      upcoming_speed_color = COLORS.black
+      if ui_state.is_metric:
+        self._draw_vienna_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
+      else:
+        self._draw_mutcd_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
+
+      distance_font_size = self._fit_font_size(self._font_medium, distance_text, upcoming_width, 30, 24, 16)
+      distance_size = measure_text_cached(self._font_medium, distance_text, distance_font_size)
+      rl.draw_text_ex(self._font_medium, distance_text, rl.Vector2(upcoming_x + upcoming_width / 2 - distance_size.x / 2, upcoming_y + upcoming_height),
+                      distance_font_size, 0, COLORS.grey)
+
+    self._draw_speed_limit_sign(sign_x, sign_y, sign_width, sign_height)
+
+    if self.speed_limit_offset != 0 and self.speed_limit_valid:
+      offset_text = str(abs(round(self.speed_limit_offset)))
+      badge_size = OFFSET_BADGE_SIZE
+      badge_rect = self._offset_badge_rect(rect, sign_x, sign_y, sign_width, sign_height, badge_size, has_upcoming_limit)
+
+      if ui_state.is_metric:
+        badge_radius = badge_size / 2
+        badge_center_x = badge_rect.x + badge_radius
+        badge_center_y = badge_rect.y + badge_radius
+        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius + 2, COLORS.dark_grey)
+        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius, COLORS.badge_bg)
+        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_center_x, badge_center_y), COLORS.white,
+                                     badge_size - 10, badge_size - 8, min_size=24)
+      else:
+        rl.draw_rectangle_rounded(badge_rect, 0.25, 10, COLORS.badge_bg)
+        rl.draw_rectangle_rounded_lines_ex(badge_rect, 0.25, 10, 2, COLORS.dark_grey)
+        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_rect.x + badge_size / 2, badge_rect.y + badge_size / 2),
+                                     COLORS.white, badge_size - 10, badge_size - 8, min_size=24)
+
+    scc_tag_x = min(left_x + speed_size.x + COLUMN_GAP, readout_right - SCC_TAG_WIDTH)
+    scc_tag_y = speed_y + (speed_size.y - (SCC_TAG_HEIGHT * 2 + SCC_TAG_GAP)) / 2
+    if scc_tag_x >= left_x + speed_size.x + 8:
+      self._draw_scc_icons(scc_tag_x, scc_tag_y, readout_right)
+
+    self._bookmark_icon.render(rect)
+
+    if ui_state.started:
+      alert_obj, no_alert = self._alert_renderer.will_render()
+      self._alert_alpha_filter.update(0 if no_alert else 1)
+      alpha = self._alert_alpha_filter.x
+      if alpha > 0.01:
+        rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), rl.Color(0, 0, 0, int(150 * alpha)))
+      self._alert_renderer.render(rect)
+
+  def _draw_scc_icons(self, x: float, y: float, right_limit: float) -> None:
+    sm = ui_state.sm
+    if not sm.valid["longitudinalPlanSP"]:
+      return
+    scc = sm["longitudinalPlanSP"].smartCruiseControl
+
+    drawn = 0
+
+    for label, active in [("SCC-V", scc.vision.active), ("SCC-M", scc.map.active)]:
+      if not active:
+        continue
+      tag_x = x
+      if tag_x + SCC_TAG_WIDTH > right_limit:
+        return
+      tag_y = y + drawn * (SCC_TAG_HEIGHT + SCC_TAG_GAP)
+      rl.draw_rectangle_rounded(rl.Rectangle(tag_x, tag_y, SCC_TAG_WIDTH, SCC_TAG_HEIGHT), 0.3, 10, COLORS.green)
+      self._draw_text_centered_fit(self._font_bold, label, 18, rl.Vector2(tag_x + SCC_TAG_WIDTH / 2, tag_y + SCC_TAG_HEIGHT / 2), COLORS.black,
+                                   SCC_TAG_WIDTH - 10, SCC_TAG_HEIGHT - 4, min_size=14)
+      drawn += 1
+
+  def _draw_speed_limit_sign(self, x: float, y: float, sign_width: float, sign_height: float) -> None:
+    speed_str = str(round(self.speed_limit)) if self.speed_limit_valid and self.speed_limit > 0 else "--"
+    speed_color = COLORS.black if not self.speed_limit_valid or self.current_speed <= self.speed_limit else COLORS.red
+
+    if ui_state.is_metric:
+      self._draw_vienna_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
+    else:
+      self._draw_mutcd_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
+
+  def _draw_road_name(self, x: float, y: float, width: float) -> None:
+    if width <= 0:
+      return
+
+    road_display = self.road_name if self.road_name else "--"
+    font_size = self._fit_font_size(self._font_semi_bold, road_display, width, 38, ROAD_FONT_SIZE, 28)
+    road_size = measure_text_cached(self._font_semi_bold, road_display, font_size)
+    text_width = road_size.x
+
+    if text_width <= width:
+      self._marquee_offset = 0.0
+      self._marquee_direction = 1
+      self._marquee_pause_timer = 0.0
+      rl.draw_text_ex(self._font_semi_bold, road_display, rl.Vector2(x, y), font_size, 0, COLORS.white)
+    else:
+      overflow = text_width - width
+      dt = rl.get_frame_time()
+
+      if self._marquee_pause_timer > 0:
+        self._marquee_pause_timer -= dt
+      else:
+        self._marquee_offset += self._marquee_direction * self._marquee_speed * dt
+
+        if self._marquee_offset >= overflow:
+          self._marquee_offset = overflow
+          self._marquee_direction = -1
+          self._marquee_pause_timer = self._marquee_pause_duration
+        elif self._marquee_offset <= 0:
+          self._marquee_offset = 0
+          self._marquee_direction = 1
+          self._marquee_pause_timer = self._marquee_pause_duration
+
+      rl.begin_scissor_mode(int(x), int(y), int(width), int(road_size.y + 4))
+      text_pos = rl.Vector2(x - self._marquee_offset, y)
+      rl.draw_text_ex(self._font_semi_bold, road_display, text_pos, font_size, 0, COLORS.white)
+      rl.end_scissor_mode()
+
+  def _draw_vienna_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
+    center = rl.Vector2(x + width / 2, y + height / 2)
+    outer_radius = min(width, height) / 2
+
+    rl.draw_circle_v(center, outer_radius, COLORS.white)
+    ring_width = outer_radius * 0.18
+    rl.draw_ring(center, outer_radius - ring_width, outer_radius, 0, 360, 36, COLORS.red)
+
+    font_size = outer_radius * (0.7 if len(speed_str) >= 3 else 0.9)
+    self._draw_text_centered_fit(self._font_bold, speed_str, int(font_size), center, speed_color, width * 0.72, height * 0.50, min_size=24)
+
+  def _draw_mutcd_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
+    sign_rect = rl.Rectangle(x, y, width, height)
+    rl.draw_rectangle_rounded(sign_rect, 0.35, 10, COLORS.white)
+
+    inset = max(4, width * 0.05)
+    inner_rect = rl.Rectangle(x + inset, y + inset, width - inset * 2, height - inset * 2)
+    outer_radius = 0.35 * width / 2.0
+    inner_radius = outer_radius - inset
+    inner_roundness = inner_radius / (inner_rect.width / 2.0)
+    rl.draw_rectangle_rounded_lines_ex(inner_rect, inner_roundness, 10, 3, COLORS.black)
+
+    mid_x = x + width / 2
+    label_size = max(18, int(width * 0.26))
+    if is_upcoming:
+      self._draw_text_centered_fit(self._font_bold, tr("AHEAD"), int(width * 0.34), rl.Vector2(mid_x, y + height * 0.28), COLORS.black,
+                                   width * 0.94, height * 0.32, min_size=20)
+    else:
+      self._draw_text_centered_fit(self._font_bold, tr("SPEED"), label_size, rl.Vector2(mid_x, y + height * 0.20), COLORS.black,
+                                   width * 0.84, height * 0.24, min_size=16)
+      self._draw_text_centered_fit(self._font_bold, tr("LIMIT"), label_size, rl.Vector2(mid_x, y + height * 0.40), COLORS.black,
+                                   width * 0.84, height * 0.24, min_size=16)
+
+    speed_font_size = int(width * 0.60) if len(speed_str) >= 3 else int(width * 0.72)
+    self._draw_text_centered_fit(self._font_bold, speed_str, speed_font_size, rl.Vector2(mid_x, y + height * 0.72), speed_color,
+                                 width * 0.90, height * 0.52, min_size=32)
+
+  def _draw_text_centered(self, font, text, size, pos_center, color):
+    sz = measure_text_cached(font, text, size)
+    rl.draw_text_ex(font, text, rl.Vector2(pos_center.x - sz.x / 2, pos_center.y - sz.y / 2), size, 0, color)
+
+  def _draw_text_centered_fit(self, font, text, size, pos_center, color, max_width: float, max_height: float, min_size: int = 10):
+    size = self._fit_font_size(font, text, max_width, max_height, size, min_size)
+    self._draw_text_centered(font, text, size, pos_center, color)
+
+  def _fit_font_size(self, font, text: str, max_width: float, max_height: float, max_size: int | float, min_size: int) -> int:
+    size = int(max_size)
+    while size > min_size:
+      text_size = measure_text_cached(font, text, size)
+      if text_size.x <= max_width and text_size.y <= max_height:
+        return size
+      size -= 2
+    return min_size
+
+  def _offset_badge_rect(self, panel_rect: rl.Rectangle, sign_x: float, sign_y: float, sign_width: float, sign_height: float,
+                         badge_size: float, has_upcoming_limit: bool) -> rl.Rectangle:
+    if ui_state.is_metric:
+      radius = min(sign_width, sign_height) / 2
+      center_x = sign_x + sign_width / 2
+      center_y = sign_y + sign_height / 2
+      badge_x_ratio = VIENNA_BADGE_UPCOMING_X_RATIO if has_upcoming_limit else VIENNA_BADGE_X_RATIO
+      badge_center_x = center_x + radius * badge_x_ratio
+      badge_center_y = center_y + radius * VIENNA_BADGE_Y_RATIO
+      badge_x = badge_center_x - badge_size / 2
+      badge_y = badge_center_y - badge_size / 2
+    else:
+      badge_x = sign_x + sign_width - badge_size * 0.45
+      badge_y = sign_y - badge_size * 0.75
+
+    return rl.Rectangle(
+      self._clamp(
+        badge_x,
+        panel_rect.x + OFFSET_BADGE_PANEL_PADDING,
+        panel_rect.x + panel_rect.width - badge_size - OFFSET_BADGE_PANEL_PADDING,
+      ),
+      self._clamp(
+        badge_y,
+        panel_rect.y + OFFSET_BADGE_PANEL_PADDING,
+        panel_rect.y + panel_rect.height - badge_size - OFFSET_BADGE_PANEL_PADDING,
+      ),
+      badge_size,
+      badge_size,
+    )
+
+  @staticmethod
+  def _clamp(value: float, min_value: float, max_value: float) -> float:
+    return max(min_value, min(max_value, value))
+
+  def _format_distance(self, distance: float) -> str:
+    if ui_state.is_metric:
+      if distance < 50:
+        return tr("Near")
+      if distance >= 1000:
+        return f"{distance * METER_TO_KM:.1f}" + tr("km")
+      if distance < 200:
+        rounded = max(10, int(distance / 10) * 10)
+      else:
+        rounded = int(distance / 100) * 100
+      return str(rounded) + tr("m")
+    else:
+      distance_mi = distance * METER_TO_MILE
+      if distance_mi < 0.1:
+        return tr("Near")
+      return f"{distance_mi:.1f}" + tr("mi")

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

@@ -0,0 +1,29 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import AugmentedRoadView
+
+
+class _SuppressedConfidenceBall:
+  def render(self, *_):
+    pass
+
+
+class AugmentedRoadViewSP(AugmentedRoadView):
+  def __init__(self, **kwargs):
+    super().__init__(**kwargs)
+    self._show_confidence_ball: bool = True
+    self._real_confidence_ball = self._confidence_ball
+    self._confidence_ball = _SuppressedConfidenceBall()
+
+  def set_show_confidence_ball(self, show: bool) -> None:
+    self._show_confidence_ball = show
+
+  def _render(self, _) -> None:
+    super()._render(_)
+    if self._show_confidence_ball:
+      self._real_confidence_ball.render(self.rect)

openpilot/selfdrive/ui/sunnypilot/mici/tests/test_scroller_sp.py

@@ -0,0 +1,83 @@
+import pyray as rl
+
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.system.ui.lib.application import MouseEvent, MousePos, gui_app
+from openpilot.system.ui.lib.scroll_panel2 import ScrollState
+from openpilot.system.ui.widgets import Widget
+from openpilot.system.ui.widgets import scroller as scroller_mod
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class DummyScrollIndicator:
+  def update(self, *_) -> None:
+    pass
+
+  def render(self) -> None:
+    pass
+
+
+class DummyWidget(Widget):
+  def __init__(self, rect: rl.Rectangle):
+    super().__init__()
+    self.set_rect(rect)
+
+  def _render(self, _) -> None:
+    pass
+
+
+def _mouse_event(x: float, y: float, *, pressed: bool = False, released: bool = False,
+                 down: bool = True, t: float = 0.0) -> MouseEvent:
+  return MouseEvent(MousePos(x, y), 0, pressed, released, down, t)
+
+
+class TestScrollerSP(OpenpilotTestCase):
+  def test_vertical_snap_items_are_supported(self, monkeypatch):
+    monkeypatch.setattr(scroller_mod, "ScrollIndicator", DummyScrollIndicator)
+
+    scroller = scroller_mod._Scroller([], horizontal=False, snap_items=True, scroll_indicator=False)
+    scroller.set_rect(rl.Rectangle(0, 0, 100, 100))
+    scroller.scroll_panel.set_offset(-60)
+
+    captured_snap_target = None
+
+    def update(_, __, snap_target=None):
+      nonlocal captured_snap_target
+      captured_snap_target = snap_target
+      return scroller.scroll_panel.get_offset()
+
+    monkeypatch.setattr(scroller.scroll_panel, "update", update)
+
+    visible_items: list[Widget] = [
+      DummyWidget(rl.Rectangle(0, -60, 100, 100)),
+      DummyWidget(rl.Rectangle(0, 40, 100, 100)),
+    ]
+    scroller._get_scroll(visible_items, 200)
+
+    assert captured_snap_target == -100
+
+  def test_scroll_panel_sp_rejects_orthogonal_drags(self, monkeypatch):
+    panel = GuiScrollPanel2SP(horizontal=True)
+    bounds = rl.Rectangle(0, 0, 100, 100)
+
+    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(10, 10, pressed=True, t=1.0)])
+    panel.update(bounds, 200)
+    assert panel.state == ScrollState.PRESSED
+
+    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(23, 60, t=1.1)])
+    panel.update(bounds, 200)
+
+    assert panel.state == ScrollState.STEADY
+    assert panel.get_offset() == 0
+
+  def test_scroll_panel_sp_can_disable_out_of_bounds_handling(self, monkeypatch):
+    panel = GuiScrollPanel2SP(horizontal=False, handle_out_of_bounds=False)
+    bounds = rl.Rectangle(0, 0, 100, 100)
+    monkeypatch.setattr(gui_app, "_mouse_events", [])
+
+    panel.set_offset(20)
+    panel.update(bounds, 200)
+    assert panel.get_offset() == 0
+
+    panel.set_offset(-150)
+    panel.update(bounds, 200)
+    assert panel.get_offset() == -100

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroll_panel_sp.py

@@ -0,0 +1,33 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import pyray as rl
+from openpilot.system.ui.lib.application import MouseEvent
+from openpilot.system.ui.lib.scroll_panel2 import GuiScrollPanel2, ScrollState
+
+
+class GuiScrollPanel2SP(GuiScrollPanel2):
+  """Scroll panel behavior for nested Mici pagers."""
+
+  def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
+    super().__init__(horizontal, handle_out_of_bounds=handle_out_of_bounds)
+
+  def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
+                          content_size: float) -> None:
+    state_before_update = self._state
+    super()._handle_mouse_event(mouse_event, bounds, bounds_size, content_size)
+
+    if self._state == ScrollState.MANUAL_SCROLL and state_before_update == ScrollState.PRESSED and \
+       self._initial_click_event is not None:
+      drag_x = abs(mouse_event.pos.x - self._initial_click_event.pos.x)
+      drag_y = abs(mouse_event.pos.y - self._initial_click_event.pos.y)
+      primary_drag = drag_x if self._horizontal else drag_y
+      cross_drag = drag_y if self._horizontal else drag_x
+      if cross_drag > primary_drag:
+        self._state = ScrollState.STEADY
+        self._velocity = 0.0
+        self._velocity_buffer.clear()

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroller_sp.py

@@ -0,0 +1,16 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from openpilot.system.ui.widgets.scroller import Scroller
+from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
+
+
+class ScrollerSP(Scroller):
+  def __init__(self, **kwargs):
+    super().__init__(**kwargs)
+    inner = self._scroller
+    inner.scroll_panel = GuiScrollPanel2SP(inner._horizontal, handle_out_of_bounds=not inner._snap_items)

openpilot/selfdrive/ui/ui.py

@@ -10,6 +10,9 @@ from openpilot.selfdrive.ui.layouts.main import MainLayout
 from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
 from openpilot.selfdrive.ui.ui_state import ui_state
 
+if gui_app.sunnypilot_ui():
+  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.main import MiciMainLayoutSP as MiciMainLayout
+
 BIG_UI = gui_app.big_ui()
 
 

openpilot/sunnypilot/modeld_v2/compile_modeld.py

@@ -7,12 +7,14 @@ See the LICENSE.md file in the root directory for more details.
 """
 
 import argparse
+import atexit
 import codecs
 import gc
 import math
 import multiprocessing as mp
 import os
 import pickle
+import shutil
 import tempfile
 import time
 from functools import partial
@@ -20,8 +22,8 @@ from typing import Any
 
 import numpy as np
 
-from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, read_parts, write_bundle
-from openpilot.sunnypilot.modeld_v2.plain_artifact_compiler import capture_frame, record_kernel_linear, serialize_jit
+from openpilot.common.file_chunker import chunk_file, get_chunk_targets, open_file_chunked
+from openpilot.sunnypilot.modeld_v2.helpers import dump_oob, load_oob
 import openpilot.sunnypilot.modeld_v2.stock_dependencies as stock
 from openpilot.system.camerad.cameras.nv12_info import get_nv12_info
 
@@ -53,6 +55,16 @@ def _patch_tinygrad_fetch_fw():
     pass
 _patch_tinygrad_fetch_fw()
 
+def _patch_ops_serialization():
+  try:
+    from tinygrad.uop.ops import Ops
+    def __reduce_ex__(self, proto):
+      return (getattr, (self.__class__, self.name))
+    Ops.__reduce_ex__ = __reduce_ex__
+  except ImportError:
+    pass
+_patch_ops_serialization()
+
 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']
@@ -60,7 +72,6 @@ POLICY_INPUTS = ['img_q', 'big_img_q', 'feat_q', 'desire_q', 'packed_npy_inputs'
 class MetadataOnnxPBParser(OnnxPBParser):
   def _parse_ModelProto(self) -> dict:
     obj: dict[str, Any] = {"graph": {"input": [], "output": []}, "metadata_props": []}
-    self.opset_imports = {}
     for fid, wire_type in self._parse_message(self.reader.len):
       match fid:
         case 7:
@@ -139,10 +150,6 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
   return shapes, sizes
 
 
-def host_view(tensor: Tensor) -> np.ndarray: # QCOM -> CPU round trip of tfm takes 5ms longer than host memory view
-  return np.frombuffer(tensor._buffer()._host_mv(), dtype=np.float32).reshape(tensor.shape)
-
-
 def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = Device.DEFAULT,
                             is_supercombo: bool = False) -> tuple[dict, dict]:
   road_key, _ = _detect_vision_keys(input_shapes)
@@ -178,7 +185,7 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
     'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
     'desire_q': Tensor(np.zeros((frame_skip * desire_shape[1], desire_shape[0], desire_shape[2]),
                   dtype=np.float32), device=device).contiguous().realize(),
-    'packed_npy_inputs': Tensor(packed_npy_inputs, device=device).realize(),
+    'packed_npy_inputs': Tensor(packed_npy_inputs, device=device if os.getenv('CHESTNUT') else 'NPY').realize(),
   }
 
   if features_buffer:
@@ -190,11 +197,9 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
   for key in ('tfm', 'big_tfm'):
     if key not in npy_arrays:
       npy_arrays[key] = np.eye(3, dtype=np.float32)
-    queues[key] = Tensor(npy_arrays[key], device=device).realize()
+    queues[key] = Tensor(npy_arrays[key], device='NPY').realize()
 
-  packed = host_view(queues['packed_npy_inputs'])
-  npy_arrays |= {k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed, split_indices) if sizes else [], strict=True)}
-  return queues, npy_arrays | {k: host_view(queues[k]) for k in ('tfm', 'big_tfm')}
+  return queues, npy_arrays
 
 
 def make_split_input_queues(vision_input_shapes: dict, policy_input_shapes: dict,
@@ -216,8 +221,8 @@ def make_warp_queues(device=Device.DEFAULT):
     'tfm': np.zeros((3, 3), dtype=np.float32),
     'big_tfm': np.zeros((3, 3), dtype=np.float32),
   }
-  queues = {k: Tensor(v, device=device).realize() for k, v in npy.items()}
-  return queues, {k: host_view(v) for k, v in queues.items()}
+  queues = {k: Tensor(v, device='NPY').realize() for k, v in npy.items()}
+  return queues, npy
 
 
 def make_run_policy(vision_runner, policy_runners: list, features_slice: slice, frame_skip: int, input_shapes: dict):
@@ -277,19 +282,8 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
   return run_policy
 
 
-class _CheckFrameRecorder:
-  def __init__(self, jit):
-    self.jit, self.frame = jit, None
-
-  def __call__(self, *args, **kwargs):
-    if self.frame is not None or args or self.jit.cnt < 2:
-      return self.jit(*args, **kwargs)
-    self.frame, result = capture_frame(self.jit, kwargs, None)
-    return result
-
-
 def compile_jit(jit_or_fn, input_keys_or_make_inputs, make_queues=None, make_random_inputs=None,
-                benchmark_runs: int = 1, clear_refs=None):
+                benchmark_runs: int = 1, clear_refs=None, return_loaded: bool = True):
   if callable(input_keys_or_make_inputs) and make_queues is None:
     fn = jit_or_fn
     make_inputs = input_keys_or_make_inputs
@@ -340,23 +334,22 @@ def compile_jit(jit_or_fn, input_keys_or_make_inputs, make_queues=None, make_ran
 
   print('capture + replay')
   gc.collect()
-  recorder = _CheckFrameRecorder(jit)
-  with record_kernel_linear() as recorded:
-    test_val = run_eval(recorder, 42, 3)
-  assert len(recorded) == 1, f"expected one captured kernel list, got {len(recorded)}"
-  part = serialize_jit(jit, recorded[0], recorder.frame)
-  print(f'plain artifact round trip ({benchmark_runs} runs per seed)')
-  if clear_refs:
-    clear_refs()
-  gc.collect()
-  loaded_jit = PlainJit(part[0], memoryview(part[1]))
+  test_val = run_eval(jit, 42, 3)
+  print(f'pickle round trip ({benchmark_runs} runs per seed)')
+  with tempfile.TemporaryFile(dir=".") as f:
+    dump_oob(jit, f)
+    if clear_refs:
+      clear_refs()
+    gc.collect()
+    f.seek(0)
+    loaded_jit = load_oob(f)
 
   for seed in (42, 43):
     reference = test_val if seed == 42 else run_eval(jit_or_fn, seed, 1)
     actual = run_eval(loaded_jit, seed, benchmark_runs)
     for ref, val in zip(reference, actual, strict=True):
       np.testing.assert_array_equal(ref, val)
-  return part
+  return loaded_jit if return_loaded else jit
 
 
 def _parse_size(size_str: str) -> tuple[int, int]:
@@ -364,6 +357,16 @@ def _parse_size(size_str: str) -> tuple[int, int]:
   return int(width), int(height)
 
 
+def read_file_chunked_to_disk(path):
+  if not path:
+    return None
+  tmp_path = f'{path}.unchunked'
+  with open(tmp_path, 'wb') as f, open_file_chunked(path) as src:
+    shutil.copyfileobj(src, f)
+  atexit.register(lambda: os.path.exists(tmp_path) and os.remove(tmp_path))
+  return tmp_path
+
+
 def _load_policy_runners(args: argparse.Namespace) -> tuple[list, list]:
   runners, keys = [], []
   for name, onnx_arg in [('policy', args.policy_onnx), ('off_policy', args.off_policy_onnx), ('on_policy', args.on_policy_onnx)]:
@@ -384,7 +387,10 @@ def _compile_warp_resolution_worker(cam_w, cam_h, model_w, model_h, benchmark_ru
     warp = None
   compiled_jit = compile_jit(warp, WARP_INPUTS, make_warp_queues, make_random_inputs=make_random_warp_inputs,
                             benchmark_runs=benchmark_runs, clear_refs=cleanup_warp)
-  write_bundle(result_path, {(cam_w, cam_h): compiled_jit}, {'device': Device.DEFAULT})
+
+  result_data = (compiled_jit, Device.DEFAULT)
+  with open(result_path, "wb") as f:
+    dump_oob(result_data, f)
 
 
 if __name__ == "__main__":
@@ -415,6 +421,12 @@ if __name__ == "__main__":
   model_w, model_h = args.model_size
   output_data = {}
 
+  args.vision_onnx = read_file_chunked_to_disk(args.vision_onnx)
+  args.policy_onnx = read_file_chunked_to_disk(args.policy_onnx)
+  args.off_policy_onnx = read_file_chunked_to_disk(args.off_policy_onnx)
+  args.on_policy_onnx = read_file_chunked_to_disk(args.on_policy_onnx)
+  args.supercombo_onnx = read_file_chunked_to_disk(args.supercombo_onnx)
+
   is_unified_supercombo = False
   if args.model_type == 'supercombo':
     assert args.supercombo_onnx
@@ -437,10 +449,8 @@ if __name__ == "__main__":
                                   frame_copy_size=frame_copy_size)
       warp = stock.make_warp(nv12, model_w, model_h)
       run_model_jit = TinyJit(stock.make_run_model(warp, run_policy, model_metadata, frame_copy_size), prune=True)
-      write_bundle(part_path := f"{args.output}.{cam_w}x{cam_h}", {(cam_w, cam_h): compile_jit(run_model_jit, stock.MODELD_INPUTS, make_model_queues,
-                                                                                               benchmark_runs=args.benchmark_runs)})
-      output_data[(cam_w, cam_h)] = read_parts(part_path)[0][(cam_w, cam_h)]
-      os.remove(part_path)
+      compiled_jit = compile_jit(run_model_jit, stock.MODELD_INPUTS, make_model_queues, benchmark_runs=args.benchmark_runs, return_loaded=False)
+      output_data[(cam_w, cam_h)] = compiled_jit
       gc.collect()
     del model_runner, run_policy
     gc.collect()
@@ -508,12 +518,18 @@ if __name__ == "__main__":
 
       tmp_files.append((cam_w, cam_h, tmp_res.name))
     for cam_w, cam_h, tmp_name in tmp_files:
-      warp_parts, warp_extras = read_parts(tmp_name)
-      output_data[(cam_w, cam_h)] = warp_parts[(cam_w, cam_h)]
-      output_data['input_devices']['warp'] = warp_extras['device']
+      with open(tmp_name, "rb") as f:
+        compiled_jit, dev_name = load_oob(f)
+      output_data[(cam_w, cam_h)] = compiled_jit
+      output_data['input_devices']['warp'] = dev_name
       os.remove(tmp_name)
     output_data['metadata']['warp_dev'] = Device.DEFAULT
 
-  parts = {key: output_data.pop(key) for key in [key for key, value in output_data.items() if isinstance(value, tuple)]}
-  write_bundle(args.output, parts, output_data)
-  print(f"Saved model to {args.output} ({os.path.getsize(args.output) / 1e6:.2f} MB, {len(parts)} JITs)")
+  with open(args.output, "wb") as file:
+    dump_oob(output_data, file)
+
+  pkl_size = os.path.getsize(args.output)
+  print(f"Saved combined JIT to {args.output} ({pkl_size / 1e6:.2f} MB)")
+  chunk_targets = get_chunk_targets(args.output, pkl_size)
+  chunk_file(args.output, chunk_targets)
+  print(f"Chunked into {len(chunk_targets) - 1} file(s)")

openpilot/sunnypilot/modeld_v2/compile_modeld_v2.py

@@ -1,59 +1,11 @@
 #!/usr/bin/env python3
-import argparse
+import runpy
 import os
-import sys
 
-import numpy as np
-
-from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, write_bundle
-from openpilot.sunnypilot.modeld_v2.plain_artifact_compiler import capture_frame, record_kernel_linear, serialize_jit
-
-
-def initialize_check_inputs(arrays: dict):
-  rng = np.random.default_rng(7)
-  for value in arrays.values():
-    value[...] = rng.standard_normal(value.shape) if value.dtype.kind == "f" else rng.integers(0, 2 if value.dtype == np.bool_ else 16, value.shape)
+from openpilot.sunnypilot.modeld_v2.compile_modeld import _patch_ops_serialization
 
 
 if __name__ == "__main__":
-  sys.path.insert(0, os.environ.get("TINYGRAD_PATH", "tinygrad_repo"))
-  from examples.openpilot.compile_onnx import onnx_metadata
-  from examples.openpilot.helpers import allocate_inputs, benchmark
-  from tinygrad import Device, Tensor, TinyJit
-  from tinygrad.dtype import _to_np_dtype
-  from tinygrad.nn.onnx import OnnxRunner
-
-  parser = argparse.ArgumentParser(description="Compile a native-architecture ONNX model into a plain tinygrad artifact")
-  parser.add_argument('onnx')
-  parser.add_argument('output')
-  parser.add_argument('--device-input', action='append', default=[])
-  parser.add_argument('--benchmark-runs', type=int, default=20)
-  args = parser.parse_args()
-
-  runner, (properties, output_shapes) = OnnxRunner(args.onnx), onnx_metadata(args.onnx)
-  device_inputs = runner.graph_inputs.keys() if '*' in args.device_input else args.device_input
-  metadata = {'metadata': properties} | {f'{kind}_shapes': {name: tuple(d if isinstance(d, int) else 0 for d in shape) for name, shape in shapes.items()}
-                                         for kind, shapes in [('input', {name: spec.shape for name, spec in runner.graph_inputs.items()}),
-                                                              ('output', output_shapes)]}
-  input_specs = {name: (tuple(s if isinstance(s, int) else 1 for s in spec.shape), np.dtype(_to_np_dtype(spec.dtype)).str,
-                        Device.DEFAULT if name in device_inputs else 'NPY') for name, spec in runner.graph_inputs.items()}
-
-  def model(inputs):
-    return {name: value.contiguous() for name, value in runner({name: value.to(Device.DEFAULT) for name, value in inputs.items()}).items()}
-  output_specs = {name: (value.shape, np.dtype(_to_np_dtype(value.dtype)).name, Device.DEFAULT) for name, value in model(allocate_inputs(input_specs)).items()}
-
-  @TinyJit(prune=True)
-  def jit(output_buffers, **inputs):
-    Tensor.realize(*(output_buffers[name].assign(value) for name, value in model(inputs).items()))
-
-  check_inputs = allocate_inputs(input_specs, initialize_check_inputs) | {'output_buffers': allocate_inputs(output_specs)}
-  with record_kernel_linear() as recorded:
-    for i in range(2 + args.benchmark_runs):
-      benchmark(jit, cb=lambda t, i=i: print(f"  [{i + 1}/{2 + args.benchmark_runs}] {t * 1e3:.2f} ms"), **check_inputs)
-  assert len(recorded) == 1, f"expected one captured kernel list, got {len(recorded)}"
-
-  frame, _ = capture_frame(jit, check_inputs, 'output_buffers')
-  part = serialize_jit(jit, recorded[0], frame)
-  PlainJit(part[0], memoryview(part[1]))
-  write_bundle(args.output, {'run': part}, {'metadata': metadata, 'input_specs': input_specs, 'output_specs': output_specs})
-  print(f"Saved model to {args.output} ({os.path.getsize(args.output) / 1e6:.2f} MB, {len(part[0]['calls'])} kernels)")
+  _patch_ops_serialization()
+  upstream_script = os.path.join(os.environ.get("TINYGRAD_PATH", "tinygrad_repo"), "examples/openpilot/compile_onnx.py")
+  runpy.run_path(upstream_script, run_name="__main__")

openpilot/sunnypilot/modeld_v2/helpers.py

@@ -5,23 +5,14 @@ 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 builtins
-import contextlib
-import dataclasses
-import functools
-import hashlib
 import io
-import json
-import math
-import mmap
-import os
-import pickle
 import struct
-
-MAGIC = b"SPTGPLN1"
-ALIGNMENT = 256
-METADATA_TYPES = ("slice", "tuple", "list", "dict", "set", "frozenset", "complex")
-RUNTIME_ENVIRONMENT = ("GMMU", "AMD_AQL", "AMD_DISABLE_SDMA", "GRAPH_ONE_KERNEL")
+import pickle
+import inspect
+import importlib
+import tempfile
+import shutil
+import enum
 
 
 def _patch_system_flock_acquire():
@@ -41,246 +32,86 @@ def _patch_system_flock_acquire():
     pass
 _patch_system_flock_acquire()
 
-
-class ArtifactMismatch(RuntimeError):
-  pass
-
-
-class Blob:
-  def __init__(self, sink=None):
-    self.chunks: list = []
-    self.locations: dict[bytes, list[int]] = {}
-    self.size, self.write = 0, sink.write if sink else self.chunks.append
-
-  def add(self, data) -> list[int]:
-    if (key := hashlib.blake2b(data, digest_size=16).digest()) not in self.locations:
-      start = self.size + -self.size % ALIGNMENT
-      self.write(bytes(start - self.size)), self.write(data)
-      self.locations[key], self.size = [start, start + memoryview(data).nbytes], start + memoryview(data).nbytes
-    return self.locations[key]
-
-
-class _MetadataUnpickler(pickle.Unpickler):
-  def find_class(self, module, name):
-    if module == "builtins" and name in METADATA_TYPES:
-      return getattr(builtins, name)
-    raise pickle.UnpicklingError(f"{module}.{name} is not allowed in model metadata")
-
-
-def flatten(value) -> list:
-  if isinstance(value, (tuple, list)):
-    return [tensor for item in value for tensor in flatten(item)]
-  return [] if value is None else [value]
-
-
-def _relocate(value, part_blob: memoryview, blob: Blob):
-  if isinstance(value, dict):
-    return {k: blob.add(part_blob[slice(*v)]) if k in ("lib", "init", "data") else _relocate(v, part_blob, blob) for k, v in value.items()}
-  return [_relocate(v, part_blob, blob) for v in value] if isinstance(value, list) else value
-
-
-def write_bundle(path: str, parts: dict, extras: dict | None = None):
-  blob = Blob()
-  headers = {key: _relocate(part_header, memoryview(part_blob), blob) for key, (part_header, part_blob) in parts.items()}
-  extras_location = blob.add(pickle.dumps(extras or {}, protocol=4))
-  entries = [{"key": list(key) if isinstance(key, tuple) else key, "blob": [0, blob.size], "header": header} for key, header in headers.items()]
-  header = json.dumps({"parts": entries, "extras": extras_location}).encode()
-  with open(path, "wb") as file:
-    file.write(MAGIC + struct.pack("<Q", len(header)) + header + bytes(-(len(MAGIC) + 8 + len(header)) % ALIGNMENT))
-    file.writelines(blob.chunks)
-
-
-def read_parts(path: str) -> tuple[dict, dict]:
-  with open(path, "rb") as file:
-    data = memoryview(mmap.mmap(file.fileno(), 0, access=mmap.ACCESS_READ))
-  if bytes(data[:len(MAGIC)]) != MAGIC:
-    raise ValueError(f"{path} is not a plain tinygrad model, recompile it with compile_modeld.py")
-  start = len(MAGIC) + 8 + struct.unpack_from("<Q", data, len(MAGIC))[0]
-  header, blob = json.loads(bytes(data[len(MAGIC) + 8:start])), data[start + -start % ALIGNMENT:]
-  parts = {tuple(e["key"]) if isinstance(e["key"], list) else e["key"]: (e["header"], blob[slice(*e["blob"])]) for e in header["parts"]}
-  return parts, _MetadataUnpickler(io.BytesIO(bytes(blob[slice(*header["extras"])]))).load()
-
-
-def load_model(path: str, device_map: dict | None = None, verify: bool = True, cache: bool = True) -> dict:
-  parts, extras = read_parts(path)
-  if cache and (cached := _read_cache(path, parts, device_map)) is not None:
-    return extras | cached
-  shared: dict = {}
-  jits = {key: PlainJit(header, blob, device_map, verify, shared) for key, (header, blob) in parts.items()}
-  if cache:
-    _write_cache(path, jits, device_map)
-  return extras | jits
-
-
-@functools.cache
-def tinygrad_identity() -> str:
-  import tinygrad
-  root, digest = os.path.dirname(tinygrad.__file__), hashlib.sha256()
-  for directory, _, files in sorted(os.walk(root)):
-    for name in sorted(file for file in files if file.endswith(".py")):
-      stat = os.stat(path := os.path.join(directory, name))
-      digest.update(f"{os.path.relpath(path, root)}:{stat.st_size}:{stat.st_mtime_ns};".encode())
-  return digest.hexdigest()
-
-
-def _cache_key(path: str, device_map: dict | None) -> bytes:
-  stat = os.stat(path)
-  return json.dumps({"format": MAGIC.decode(), "tinygrad": tinygrad_identity(), "size": stat.st_size, "mtime_ns": stat.st_mtime_ns,
-                     "device_map": sorted((device_map or {}).items()), "env": [os.environ.get(name, "") for name in RUNTIME_ENVIRONMENT]}).encode()
-
-
-def _cache_header_matches(file, path: str, device_map: dict | None) -> bool:
-  return file.read(struct.unpack("<Q", file.read(8))[0]) == _cache_key(path, device_map)
-
-
-def cache_is_fresh(path: str, device_map: dict | None = None) -> bool: # entry point for warmup proc
+def _pad_args(func, args, kwargs):
   try:
-    with open(f"{path}.cache", "rb") as file:
-      return _cache_header_matches(file, path, device_map)
-  except (OSError, struct.error):
-    return False
-
-
-def _read_cache(path: str, parts: dict, device_map: dict | None) -> dict | None:
-  try:
-    with open(f"{path}.cache", "rb") as file:
-      if not _cache_header_matches(file, path, device_map):
-        return None
-      shared: dict = {}
-      buffers = {repr(key): _allocate_buffers(header, blob, device_map, shared) for key, (header, blob) in parts.items()}
-      return type("_Unpickler", (pickle.Unpickler,), {"persistent_load": lambda self, pid: buffers[pid[0]][pid[1]]})(file).load()
+    sig = inspect.signature(func)
   except Exception:
-    return None
+    return args, kwargs
+  params = list(sig.parameters.values())
+  if inspect.isfunction(func) and params and params[0].name in ('cls', 'self'):
+    params = params[1:]
+
+  new_args = list(args)
+  has_varargs = any(p.kind == inspect.Parameter.VAR_POSITIONAL for p in params)
+  if len(new_args) > len(params) and not has_varargs:
+    new_args = new_args[:len(params)]
+
+  for i in range(len(new_args), len(params)):
+    param = params[i]
+    if param.kind in (inspect.Parameter.VAR_POSITIONAL, inspect.Parameter.VAR_KEYWORD):
+      continue
+    val = param.default if param.default is not inspect.Parameter.empty else None
+    new_args.append(val)
+  return new_args, kwargs
 
 
-def _write_cache(path: str, jits: dict, device_map: dict | None) -> None:
-  from tinygrad.device import Buffer
-  owners = {id(buffer): (repr(key), index) for key, jit in jits.items() for index, buffer in enumerate(jit.buffers)}
+def _dynamic_factory(real_class):
+  if isinstance(real_class, type) and issubclass(real_class, enum.Enum):
+    return real_class
 
-  class _Pickler(pickle.Pickler):
-    def persistent_id(self, obj):
-      return owners.get(id(obj)) if isinstance(obj, Buffer) else None
+  def factory(*args, **kwargs):
+    try:
+      return real_class(*args, **kwargs)
+    except TypeError:
+      new_args, new_kwargs = _pad_args(real_class, args, kwargs)
+      return real_class(*new_args, **new_kwargs)
 
-  key, tmp_path = _cache_key(path, device_map), f"{path}.cache.{os.getpid()}.tmp"
-  with contextlib.suppress(Exception):
-    with open(tmp_path, "wb") as file:
-      file.write(struct.pack("<Q", len(key)) + key)
-      _Pickler(file, protocol=5).dump({name: _Jit(jit.captured, jit.input_names, jit.buffers) for name, jit in jits.items()})
-    os.replace(tmp_path, f"{path}.cache")
+  class DynamicMeta(type(real_class)):
+    def __call__(cls, *args, **kwargs):
+      return factory(*args, **kwargs)
+
+  class DynamicProxy(real_class, metaclass=DynamicMeta):
+    __slots__ = ()
+
+    def __new__(cls, *args, **kwargs):
+      return factory(*args, **kwargs)
+
+  DynamicProxy.__name__ = real_class.__name__
+  DynamicProxy.__module__ = real_class.__module__
+  return DynamicProxy
 
 
-# Everything below this comment block calls tinygrad internals, so after a tinygrad bump this
-# is the only code to update, and models are not recompiled. How to do this when discountchubbs is not available:
-#   1. run modeld_v2/tests/test_plain_artifact.py on the new tinygrad and fix each failing call against the new API: Buffer,
-#      UOp.from_buffer/param (ParamArg), ProgramInfo, Target, KernelInfo, compile_linear, CapturedJit and
-#      _prepare_jit_inputs in tinygrad/engine/jit.py
-#   2. load a real model with verify=True: ArtifactMismatch means the rebuilt graph still differs from the one that was compiled
-# The boot cache is keyed on the tinygrad source, so it rebuilds itself. Only a change in how the device runs kernel binaries needs a recompile.
-# Honestly, I would just have your clanker try it because you likely have zero idea what you are looking at lol..
-
-def _dtype(text: str):
-  from tinygrad.dtype import dtypes
-  return eval(text, {"__builtins__": {}}, {"dtypes": dtypes})
+class DynamicTinygradUnpickler(pickle.Unpickler):
+  def find_class(self, module, name):
+    real_class = getattr(importlib.import_module(module), name)
+    if module.startswith("tinygrad"):
+      return _dynamic_factory(real_class)
+    return real_class
 
 
-def _device(recorded: str, device_map: dict | None) -> str:
-  from tinygrad import Device
-  device_map = device_map or {}
-  return Device.canonicalize(device_map.get(recorded, device_map.get(recorded.split(":", 1)[0], recorded)))
+def load_oob(f):
+  opcodes = f.read(struct.unpack('<q', f.read(8))[0])
+  def buffers():
+    while (h := f.read(8)):
+      pb = pickle.PickleBuffer(bytearray(struct.unpack('<q', h)[0]))
+      f.readinto(pb)
+      yield pb
+  return DynamicTinygradUnpickler(io.BytesIO(opcodes), buffers=buffers()).load()
 
 
-def _allocate_buffers(header: dict, blob: memoryview, device_map: dict | None, shared: dict) -> list:
-  import numpy as np
-  from tinygrad.device import Buffer
-  written = {call["args"][i]["buffer"] for call in header["calls"] for i in (call["outs"] if call["kind"] == "program" else (0,))
-             if "buffer" in call["args"][i]}
-  buffers = []
-  for index, entry in enumerate(header["buffers"]):
-    device, data = _device(entry["device"], device_map), blob[slice(*entry["init"])] if "init" in entry else None
-    # read-only data the parts share in the file (weights common to every camera resolution) is uploaded once to the nut
-    key = (device, entry["dtype"], np.frombuffer(data, np.uint8).ctypes.data, len(data)) if data and index not in written else object()
-    if key not in shared:
-      shared[key] = Buffer(device, entry["nbytes"], initial_value=pickle.PickleBuffer(data) if data else None).ensure_allocated()
-    buffers.append(shared[key])
-  return buffers
+def dump_oob(obj, f):
+  with tempfile.TemporaryFile(dir=".") as tmp:
+    def buffer_cb(buffer):
+      data = buffer.raw()
+      tmp.write(struct.pack('<q', len(data)))
+      tmp.write(data)
+      buffer.release()
+      return False
 
-
-def _program_uop(call: dict, lib: bytes):
-  from tinygrad.helpers import Target
-  from tinygrad.uop.ops import KernelInfo, Ops, ProgramInfo, UOp
-  parameters = []
-  for name, compact_slot, dtype, shape in call["signature"]:
-    parameter = UOp.param(call["globals"][compact_slot], _dtype(dtype), math.prod(shape))
-    image = (shape[0], shape[1]) if len(shape) == 3 and shape[2] == 4 else None
-    parameters.append(parameter.replace(arg=dataclasses.replace(parameter.arg, name=name, image=image)))
-  info = ProgramInfo(global_size=tuple(call["global_size"]), local_size=tuple(call["local_size"]), vars=(), globals=tuple(call["globals"]),
-                     outs=tuple(call["outs"]), ins=tuple(call["ins"]), target=Target(**call["target"]))
-  return UOp(Ops.PROGRAM, src=(UOp(Ops.SINK, arg=KernelInfo(name=call["name"])), UOp(Ops.LINEAR, src=tuple(parameters)),
-                               UOp(Ops.SOURCE, arg=""), UOp(Ops.BINARY, arg=lib)), arg=info)
-
-
-class _Jit:
-  def __init__(self, captured, input_names: list, buffers: list):
-    self.captured, self.input_names, self.buffers = captured, input_names, buffers
-
-  def __call__(self, *args, **kwargs):
-    import tinygrad.engine.jit as jit
-    input_uops, var_vals, names, _ = jit._prepare_jit_inputs(args, kwargs)
-    if names != self.input_names:
-      raise ValueError(f"expected inputs {self.input_names}, got {names}")
-    return self.captured(input_uops, var_vals)
-
-
-class PlainJit(_Jit):
-  def __init__(self, header: dict, blob: memoryview, device_map: dict | None = None, verify: bool = True, shared: dict | None = None):
-    import numpy as np
-    import tinygrad.engine.jit as jit
-    from tinygrad import Tensor
-    from tinygrad.device import Buffer
-    from tinygrad.dtype import dtypes
-    from tinygrad.uop.ops import Ops, UOp
-
-    inputs = {spec["slot"]: spec for spec in header["inputs"]}
-    buffers = _allocate_buffers(header, blob, device_map, {} if shared is None else shared)
-    bases = [UOp.from_buffer(buffer, _dtype(entry["dtype"])) for buffer, entry in zip(buffers, header["buffers"], strict=True)]
-
-    def argument(described: dict):
-      if "input" in described:
-        spec = inputs[described["input"]]
-        return UOp.param(described["input"], _dtype(spec["dtype"]), spec["numel"], _device(spec["device"], device_map))
-      base, dtype, offset, nbytes = bases[described["buffer"]], _dtype(described["dtype"]), described["offset"], described["nbytes"]
-      if offset == 0 and nbytes == header["buffers"][described["buffer"]]["nbytes"] and dtype == base.dtype:
-        return base
-      return (base if base.dtype.itemsize == 1 else base.bitcast(dtypes.uint8)).shrink(((offset, offset + nbytes),)).bitcast(dtype)
-
-    calls = []
-    for call in header["calls"]:
-      arguments = [argument(described) for described in call["args"]]
-      if call["kind"] == "program":
-        calls.append(_program_uop(call, bytes(blob[slice(*call["lib"])])).call(*arguments))
-      else:
-        calls.append(arguments[0].store_call(arguments[1]))
-    # stand-ins for JIT inputs: copy staging to GPU is decided from the input buffers, the real ones bind per call
-    stand_ins = {slot: UOp.from_buffer(Buffer(_device(spec["device"], device_map), spec["numel"] * _dtype(spec["dtype"]).itemsize).ensure_allocated(),
-                                       _dtype(spec["dtype"])) for slot, spec in inputs.items()}
-    input_uops = tuple(stand_ins.get(slot, next(iter(stand_ins.values()), None)) for slot in range(max(stand_ins, default=-1) + 1))
-    linear = jit.compile_linear(UOp(Ops.LINEAR, src=tuple(calls)), beam=0, input_uops=input_uops, cache=False)
-
-    returned = [Tensor(argument(t)).reshape(tuple(t["shape"])) for t in header["returns"]["tensors"]]
-    ret = {"NoneType": None, "Tensor": returned[0] if returned else None, "tuple": tuple(returned), "list": returned}[header["returns"]["kind"]]
-    super().__init__(jit.CapturedJit(ret, linear, header["input_names"], []), header["input_names"], buffers)
-
-    if not verify or not (check := header.get("check")):
-      return
-    def array(stored):
-      return np.frombuffer(blob[slice(*stored["data"])], dtype=np.dtype(stored["dtype"])).reshape(stored["shape"]).copy()
-    kwargs: dict = {}
-    for path, stored, device in check["inputs"]:
-      tensor = Tensor(array(stored), device=_device(device, device_map)).realize()
-      kwargs[path[0]] = tensor if len(path) == 1 else {**kwargs.get(path[0], {}), path[1]: tensor}
-    result = self(**kwargs)
-    outputs = kwargs[check["output_container"]].values() if check["output_container"] else flatten(result)
-    for index, (got, stored) in enumerate(zip([t.numpy() for t in outputs], check["outputs"], strict=True)):
-      expected = array(stored)
-      if got.shape != expected.shape or not np.allclose(got, expected, rtol=1e-3, atol=1e-3, equal_nan=True):
-        raise ArtifactMismatch(f"output {index} differs from the compile-time reference frame; recompile the model")
+    stream = io.BytesIO()
+    pickle.Pickler(stream, protocol=5, buffer_callback=buffer_cb).dump(obj)
+    opcodes = stream.getvalue()
+    f.write(struct.pack('<q', len(opcodes)))
+    f.write(opcodes)
+    tmp.seek(0)
+    shutil.copyfileobj(tmp, f)

openpilot/sunnypilot/modeld_v2/model_adapters.py

@@ -23,8 +23,8 @@ from tinygrad.uop.ops import UOp
 
 
 def input_view(buffer: Buffer, shape: tuple[int, ...], dtype: DType, offset: int) -> Tensor:
-  view = buffer.view(math.prod(shape) * dtype.itemsize, offset).ensure_allocated()
-  return Tensor(UOp.from_buffer(view, dtype)).reshape(shape)
+  view = buffer.view(math.prod(shape), dtype, offset).ensure_allocated()
+  return Tensor(UOp.from_buffer(view)).reshape(shape)
 
 
 class BaseModelAdapter:

openpilot/sunnypilot/modeld_v2/modeld.py

@@ -24,6 +24,7 @@ from openpilot.cereal.messaging import PubMaster, SubMaster
 from openpilot.cereal.visionipc import VisionStreamType
 from msgq.visionipc import VisionIpcClient, VisionBuf
 from opendbc.car.car_helpers import get_demo_car_params
+from openpilot.common.file_chunker import open_file_chunked
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.params import Params
 from openpilot.common.filter_simple import FirstOrderFilter
@@ -41,7 +42,7 @@ from openpilot.sunnypilot.modeld_v2.meta_helper import load_meta_constants
 from openpilot.sunnypilot.modeld_v2.camera_offset_helper import CameraOffsetHelper
 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
-from openpilot.sunnypilot.modeld_v2.helpers import load_model
+from openpilot.sunnypilot.modeld_v2.helpers import load_oob
 from openpilot.sunnypilot.modeld_v2.model_adapters import get_model_adapter
 from openpilot.sunnypilot.models.helpers import get_active_bundle
 from openpilot.sunnypilot.selfdrive.controls.lib.relc import RoadEdgeLaneChangeController
@@ -51,7 +52,8 @@ BIG_MODEL_TIMEOUT = 60
 
 
 def _pkl_exists(path):
-  return os.path.exists(path)
+  from openpilot.common.file_chunker import get_manifest_path
+  return os.path.exists(path) or os.path.exists(get_manifest_path(path))
 
 
 def _find_driving_pkl(bundle):
@@ -106,7 +108,7 @@ class ModelState(ModelStateBase):
 
   def _init_combined(self, pkl_path, cam_w, cam_h, bundle):
     cloudlog.warning(f"loading combined pkl: {pkl_path}")
-    jits = load_model(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'
@@ -256,8 +258,7 @@ def main(demo=False):
 
   CHESTNUT = chestnut_present()
   if CHESTNUT:
-    from tinygrad.runtime.ops_amd import AMDDevice
-    AMDDevice.wait_timeout_ms = 3000
+    os.environ['HCQDEV_WAIT_TIMEOUT_MS'] = '3000'
 
   params = Params()
   params.put_bool("ChestnutLoading", CHESTNUT)

openpilot/sunnypilot/modeld_v2/plain_artifact_compiler.py

@@ -1,90 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-import dataclasses
-import mmap
-import tempfile
-from contextlib import contextmanager
-from unittest import mock
-
-import numpy as np
-
-from openpilot.sunnypilot.modeld_v2.helpers import Blob, flatten
-
-# Compile time only/ see discountchubbs 4 assistance: turns a captured TinyJit into plain data that helpers.load_model rebuilds. It reads internals of the
-# tinygrad that compiles the model, so a tinygrad bump that breaks it blocks new builds, never loading already built models.
-@contextmanager
-def record_kernel_linear():
-  import tinygrad.engine.jit as jit
-  import tinygrad.engine.realize as realize
-  recorded, hcq_compile, compile_linear = [], realize.hcq_compile, jit.compile_linear
-
-  def recording_compile_linear(*args, **kwargs):
-    with mock.patch.object(realize, "hcq_compile", lambda linear, *a, **k: (recorded.append(linear), hcq_compile(linear, *a, **k))[1]):
-      return compile_linear(*args, **kwargs)
-
-  with mock.patch.object(jit, "compile_linear", recording_compile_linear):
-    yield recorded
-
-
-def capture_frame(jit, kwargs: dict, output_container: str | None = None):
-  inputs = [([name] if key is None else [name, key], tensor.numpy().copy(), tensor.device)
-            for name, value in kwargs.items() for key, tensor in (value.items() if isinstance(value, dict) else [(None, value)])]
-  result = jit(**kwargs)
-  outputs = kwargs[output_container].values() if output_container else flatten(result)
-  return {"inputs": inputs, "outputs": [tensor.numpy().copy() for tensor in outputs], "output_container": output_container}, result
-
-
-def serialize_jit(jit, kernel_linear, check: dict | None = None) -> tuple[dict, memoryview]:
-  from tinygrad.uop.ops import Ops
-  sink = tempfile.TemporaryFile(dir=".")
-  blob, bases, input_specs = Blob(sink), {}, {}
-
-  def store(array) -> dict:
-    array = np.ascontiguousarray(array)
-    return {"data": blob.add(array.tobytes()), "dtype": array.dtype.str, "shape": list(array.shape)}
-
-  def describe(uop) -> dict:
-    if uop.op is Ops.PARAM:
-      input_specs.setdefault(uop.arg.slot, {"dtype": repr(uop.dtype), "numel": int(uop.max_numel()), "device": uop.device})
-      return {"input": uop.arg.slot}
-    buffer = uop.buffer
-    root = buffer._base if buffer._base is not None else buffer
-    base = bases.setdefault(id(root), (len(bases), root, uop.base.dtype if buffer._base is None else uop.dtype))
-    return {"buffer": base[0], "offset": buffer.offset if buffer._base is not None else 0, "nbytes": buffer.nbytes, "dtype": repr(uop.dtype)}
-
-  calls, written, needs_init = [], set(), set()
-  for call in kernel_linear.src:
-    ast, arguments = call.src[0], [describe(argument) for argument in call.src[1:]]
-    if ast.op is Ops.PROGRAM:
-      elf, info = ast.to_elf(), ast.arg
-      global_size, local_size = info.launch_dims({})
-      calls.append({"kind": "program", "name": elf.name, "lib": blob.add(bytes(elf.lib)), "target": dataclasses.asdict(elf.target),
-                    "signature": [[name, slot, repr(dtype), [int(x) for x in shape]] for name, slot, dtype, shape in elf.signature],
-                    "global_size": [int(x) for x in global_size], "local_size": [int(x) for x in local_size],
-                    "globals": list(info.globals), "outs": list(info.outs), "ins": list(info.ins), "args": arguments})
-      outs, ins = info.outs, info.ins
-    elif ast.op is Ops.COPY:
-      calls.append({"kind": "copy", "args": arguments})
-      outs, ins = (0,), (1,)
-    else:
-      raise ValueError(f"unsupported call {ast.op} {ast.arg}")
-    needs_init |= {arguments[i]["buffer"] for i in ins if "buffer" in arguments[i] and arguments[i]["buffer"] not in written}
-    written |= {arguments[i]["buffer"] for i in outs if "buffer" in arguments[i]}
-
-  ret = jit.captured.ret
-  returns = {"kind": type(ret).__name__, "tensors": [describe(t.uop.base) | {"shape": [int(x) for x in t.shape]} for t in flatten(ret)]}
-  buffers = [{"nbytes": base.nbytes, "device": base.device, "dtype": repr(dtype)}
-             | ({"init": blob.add(base.as_memoryview())} if index in needs_init else {}) for index, base, dtype in bases.values()]
-  names = list(jit.captured.expected_names)
-  if check is not None:
-    check = {"inputs": [[path, store(array), device] for path, array, device in check["inputs"]], "outputs": [store(array) for array in check["outputs"]],
-             "output_container": check["output_container"]}
-  header = {"input_names": names, "buffers": buffers, "calls": calls, "returns": returns, "check": check,
-            "inputs": [{"slot": slot, "name": names[slot] if slot < len(names) else None} | input_specs[slot] for slot in sorted(input_specs)]}
-  with sink:
-    sink.flush()
-    return header, memoryview(mmap.mmap(sink.fileno(), 0, access=mmap.ACCESS_READ) if blob.size else b"")

openpilot/sunnypilot/modeld_v2/tests/helpers.py

@@ -188,8 +188,10 @@ def make_pkl_data(archetype):
 
 
 def write_pkl(tmp_path, archetype):
+  from openpilot.sunnypilot.modeld_v2.helpers import dump_oob
   pkl_path = tmp_path / 'driving_test_tinygrad.pkl'
-  pkl_path.write_bytes(pickle.dumps(make_pkl_data(archetype)))
+  with open(pkl_path, 'wb') as f:
+    dump_oob(make_pkl_data(archetype), f)
   return pkl_path
 
 
@@ -209,7 +211,6 @@ def patch_modeld(monkeypatch):
   def _patch(bundle):
     monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
     monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: bundle)
-    monkeypatch.setattr(modeld_module, 'load_model', lambda path: pickle.loads(pathlib.Path(path).read_bytes()))
 
   return _patch
 

openpilot/sunnypilot/modeld_v2/tests/test_combined_pkl_loader.py

@@ -90,6 +90,7 @@ class TestStockEquivalence(OpenpilotTestCase):
 
   def test_unified_run_model(self, tmp_path, monkeypatch, patch_modeld):
     from openpilot.common.hardware import hw
+    from openpilot.sunnypilot.modeld_v2.helpers import dump_oob
     shapes = {'img': (1, 12, 128, 256), 'big_img': (1, 12, 128, 256), 'features_buffer': (1, 24, 32, 512),
               'desire_pulse': (1, 25, 8), 'traffic_convention': (1, 2), 'action_t': (1, 2)}
     import codecs
@@ -101,7 +102,8 @@ class TestStockEquivalence(OpenpilotTestCase):
       (CAM_W, CAM_H): tests_helpers._noop_jit,
       'run_policy': tests_helpers._noop_jit,
     }
-    (tmp_path / 'driving_test_tinygrad.pkl').write_bytes(pickle.dumps(pkl_data))
+    with open(tmp_path / 'driving_test_tinygrad.pkl', 'wb') as f:
+      dump_oob(pkl_data, f)
     bundle = DummyBundle(models=[DummyModel('supercombo', 'driving_test_tinygrad.pkl')])
     patch_modeld(bundle)
     monkeypatch.setattr(hw.Paths, 'model_root', staticmethod(lambda: str(tmp_path)))

openpilot/sunnypilot/modeld_v2/tests/test_compile_modeld.py

@@ -5,12 +5,16 @@ 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 tempfile
 import unittest
+from pathlib import Path
 
 import numpy as np
 from openpilot.common.parameterized import parameterized
 
-from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, _detect_desire_key
+from openpilot.common.file_chunker import chunk_file, get_chunk_targets
+from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, _detect_desire_key, read_file_chunked_to_disk
 from openpilot.common.test import OpenpilotTestCase
 
 
@@ -164,6 +168,36 @@ class TestOutputSlicePreservation(OpenpilotTestCase):
       "vision and policy slices should not overlap in keys"
 
 
+class TestReadFileChunkedToDisk(OpenpilotTestCase):
+  def test_none_passthrough(self):
+    assert read_file_chunked_to_disk(None) is None
+
+  def test_unchunked_source_staged_on_disk(self):
+    with tempfile.TemporaryDirectory() as d:
+      src = Path(d) / "driving_supercombo.onnx"
+      payload = os.urandom(1024)
+      src.write_bytes(payload)
+
+      out = Path(read_file_chunked_to_disk(str(src)))
+
+      assert out.parent == Path(d)
+      assert out.name == "driving_supercombo.onnx.unchunked"
+      assert out.read_bytes() == payload
+
+  def test_chunked_source_reassembled_on_disk(self):
+    with tempfile.TemporaryDirectory() as d:
+      src = Path(d) / "driving_supercombo.onnx"
+      payload = os.urandom(4096)
+      src.write_bytes(payload)
+      chunk_file(str(src), get_chunk_targets(str(src), len(payload)))
+      assert not src.exists()
+
+      out = Path(read_file_chunked_to_disk(str(src)))
+
+      assert out.parent == Path(d)
+      assert out.read_bytes() == payload
+
+
 class Test4DFeaturesBuffer(OpenpilotTestCase):
   def test_get_policy_npy_shapes_4d(self):
     from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes

openpilot/sunnypilot/modeld_v2/tests/test_fallback.py

@@ -5,11 +5,13 @@ 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 pickle
+import io
 import requests
 
+from openpilot.common.file_chunker import get_chunk_name
 from openpilot.common.hardware import hw
 from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.modeld_v2.helpers import dump_oob
 import openpilot.sunnypilot.modeld_v2.modeld as modeld_module
 from openpilot.sunnypilot.modeld_v2.tests import helpers as tests_helpers
 from openpilot.sunnypilot.modeld_v2.tests.helpers import DummyModel, DummyBundle, CAM_W, CAM_H
@@ -41,11 +43,14 @@ class TestFallback(OpenpilotTestCase):
     small_json = requests.get(ModelFetcher.MODEL_URL).json()
     small_bundle = ModelParser.parse_models(small_json)[-1]
 
-    oob_bytes = pickle.dumps(tests_helpers.make_pkl_data(tests_helpers.ARCHETYPES['supercombo_non20hz']))
-    monkeypatch.setattr(modeld_module, 'load_model', lambda path: pickle.loads(open(path, 'rb').read()))
+    buf = io.BytesIO()
+    dump_oob(tests_helpers.make_pkl_data(tests_helpers.ARCHETYPES['supercombo_non20hz']), buf)
+    oob_bytes = buf.getvalue()
 
     for bundle in (big_bundle, small_bundle):
-      (tmp_path / bundle.models[0].artifact.fileName).write_bytes(oob_bytes)
+      artifact = bundle.models[0].artifact
+      for i in range(len(artifact.chunks)):
+        (tmp_path / get_chunk_name(artifact.fileName, i, len(artifact.chunks))).write_bytes(oob_bytes if i == 0 else b"")
 
     monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, chestnut=None: small_bundle)
     assert modeld_module.ModelState(CAM_W, CAM_H, chestnut=False).chestnut is False

openpilot/sunnypilot/modeld_v2/tests/test_models.py

@@ -7,14 +7,71 @@ See the LICENSE.md file in the root directory for more details.
 
 import os
 import unittest
-
-from openpilot.sunnypilot.modeld_v2.helpers import PlainJit, load_model
+from unittest.mock import patch
+from openpilot.common.file_chunker import open_file_chunked
+from openpilot.sunnypilot.modeld_v2.helpers import load_oob
+from tinygrad.device import Device
 
 
-class TestRegistryModels(unittest.TestCase):
-  def test_model_loads(self):
-    if not (base_name := os.environ.get("MODEL_BASE_NAME")):
-      self.skipTest("MODEL_BASE_NAME env var not set, skipping integration test.")
-    bundle = load_model(os.path.join(os.environ.get("MODEL_DIR", "/tmp/models"), base_name), {"QCOM": "CPU", "AMD": "CPU"}, verify=False, cache=False)
-    jits = [value for value in bundle.values() if isinstance(value, PlainJit)]
-    assert "metadata" in bundle and jits and all(len(jit.captured.linear.src) > 0 for jit in jits)
+class TestLegacyModels(unittest.TestCase):
+  def test_legacy_model_load(self):
+    base_name = os.environ.get("MODEL_BASE_NAME")
+    if not base_name:
+      raise unittest.SkipTest("MODEL_BASE_NAME env var not set, skipping integration test.")
+    chunk_dir = os.environ.get("MODEL_CHUNK_DIR", "/tmp/model_chunks")
+    base_path = os.path.join(chunk_dir, base_name)
+
+    try:
+      f = open_file_chunked(base_path)
+    except Exception as error:
+      self.fail(f"Failed to open chunked file {base_path}: {error}")
+    self.addCleanup(f.close)
+
+    real_getitem = Device.__class__.__getitem__
+
+    def safe_getitem(device_self, ix):
+      if ix == "QCOM" and not os.path.exists("/dev/kgsl-3d0"):
+        return real_getitem(device_self, "CPU")
+      if ix == "AMD" and not os.path.exists("/dev/kfd"):
+        return real_getitem(device_self, "CPU")
+      return real_getitem(device_self, ix)
+
+    with patch.object(Device.__class__, "__getitem__", safe_getitem):
+      obj = load_oob(f)
+
+      assert isinstance(obj, dict), "Parsed object is not a dictionary"
+      assert "metadata" in obj, "Metadata key is missing"
+
+      def traverse_jits(d):
+        if hasattr(d, "captured") and d.captured is not None:
+          linear_attr = getattr(d.captured, "_linear", None)
+          if linear_attr is None:
+            try:
+              linear_attr = getattr(d.captured, "linear", None)
+            except AssertionError as e:
+              if "alloc size must be positive" in str(e):
+                return
+              raise
+
+          if linear_attr is not None:
+            stack = [linear_attr]
+            visited = set()
+            while stack:
+              node = stack.pop()
+              if id(node) in visited:
+                continue
+              visited.add(id(node))
+              if hasattr(node, "src") and node.src is not None:
+                for child in node.src:
+                  stack.append(child)
+        elif isinstance(d, dict):
+          for v in d.values():
+            traverse_jits(v)
+        elif isinstance(d, (list, tuple)):
+          for v in d:
+            traverse_jits(v)
+
+      if "run_model" in obj:
+        traverse_jits(obj["run_model"])
+      if "run_policy" in obj:
+        traverse_jits(obj["run_policy"])

openpilot/sunnypilot/modeld_v2/warmup.py

@@ -1,42 +0,0 @@
-#!/usr/bin/env python3
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import os
-os.environ['GMMU'] = '0'
-import multiprocessing
-import time
-from openpilot.common.hardware.hw import Paths
-from openpilot.common.params import Params
-from openpilot.common.swaglog import cloudlog
-from openpilot.selfdrive.modeld.helpers import chestnut_present
-from openpilot.sunnypilot.modeld_v2.helpers import cache_is_fresh, load_model
-from openpilot.sunnypilot.models.helpers import get_selected_bundle
-
-
-def main():
-  """
-  The main entry point for offroad cache creation.
-  Runs every 10 seconds and checks for stale model caches.
-  Chestnut cache needs the gpu to build, so that slot waits until it is plugged in, or simply runs during modeld startup.
-  """
-  params, failed, spawn = Params(), set(), multiprocessing.get_context("spawn")
-  while True:
-    for bundle in [get_selected_bundle(params, source) for source in (("qcom", "chestnut") if chestnut_present() else ("qcom",))]:
-      path = os.path.join(Paths.model_root(), bundle.models[0].artifact.fileName) if bundle and bundle.models else ""
-      if not os.path.isfile(path) or cache_is_fresh(path) or (attempt := (path, os.stat(path).st_mtime_ns)) in failed:
-        continue
-      (worker := spawn.Process(target=load_model, args=(path,), daemon=True)).start()
-      worker.join()
-      if not cache_is_fresh(path):
-        cloudlog.error(f"model cache warmup failed for {path} with exit code {worker.exitcode}")
-        failed.add(attempt)
-    time.sleep(10)
-
-
-if __name__ == "__main__":
-  main()

openpilot/sunnypilot/models/fetcher.py

@@ -6,10 +6,12 @@ See the LICENSE.md file in the root directory for more details.
 """
 
 import time
+import os
 import requests
 from requests.exceptions import (SSLError, RequestException, HTTPError)
 from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
+from openpilot.common.hardware.hw import Paths
 from openpilot.sunnypilot.models.helpers import is_bundle_version_compatible
 from openpilot.cereal import custom
 
@@ -24,11 +26,35 @@ class ModelParser:
     download_uri.sha256 = download_uri_data.get("sha256")
     return download_uri
 
+  @staticmethod
+  def _parse_chunk(chunk_data) -> custom.ModelManagerSP.Chunk:
+    chunk = custom.ModelManagerSP.Chunk()
+    chunk.fileName = chunk_data.get("file_name")
+    chunk.sha256 = chunk_data.get("sha256")
+    return chunk
+
   @staticmethod
   def _parse_artifact(artifact_data) -> custom.ModelManagerSP.Artifact:
     artifact = custom.ModelManagerSP.Artifact()
     artifact.fileName = artifact_data.get("file_name")
     artifact.downloadUri = ModelParser._parse_download_uri(artifact_data.get("download_uri", {}))
+
+    if "chunks" in artifact_data:
+      artifact.chunks = [ModelParser._parse_chunk(chunk_data) for chunk_data in artifact_data["chunks"]]
+
+      try:
+        model_dir = Paths.model_root()
+        os.makedirs(model_dir, exist_ok=True)
+        manifest_path = os.path.join(model_dir, f"{artifact.fileName}.chunkmanifest")
+        num_chunks = str(len(artifact.chunks))
+
+        if not os.path.exists(manifest_path) or open(manifest_path).read().strip() != num_chunks:
+          with open(manifest_path, "w") as f:
+            f.write(num_chunks)
+          cloudlog.info(f"Wrote chunk manifest for {artifact.fileName}: {num_chunks} chunks")
+      except Exception as e:
+        cloudlog.warning(f"Failed to write chunk manifest for {artifact.fileName}: {e}")
+
     return artifact
 
   @staticmethod
@@ -112,8 +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_v25.json"
-  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v28.json"
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v23.json"
+  MODEL_URL_CHESTNUT = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_chestnut_v27.json"
 
   MODEL_SOURCES = {
     "qcom": (MODEL_URL, ""),
@@ -244,3 +270,5 @@ if __name__ == "__main__":
       model_overrides = {override.key: override.value for override in bundle.overrides}
       print(f"Bundle: {bundle.internalName}, Type: {model.type}, Status: {bundle.status}, Overrides: {model_overrides}")
       print(f"Artifact: {model.artifact.fileName}, Download URI: {model.artifact.downloadUri.uri}")
+      if model.artifact.chunks:
+        print(f"Contains {len(model.artifact.chunks)} chunks.")

openpilot/sunnypilot/models/helpers.py

@@ -16,7 +16,7 @@ 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 = 21
+REQUIRED_JSON_VERSION = 20
 
 CUSTOM_MODEL_PATH = Paths.model_root()
 ModelManager = custom.ModelManagerSP
@@ -29,8 +29,9 @@ _LAST_VALIDATED_RAW: dict[str, dict | None] = {}
 
 
 def _compute_hash(file_path: str) -> str | None:
+  from openpilot.common.file_chunker import open_file_chunked
   try:
-    with open(file_path, 'rb') as file:
+    with open_file_chunked(file_path) as file:
       return hashlib.file_digest(file, "sha256").hexdigest().lower()
   except FileNotFoundError:
     return None
@@ -57,11 +58,20 @@ def is_bundle_version_compatible(bundle: dict) -> bool:
 
 def _bundle_artifacts(bundle: custom.ModelManagerSP.ModelBundle) -> list[tuple[str, str]]:
   artifacts = []
+  from openpilot.common.file_chunker import get_chunk_name
   for model in getattr(bundle, 'models', []) or []:
-    artifact = getattr(model, 'artifact', None)
-    if artifact and getattr(artifact, 'fileName', None) and getattr(artifact, 'downloadUri', None):
-      if sha256 := getattr(artifact.downloadUri, 'sha256', None):
-        artifacts.append((artifact.fileName, sha256))
+    for artifact in (getattr(model, 'artifact', None),):
+      if artifact and getattr(artifact, 'fileName', None):
+        if len(artifact.chunks) > 0:
+          for i, chunk in enumerate(artifact.chunks):
+            chunk_name = get_chunk_name(artifact.fileName, i, len(artifact.chunks))
+            if getattr(chunk, 'sha256', None):
+              artifacts.append((chunk_name, chunk.sha256))
+        else:
+          if getattr(artifact, 'downloadUri', None):
+            sha256 = getattr(artifact.downloadUri, 'sha256', None)
+            if sha256:
+              artifacts.append((artifact.fileName, sha256))
   return artifacts
 
 

openpilot/sunnypilot/models/manager.py

@@ -109,6 +109,50 @@ class ModelManagerSP:
     # Clean up start time after download completes
     del self._download_start_times[model.fileName]
 
+  async def _download_chunked(self, base_url: str, base_path: str, artifact, skip: frozenset[int] | set[int] = frozenset()) -> None:
+    from openpilot.common.file_chunker import get_chunk_name, get_manifest_path
+
+    num_chunks = len(artifact.chunks)
+    if num_chunks == 0:
+      raise ValueError("No chunks defined in artifact")
+
+    manifest_path = get_manifest_path(base_path)
+    self._download_start_times[artifact.fileName] = time.monotonic()
+
+    # Shared connection saves a TCP+TLS handshake per chunk.
+    # Keep sequential: the link saturates on one stream and Session is not thread-safe.
+    completed = len(skip)
+    with requests.Session() as session:
+      for i, _ in enumerate(artifact.chunks):
+        if i in skip:
+          continue
+        chunk_url = get_chunk_name(base_url, i, num_chunks)
+        chunk_path = get_chunk_name(base_path, i, num_chunks)
+        chunk_downloaded = 0
+        with session.get(chunk_url, stream=True, timeout=DOWNLOAD_TIMEOUT) as response:
+          response.raise_for_status()
+          chunk_size = int(response.headers.get("content-length", 0))
+          with open(chunk_path, 'wb') as f:  # noqa: ASYNC230
+            for data in response.iter_content(chunk_size=self._chunk_size):
+              f.write(data)
+              chunk_downloaded += len(data)
+              if self._download_interrupted():
+                raise DownloadCancelled("Download cancelled")
+              intra = chunk_downloaded / max(chunk_size, 1)
+              progress = min(99.0, ((completed + intra) / num_chunks) * 100)
+              artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloading
+              artifact.downloadProgress.progress = progress
+              artifact.downloadProgress.eta = self._calculate_eta(artifact.fileName, progress)
+              self._sync_artifact_progress(artifact)
+              self._report_status()
+        completed += 1
+
+    with open(manifest_path, 'w') as f:  # noqa: ASYNC230
+      f.write(str(num_chunks))
+    if os.path.isfile(base_path):  # noqa: ASYNC240
+      os.remove(base_path)
+    del self._download_start_times[artifact.fileName]
+
   async def _process_artifact(self, artifact, destination_path: str) -> None:
     if not artifact.downloadUri.uri:
       return None
@@ -121,7 +165,28 @@ class ModelManagerSP:
     full_path = os.path.join(destination_path, filename)
 
     try:
-      if await verify_file(full_path, expected_hash):
+      # progress counts only valid chunks so a resumed download continues the
+      # bar from where verification left it, instead of falling back to zero
+      is_cached = False
+      valid_chunks: set[int] = set()
+      if len(artifact.chunks) > 0:
+        from openpilot.common.file_chunker import get_chunk_name
+        num_chunks = len(artifact.chunks)
+        for i, chunk in enumerate(artifact.chunks):
+          if self._download_interrupted():
+            raise DownloadCancelled("Download cancelled")
+          if await verify_file(get_chunk_name(full_path, i, num_chunks), chunk.sha256):
+            valid_chunks.add(i)
+          artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.verifying
+          artifact.downloadProgress.progress = (len(valid_chunks) / num_chunks) * 100
+          self._sync_artifact_progress(artifact)
+          self._report_status()
+        is_cached = len(valid_chunks) == num_chunks
+      else:
+        if await verify_file(full_path, expected_hash):
+          is_cached = True
+
+      if is_cached:
         artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.cached
         artifact.downloadProgress.progress = 100
         artifact.downloadProgress.eta = 0
@@ -129,9 +194,17 @@ class ModelManagerSP:
         self._report_status()
         return
 
-      await self._download_file(url, full_path, artifact)
-      if not await verify_file(full_path, expected_hash):
-        raise ValueError(f"Hash validation failed for {filename}")
+      if len(artifact.chunks) > 0:
+        await self._download_chunked(url, full_path, artifact, skip=valid_chunks)
+        from openpilot.common.file_chunker import get_chunk_name
+        for i, chunk in enumerate(artifact.chunks):
+          chunk_path = get_chunk_name(full_path, i, len(artifact.chunks))
+          if not await verify_file(chunk_path, chunk.sha256):
+            raise ValueError(f"Hash validation failed for chunk {i+1} of {filename}")
+      else:
+        await self._download_file(url, full_path, artifact)
+        if not await verify_file(full_path, expected_hash):
+          raise ValueError(f"Hash validation failed for {filename}")
 
       artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloaded
       artifact.downloadProgress.progress = 100
@@ -140,6 +213,7 @@ class ModelManagerSP:
       self._report_status()
 
     except DownloadCancelled:
+      # a cancel keeps whatever is on disk: complete chunks resume the next attempt
       self._download_start_times.pop(artifact.fileName, None)
       artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.failed
       artifact.downloadProgress.eta = 0
@@ -151,8 +225,9 @@ class ModelManagerSP:
 
     except Exception as e:
       cloudlog.error(f"Error downloading {filename}: {str(e)}")
-      if os.path.isfile(full_path):  # noqa: ASYNC240
-        os.remove(full_path)
+      for f in [full_path] + [p for p in (os.path.join(destination_path, f) for f in os.listdir(destination_path)) if filename in p]:
+        if os.path.isfile(f):  # noqa: ASYNC240
+          os.remove(f)
       artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.failed
       artifact.downloadProgress.eta = 0
       self._sync_artifact_progress(artifact)
@@ -285,11 +360,12 @@ class ModelManagerSP:
           if model.artifact.fileName:
             active_files.append(model.artifact.fileName)
 
-    # Remove all files except active ones
+    # Remove all files except active ones (including their chunk files)
     model_dir = Paths.model_root()
     try:
       for filename in os.listdir(model_dir):
-        if filename not in active_files:
+        base = filename.split('.chunk')[0] if '.chunk' in filename else filename
+        if base not in active_files and filename not in active_files:
           file_path = os.path.join(model_dir, filename)
           if os.path.isfile(file_path):
             os.remove(file_path)

openpilot/sunnypilot/models/tests/test_manager_download.py

@@ -17,9 +17,11 @@ from typing import Any
 from unittest import mock
 
 import requests
+from urllib3.connectionpool import HTTPConnectionPool
 
 from openpilot.cereal import custom
 from openpilot.common.test import OpenpilotTestCase
+from openpilot.common.file_chunker import get_chunk_name, get_manifest_path
 from openpilot.selfdrive.test.helpers import http_server_context
 from openpilot.sunnypilot.models import manager as manager_module
 from openpilot.sunnypilot.models.fetcher import ModelFetcher, get_cached_bundles
@@ -28,6 +30,7 @@ from openpilot.sunnypilot.models.helpers import (get_active_bundle, get_active_s
                                                   resolve_bundle_by_ref, validate_active_bundles)
 from openpilot.sunnypilot.models.manager import ModelManagerSP
 
+CHUNK_BODIES = [b'A' * 5000, b'B' * 5000, b'C' * 3000]
 WHOLE_BODY = b'Z' * 9000
 
 
@@ -46,7 +49,12 @@ class DownloadHandler(http.server.BaseHTTPRequestHandler):
     pass
 
   def _body_for(self, path):
-    return WHOLE_BODY if path.endswith('.pkl') else None
+    if path.endswith('.whole'):
+      return WHOLE_BODY
+    for i in range(len(CHUNK_BODIES)):
+      if path.endswith(get_chunk_name('', i, len(CHUNK_BODIES))):
+        return CHUNK_BODIES[i]
+    return None
 
   def do_GET(self):
     type(self).request_paths.append(self.path)
@@ -111,19 +119,35 @@ class ManagerDownloadTestBase(OpenpilotTestCase):
     if artifact is not None:
       self.reported.append(float(artifact.downloadProgress.progress))
 
-  def make_artifact(self):
+  def make_artifact(self, chunked: bool):
     bundle = custom.ModelManagerSP.ModelBundle.new_message()
     bundle.init('models', 1)
     artifact = bundle.models[0].artifact
     artifact.fileName = 'driving_test_tinygrad.pkl'
-    artifact.downloadUri.uri = self.base_url + '/driving_test_tinygrad.pkl'
-    artifact.downloadUri.sha256 = sha256(WHOLE_BODY)
+    if chunked:
+      artifact.downloadUri.uri = self.base_url + '/driving_test_tinygrad.pkl'
+      artifact.downloadUri.sha256 = sha256(b''.join(CHUNK_BODIES))
+      artifact.init('chunks', len(CHUNK_BODIES))
+      for i, body in enumerate(CHUNK_BODIES):
+        artifact.chunks[i].sha256 = sha256(body)
+    else:
+      artifact.downloadUri.uri = self.base_url + '/driving_test_tinygrad.pkl.whole'
+      artifact.downloadUri.sha256 = sha256(WHOLE_BODY)
     self._bundle = bundle
     self.artifact = artifact
     return artifact
 
+  def chunk_paths(self, base_path):
+    return [get_chunk_name(base_path, i, len(CHUNK_BODIES)) for i in range(len(CHUNK_BODIES))]
+
+  def assert_no_partials(self, base_path):
+    leftovers = [p for p in [base_path, get_manifest_path(base_path)] + self.chunk_paths(base_path)
+                 if os.path.isfile(p)]
+    assert leftovers == [], f"partial files left behind: {leftovers}"
+
+
 class TestManagerDownload(ManagerDownloadTestBase):
-  """Exercises the real _download_file against a local server."""
+  """Exercises the real _download_file / _download_chunked against a local server."""
 
   def run_with_server(self, fn):
     with http_server_context(handler=DownloadHandler) as (host, port):
@@ -132,7 +156,7 @@ class TestManagerDownload(ManagerDownloadTestBase):
 
   def test_download_file_writes_exact_bytes(self):
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=False)
       path = os.path.join(self.dest, artifact.fileName)
       asyncio.run(self.manager._download_file(artifact.downloadUri.uri, path, artifact))
       with open(path, 'rb') as f:
@@ -142,67 +166,111 @@ class TestManagerDownload(ManagerDownloadTestBase):
       assert artifact.fileName not in self.manager._download_start_times
     self.run_with_server(body)
 
+  def test_download_chunked_writes_all_chunks_and_manifest(self):
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+
+      for i, expected in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'rb') as f:
+          assert f.read() == expected, f"chunk {i} body mismatch"
+
+      with open(get_manifest_path(base_path)) as f:
+        assert f.read() == str(len(CHUNK_BODIES))
+
+      assert not os.path.isfile(base_path), "base file should be removed after chunking"
+      assert artifact.fileName not in self.manager._download_start_times
+    self.run_with_server(body)
+
   def test_progress_is_monotonic_and_bounded(self):
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
-      asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
 
       assert self.reported, "expected progress reports"
       for a, b in zip(self.reported, self.reported[1:], strict=False):
         assert b >= a, f"progress went backwards: {a} -> {b}"
+      assert max(self.reported) <= 99.0, f"chunked progress must stay <=99 until verify, got {max(self.reported)}"
+    self.run_with_server(body)
+
+  def test_session_is_reused_across_chunks(self):
+    """One connection pool shared across every chunk."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+
+      pools = []
+      original = HTTPConnectionPool.urlopen
+
+      def tracked(pool_self, *args, **kwargs):
+        pools.append(id(pool_self))
+        return original(pool_self, *args, **kwargs)
+
+      with mock.patch.object(HTTPConnectionPool, 'urlopen', tracked):
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+
+      assert len(pools) == len(CHUNK_BODIES), f"expected one request per chunk, got {len(pools)}"
+      assert len(set(pools)) == 1, f"connection pool not reused across chunks: {len(set(pools))} pools"
     self.run_with_server(body)
 
   def test_http_error_propagates(self):
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
-      DownloadHandler.fail_paths = {'/' + artifact.fileName: 404}
+      failing = '/' + os.path.basename(get_chunk_name(artifact.downloadUri.uri, 1, len(CHUNK_BODIES)))
+      DownloadHandler.fail_paths = {failing: 404}
 
       with self.assertRaises(requests.exceptions.HTTPError):
-        asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
-      assert not os.path.isfile(base_path)
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+
+      # chunk 1 failed, so its file and the manifest must not exist
+      assert not os.path.isfile(get_chunk_name(base_path, 1, len(CHUNK_BODIES)))
+      assert not os.path.isfile(get_manifest_path(base_path))
     self.run_with_server(body)
 
   def test_cancellation_mid_transfer(self):
     """Cancellation is checked inside the byte loop; it must still fire after the port."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
       self.manager.params.get.return_value = None  # cancelled
 
       with self.assertRaises(Exception) as ctx:
-        asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
       assert 'cancelled' in str(ctx.exception).lower()
+      assert not os.path.isfile(get_manifest_path(base_path))
     self.run_with_server(body)
 
   def test_repeat_downloads_are_stable(self):
     """Back-to-back runs must produce identical bytes and leak no start-time state."""
     def body():
       for _ in range(2):
-        artifact = self.make_artifact()
+        artifact = self.make_artifact(chunked=True)
         base_path = os.path.join(self.dest, artifact.fileName)
-        asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
-        with open(base_path, 'rb') as f:
-          assert f.read() == WHOLE_BODY
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+        for i, expected in enumerate(CHUNK_BODIES):
+          with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'rb') as f:
+            assert f.read() == expected
         assert self.manager._download_start_times == {}
     self.run_with_server(body)
 
   def test_download_ref_present_keeps_download_alive(self):
     """A pending download request (DownloadRef set) must not be cancelled mid-transfer."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
       self.manager.params.get.side_effect = lambda key: b"ref" if key == "ModelManager_DownloadRef" else None
       self.manager._download_ref = b"ref"
-      asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
-      assert os.path.isfile(base_path)
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+      assert os.path.isfile(get_manifest_path(base_path))
     self.run_with_server(body)
 
   def test_cancellation_via_download_ref(self):
     """Removing DownloadRef mid-transfer cancels the download."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
       checks = {"n": 0}
 
@@ -215,19 +283,20 @@ class TestManagerDownload(ManagerDownloadTestBase):
       self.manager.params.get.side_effect = get
       self.manager._download_ref = b"ref"
       with self.assertRaises(Exception) as ctx:
-        asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
+        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
       assert 'cancelled' in str(ctx.exception).lower()
+      assert not os.path.isfile(get_manifest_path(base_path))
     self.run_with_server(body)
 
   def test_replaced_download_ref_queues_instead_of_cancelling(self):
     """Selecting another model mid-transfer lets the running download finish."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
       self.manager.params.get.side_effect = lambda key: b"other-ref" if key == "ModelManager_DownloadRef" else None
       self.manager._download_ref = b"ref"
-      asyncio.run(self.manager._download_file(artifact.downloadUri.uri, base_path, artifact))
-      assert os.path.isfile(base_path)
+      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
+      assert os.path.isfile(get_manifest_path(base_path))
     self.run_with_server(body)
 
   def test_replaced_download_ref_is_kept(self):
@@ -246,10 +315,11 @@ class TestManagerDownload(ManagerDownloadTestBase):
   def test_cached_bundle_cancel_skips_slot_write(self):
     """A cancel must stop an already-on-disk bundle before it is applied to the slot."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       base_path = os.path.join(self.dest, artifact.fileName)
-      with open(base_path, 'wb') as f:
-        f.write(WHOLE_BODY)
+      for i, data in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'wb') as f:
+          f.write(data)
       self._bundle.ref = "test-ref"
       params, store = self._make_params_with_store()
       store["ModelManager_DownloadRef"] = None  # removed -> cancelled
@@ -259,7 +329,42 @@ class TestManagerDownload(ManagerDownloadTestBase):
         asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "qcom"))
       assert 'cancelled' in str(ctx.exception).lower()
       assert "ModelManager_ActiveBundle" not in store
-      assert os.path.isfile(base_path), "cancel must not delete the cached model"
+      assert all(os.path.isfile(p) for p in self.chunk_paths(base_path)), "cancel must not delete cached chunks"
+    self.run_with_server(body)
+
+  def test_resume_skips_valid_chunks(self):
+    """A chunk already on disk is kept and not re-downloaded; progress starts above its share."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      with open(get_chunk_name(base_path, 0, len(CHUNK_BODIES)), 'wb') as f:
+        f.write(CHUNK_BODIES[0])
+
+      asyncio.run(self.manager._process_artifact(artifact, self.dest))
+
+      chunk0_suffix = get_chunk_name('', 0, len(CHUNK_BODIES))
+      assert not any(p.endswith(chunk0_suffix) for p in DownloadHandler.request_paths), "valid chunk was re-downloaded"
+      for i, expected in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'rb') as f:
+          assert f.read() == expected
+      assert os.path.isfile(get_manifest_path(base_path))
+      assert min(self.reported) >= (1 / len(CHUNK_BODIES)) * 100 - 1, "progress must not restart below the resumed share"
+    self.run_with_server(body)
+
+  def test_verify_reports_valid_fraction_then_cached(self):
+    """A fully cached bundle publishes climbing verify progress and ends cached."""
+    def body():
+      artifact = self.make_artifact(chunked=True)
+      base_path = os.path.join(self.dest, artifact.fileName)
+      for i, data in enumerate(CHUNK_BODIES):
+        with open(get_chunk_name(base_path, i, len(CHUNK_BODIES)), 'wb') as f:
+          f.write(data)
+
+      asyncio.run(self.manager._process_artifact(artifact, self.dest))
+
+      assert DownloadHandler.request_paths == [], "cached bundle must not hit the network"
+      assert [round(p) for p in self.reported[:3]] == [33, 67, 100]
+      assert artifact.downloadProgress.status == custom.ModelManagerSP.DownloadStatus.cached
     self.run_with_server(body)
 
   def _make_params_with_store(self):
@@ -279,7 +384,7 @@ class TestManagerDownload(ManagerDownloadTestBase):
   def test_download_writes_qcom_slot(self):
     """A download resolved to the qcom source writes the qcom active bundle slot only."""
     def body():
-      artifact = self.make_artifact()
+      artifact = self.make_artifact(chunked=True)
       self._bundle.ref = "test-ref"
       self._bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
       params, store = self._make_params_with_store()
@@ -291,13 +396,15 @@ class TestManagerDownload(ManagerDownloadTestBase):
       assert self.manager.selected_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
       assert self.manager.active_bundle is not None and self.manager.active_bundle.ref == "test-ref"
       assert self.manager.active_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
-      assert os.path.isfile(os.path.join(self.dest, artifact.fileName))
+      chunk_names = [get_chunk_name(artifact.fileName, i, len(artifact.chunks)) for i in range(len(artifact.chunks))]
+      missing = [c for c in chunk_names if not os.path.isfile(os.path.join(self.dest, c))]
+      assert missing == [], f"chunks missing from the cache: {missing}"
     self.run_with_server(body)
 
   def test_download_writes_chestnut_slot(self):
     """A download resolved to the chestnut source writes the chestnut active bundle slot only."""
     def body():
-      self.make_artifact()
+      self.make_artifact(chunked=True)
       self._bundle.ref = "big-ref"
       self._bundle.minimumSelectorVersion = helpers.REQUIRED_JSON_VERSION
       params, store = self._make_params_with_store()
@@ -675,7 +782,7 @@ class TestEffectiveSource(OpenpilotTestCase):
 
 @unittest.skipUnless(os.environ.get('RUN_INTEGRATION_TESTS'), 'requires external network')
 class TestLiveModelManifest(OpenpilotTestCase):
-  """Every artifact URL in the published manifest must resolve."""
+  """Every artifact and chunk URL in the published manifest must resolve."""
 
   def test_all_manifest_urls_available(self):
     from openpilot.sunnypilot.models.fetcher import ModelFetcher
@@ -687,7 +794,10 @@ class TestLiveModelManifest(OpenpilotTestCase):
     for bundle in manifest.get('bundles', []):
       for model in bundle.get('models', []):
         artifact = model['artifact']
-        urls = [artifact['download_uri']['url']]
+        url = artifact['download_uri']['url']
+        chunks = artifact.get('chunks', [])
+        urls = ([url] if not chunks
+                else [get_chunk_name(url, i, len(chunks)) for i in range(len(chunks))])
         for u in urls:
           try:
             r = session.head(u, timeout=15, allow_redirects=True)

openpilot/sunnypilot/selfdrive/car/intelligent_cruise_button_management/controller.py

@@ -115,7 +115,7 @@ class IntelligentCruiseButtonManagement:
     self.is_ready = ready and not button_pressed
 
   def run(self, CS: car.CarState, CC: car.CarControl, LP_SP: custom.LongitudinalPlanSP, is_metric: bool) -> None:
-    if self.CP_SP.pcmCruiseSpeed:
+    if self.CP_SP.pcmCruiseSpeed or not self.CP_SP.intelligentCruiseButtonManagementAvailable:
       return
 
     self.is_metric = is_metric

openpilot/sunnypilot/selfdrive/car/interfaces.py

@@ -127,6 +127,10 @@ def initialize_params(params) -> list[dict[str, Any]]:
   keys.extend([
     "ToyotaEnforceStockLongitudinal",
     "ToyotaStopAndGoHack",
+    "ToyotaTSS2Long",
+    "ToyotaEnhancedBsm",
+    "ToyotaAutoHold",
+    "ToyotaBrakeOnset",
   ])
 
   return [{k: params.get(k, return_default=True)} for k in keys]

openpilot/sunnypilot/selfdrive/car/tests/test_custom_cruise.py

@@ -1,14 +1,26 @@
+from opendbc.can.parser import CANParser
+from opendbc.car import create_button_events
 from opendbc.car.structs import car
+from opendbc.car.toyota.carstate import get_virtual_cruise_button, VIRTUAL_CRUISE_BUTTONS
+from openpilot.cereal import custom
 from openpilot.common.constants import CV
 from openpilot.common.parameterized import parameterized, parameterized_class
 from openpilot.common.params import Params
-from openpilot.selfdrive.car.cruise import V_CRUISE_INITIAL
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.car.cruise import TOYOTA_VIRTUAL_CRUISE_LONG_PRESS, VCruiseHelper, V_CRUISE_INITIAL, V_CRUISE_UNSET
 from openpilot.selfdrive.car.tests.test_cruise_speed import TestVCruiseHelper
+from openpilot.sunnypilot.selfdrive.car.interfaces import initialize_params
 
 ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 
 
+class TestToyotaParamsHandoff(OpenpilotTestCase):
+  def test_tss2_long_tuning_param_is_forwarded_to_opendbc(self):
+    keys = {next(iter(entry)) for entry in initialize_params(Params())}
+    assert "ToyotaTSS2Long" in keys
+
+
 # TODO: test pcmCruise and pcmCruiseSpeed
 @parameterized_class(('pcm_cruise', 'pcm_cruise_speed'), [(False, True)])
 class TestCustomAccIncrements(TestVCruiseHelper):
@@ -114,8 +126,8 @@ class TestCustomAccIncrements(TestVCruiseHelper):
   def test_rounding_behavior(self):
     """Test rounding behavior for 5 and 10 increments"""
     test_cases = [
-      (47, 5, 50),   # 47 -> 50 (round up to next 5)
-      (45, 5, 50),   # 45 -> 50 (already at 5, increment by 5)
+      (47, 5, 50),  # 47 -> 50 (round up to next 5)
+      (45, 5, 50),  # 45 -> 50 (already at 5, increment by 5)
       (43, 10, 50),  # 43 -> 50 (round up to next 10)
       (40, 10, 50),  # 40 -> 50 (already at 10, increment by 10)
     ]
@@ -146,3 +158,302 @@ class TestCustomAccIncrements(TestVCruiseHelper):
     initial_speed = self.v_cruise_helper.v_cruise_kph
     self.press_button_long(ButtonType.accelCruise)
     assert self.v_cruise_helper.v_cruise_kph == initial_speed + 10  # Should fallback to 10
+
+
+class TestToyotaVirtualCruiseSpeed(OpenpilotTestCase):
+  def setup_method(self):
+    self.params = Params()
+    self.params.put_bool("CustomAccIncrementsEnabled", True, block=True)
+    self.params.put("CustomAccShortPressIncrement", 5, block=True)
+    self.params.put("CustomAccLongPressIncrement", 5, block=True)
+
+    CP = car.CarParams(brand="toyota", pcmCruise=True, openpilotLongitudinalControl=True)
+    CP_SP = custom.CarParamsSP(pcmCruiseSpeed=False)
+    self.v_cruise_helper = VCruiseHelper(CP, CP_SP)
+    self.v_cruise_helper.read_custom_set_speed_params()
+    self.route_parser = CANParser("toyota_nodsu_pt_generated", [("CLUTCH", 16)], 0)
+    self.route_button = 0
+
+  @staticmethod
+  def car_state(canonical_kph, cluster_kph, *, available=True, standstill=False, gas_pressed=False, v_ego_kph=0.0, button_events=None):
+    CS = car.CarState(
+      gasPressed=gas_pressed,
+      vEgo=v_ego_kph * CV.KPH_TO_MS,
+      cruiseState={
+        "available": available,
+        "speed": canonical_kph * CV.KPH_TO_MS,
+        "speedCluster": cluster_kph * CV.KPH_TO_MS,
+        "standstill": standstill,
+      },
+    )
+    CS.buttonEvents = button_events or []
+    return CS
+
+  def seed_enabled(self, canonical_kph, cluster_kph, *, is_metric=True):
+    CS = self.car_state(canonical_kph, cluster_kph)
+    self.v_cruise_helper.update_v_cruise(CS, enabled=False, is_metric=is_metric)
+    self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
+    self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
+    assert self.v_cruise_helper.v_cruise_kph == canonical_kph
+    assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
+
+  def press(self, button_type, canonical_kph, cluster_kph, hold_frames=0, *, standstill=False, gas_pressed=False, v_ego_kph=0.0, is_metric=True):
+    pressed = [ButtonEvent(type=button_type, pressed=True)]
+    self.v_cruise_helper.update_v_cruise(
+      self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=pressed),
+      enabled=True,
+      is_metric=is_metric,
+    )
+    for _ in range(hold_frames):
+      self.v_cruise_helper.update_v_cruise(
+        self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph),
+        enabled=True,
+        is_metric=is_metric,
+      )
+    released = [ButtonEvent(type=button_type, pressed=False)]
+    self.v_cruise_helper.update_v_cruise(
+      self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=released),
+      enabled=True,
+      is_metric=is_metric,
+    )
+
+  def set_increments(self, short_increment, long_increment):
+    self.params.put("CustomAccShortPressIncrement", short_increment, block=True)
+    self.params.put("CustomAccLongPressIncrement", long_increment, block=True)
+    self.v_cruise_helper.read_custom_set_speed_params()
+
+  def assert_kph_almost_equal(self, actual, expected):
+    self.assertAlmostEqual(actual, expected, delta=abs(expected) * 1e-6)
+
+  def route_button_events(self, payload):
+    self.route_parser.update((1, [(0x361, bytes.fromhex(payload), 0)]))
+    current = get_virtual_cruise_button(
+      self.route_parser.vl["CLUTCH"]["CRUISE_RES"],
+      self.route_parser.vl["CLUTCH"]["CRUISE_SET"],
+    )
+    events = create_button_events(current, self.route_button, VIRTUAL_CRUISE_BUTTONS)
+    self.route_button = current
+    return events
+
+  def test_short_press_rounds_display_target_and_preserves_offset(self):
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.accelCruise, 28, 32)
+
+    assert self.v_cruise_helper.v_cruise_kph == 31
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
+
+  def test_decel_at_display_minimum_does_not_increase_target(self):
+    self.seed_enabled(26, 30)
+    self.press(ButtonType.decelCruise, 25, 29)
+
+    assert self.v_cruise_helper.v_cruise_kph == 26
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 30
+
+  @parameterized.expand((52, TOYOTA_VIRTUAL_CRUISE_LONG_PRESS - 1))
+  def test_route_length_short_press_is_not_a_long_press(self, hold_frames):
+    self.set_increments(short_increment=2, long_increment=5)
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.accelCruise, 28, 32, hold_frames=hold_frames)
+
+    assert self.v_cruise_helper.v_cruise_kph == 29
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 33
+
+  def test_toyota_long_press_uses_route_validated_cadence_and_suppresses_release(self):
+    self.set_increments(short_increment=2, long_increment=5)
+    self.seed_enabled(27, 31)
+
+    pressed = [ButtonEvent(type=ButtonType.accelCruise, pressed=True)]
+    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
+    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
+      self.v_cruise_helper.update_v_cruise(self.car_state(31, 35), enabled=True, is_metric=True)
+
+    assert self.v_cruise_helper.v_cruise_kph == 31
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
+
+    released = [ButtonEvent(type=ButtonType.accelCruise, pressed=False)]
+    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=released), enabled=True, is_metric=True)
+    assert self.v_cruise_helper.v_cruise_kph == 31
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
+
+  def test_route_4_32_second_hold_repeats_six_times(self):
+    self.seed_enabled(26, 30)
+    self.press(ButtonType.accelCruise, 30, 34, hold_frames=432)
+
+    assert self.v_cruise_helper.v_cruise_kph == 56
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 60
+
+  def test_maximum_boundary_caps_pair_and_preserves_offset(self):
+    self.seed_enabled(141, 145)
+    self.press(ButtonType.accelCruise, 142, 146)
+
+    assert self.v_cruise_helper.v_cruise_kph == 141
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 145
+
+    self.press(ButtonType.accelCruise, 143, 147)
+    assert self.v_cruise_helper.v_cruise_kph == 141
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 145
+
+  @parameterized.expand(
+    (
+      (25, 29, ButtonType.decelCruise),
+      (141, 147, ButtonType.accelCruise),
+    )
+  )
+  def test_out_of_range_raw_pair_is_not_moved_in_opposite_direction(self, canonical_kph, cluster_kph, button_type):
+    self.seed_enabled(canonical_kph, cluster_kph)
+    self.press(button_type, canonical_kph, cluster_kph)
+
+    assert self.v_cruise_helper.v_cruise_kph == canonical_kph
+    assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
+
+  def test_imperial_increment_preserves_canonical_cluster_pair(self):
+    self.seed_enabled(45, 50, is_metric=False)
+    self.press(ButtonType.accelCruise, 46, 51, is_metric=False)
+
+    assert self.v_cruise_helper.v_cruise_kph == 51
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 56
+
+  def test_engagement_button_held_does_not_change_target(self):
+    initial = self.car_state(27, 31)
+    self.v_cruise_helper.update_v_cruise(initial, enabled=False, is_metric=True)
+
+    pressed = [ButtonEvent(type=ButtonType.decelCruise, pressed=True)]
+    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=False, is_metric=True)
+    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS + 10):
+      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+
+    released = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+
+    assert self.v_cruise_helper.v_cruise_kph == 28
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 32
+
+  def test_delayed_pcm_target_seeds_before_software_ownership(self):
+    invalid = self.car_state(0, 0)
+    self.v_cruise_helper.update_v_cruise(invalid, enabled=False, is_metric=True)
+
+    release = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
+    for _ in range(4):
+      self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, button_events=release), enabled=True, is_metric=True)
+      assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
+      assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31), enabled=True, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
+
+  def test_route_payload_short_press_drives_virtual_target(self):
+    self.seed_enabled(27, 31)
+
+    pressed = self.route_button_events("a61a0000561a1a81")
+    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
+    for _ in range(52):
+      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+
+    released = self.route_button_events("861a0000561b1a81")
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
+    assert self.v_cruise_helper.v_cruise_kph == 31
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
+
+  def test_prius_route_payload_short_set_drives_virtual_target(self):
+    self.seed_enabled(31, 35)
+
+    pressed = self.route_button_events("965f000056666585")
+    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
+    for _ in range(45):
+      self.v_cruise_helper.update_v_cruise(self.car_state(30, 34), enabled=True, is_metric=True)
+
+    released = self.route_button_events("865f000056666585")
+    self.v_cruise_helper.update_v_cruise(self.car_state(30, 34, button_events=released), enabled=True, is_metric=True)
+    assert self.v_cruise_helper.v_cruise_kph == 26
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 30
+
+  def test_prius_route_payload_standstill_res_does_not_change_target(self):
+    self.seed_enabled(27, 31)
+
+    pressed = self.route_button_events("a61b0000561c1c80")
+    self.v_cruise_helper.update_v_cruise(
+      self.car_state(27, 31, standstill=True, button_events=pressed),
+      enabled=True,
+      is_metric=True,
+    )
+    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
+      self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, standstill=True), enabled=True, is_metric=True)
+
+    released = self.route_button_events("865f000056666585")
+    self.v_cruise_helper.update_v_cruise(
+      self.car_state(27, 31, standstill=True, button_events=released),
+      enabled=True,
+      is_metric=True,
+    )
+    assert self.v_cruise_helper.v_cruise_kph == 27
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 31
+
+  def test_route_payload_disengage_mid_hold_clears_pending_action(self):
+    self.seed_enabled(27, 31)
+
+    pressed = self.route_button_events("a61a0000561a1a81")
+    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
+    for _ in range(30):
+      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
+    released = self.route_button_events("861a0000561b1a81")
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, available=False, button_events=released), enabled=False, is_metric=True)
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
+
+  def test_standstill_resume_does_not_change_target(self):
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.accelCruise, 27, 31, standstill=True)
+
+    assert self.v_cruise_helper.v_cruise_kph == 27
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 31
+
+  def test_disengagement_discards_virtual_target_and_reseeds_raw_pair(self):
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.accelCruise, 28, 32)
+    assert self.v_cruise_helper.v_cruise_kph == 31
+
+    raw = self.car_state(28, 32)
+    self.v_cruise_helper.update_v_cruise(raw, enabled=False, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
+
+    self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
+    self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
+
+  def test_unavailable_and_mads_handback_discard_virtual_target(self):
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.accelCruise, 28, 32)
+    assert self.v_cruise_helper.v_cruise_kph == 31
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, available=False), enabled=False, is_metric=True)
+    assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
+    assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
+
+    self.v_cruise_helper.update_v_cruise(self.car_state(29, 33), enabled=False, is_metric=True)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 29)
+    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 33)
+
+  def test_set_during_gas_override_clips_target_to_ego_speed(self):
+    self.seed_enabled(27, 31)
+    self.press(ButtonType.decelCruise, 26, 30, gas_pressed=True, v_ego_kph=50)
+
+    assert self.v_cruise_helper.v_cruise_kph == 50
+    assert self.v_cruise_helper.v_cruise_cluster_kph == 54

openpilot/sunnypilot/selfdrive/controls/controlsd_ext.py

@@ -12,11 +12,13 @@ from openpilot.cereal import log, custom
 from opendbc.car import structs
 from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
+from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
 from openpilot.sunnypilot import PARAMS_UPDATE_PERIOD
 from openpilot.sunnypilot.livedelay.helpers import get_lat_delay
 from openpilot.sunnypilot.modeld_v2.modeld_base import ModelStateBase
 from openpilot.sunnypilot.selfdrive.controls.lib.blinker_pause_lateral import BlinkerPauseLateral
 from openpilot.sunnypilot.selfdrive.controls.lib.latcontrol_torque_v0 import LatControlTorque as LatControlTorqueV0
+from openpilot.sunnypilot.selfdrive.controls.lib.stopping_controller import StoppingController
 
 
 class ControlsExt(ModelStateBase):
@@ -31,6 +33,9 @@ class ControlsExt(ModelStateBase):
     self.CP_SP = messaging.log_from_bytes(params.get("CarParamsSP", block=True), custom.CarParamsSP)
     cloudlog.info("controlsd_ext got CarParamsSP")
 
+    self.stopping_controller = StoppingController(self.CP.stopAccel) if params.get_bool("SunnypilotStoppingController") else None
+    self._stopping_prev = (LongCtrlState.off, 0.0)
+
     self.sm_services_ext = ['radarState', 'selfdriveStateSP']
     self.pm_services_ext = ['carControlSP']
 
@@ -47,6 +52,27 @@ class ControlsExt(ModelStateBase):
     else:
       return lac
 
+  def long_accel_sp(self, actuators, CS, long_plan, accel_limits: tuple[float, float]) -> None:
+    """sunnypilot: terminal-stop policy applied after the stock LongControl.update() (see stopping_controller.py)."""
+    stock_state = self.LoC.long_control_state
+    stock_accel = actuators.accel
+    prev_state, prev_accel = self._stopping_prev
+    self._stopping_prev = (stock_state, stock_accel)
+
+    if self.stopping_controller is None:
+      return
+
+    state, accel = self.stopping_controller.update(
+      prev_state, stock_state, CS, long_plan.aTarget, prev_accel, stock_accel, accel_limits, long_plan.hasLead,
+      pitch=self.calibrated_pose.orientation.pitch if self.calibrated_pose is not None else None,
+      a_long=self.calibrated_pose.acceleration.x if self.calibrated_pose is not None else None)
+    if state != stock_state:
+      self.LoC.reset()
+    self.LoC.long_control_state = state
+    self.LoC.last_output_accel = accel
+    self._stopping_prev = (state, accel)
+    actuators.accel = float(accel)
+
   def get_params_sp(self, sm: messaging.SubMaster) -> None:
     if time.monotonic() - self._param_update_time > PARAMS_UPDATE_PERIOD:
       self.blinker_pause_lateral.get_params()

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/accel_controller.py

@@ -0,0 +1,108 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import numpy as np
+
+from openpilot.cereal import custom
+from openpilot.common.params import Params
+from openpilot.sunnypilot import get_sanitize_int_param
+
+AccelProfile = custom.LongitudinalPlanSP.AccelController.Profile
+
+MAX_ACCEL_BREAKPOINTS = [0., 3., 12,  24., 36.]  # m/s
+MAX_ACCEL_PROFILES = {
+  AccelProfile.eco:    [1.75, 1.50, 0.40, 0.15, 0.12],
+  AccelProfile.normal: [1.95, 1.80, 0.70, 0.36, 0.25],
+  AccelProfile.sport:  [2.00, 2.00, 1.20, 0.70, 0.50],
+}
+ECO_ENGINE_OFF_BP = [0., 3., 12., 16.67, 19.44, 22.22, 24., 36.]  # m/s
+ECO_ENGINE_OFF_MAX_ACCEL = [1.75, 1.50, 0.35, 0.25, 0.16, 0.12, 0.08, 0.06]
+
+CRUISE_DECEL_RESPONSE_TIME = {
+  AccelProfile.normal: 3.5,
+  AccelProfile.sport: 3.0,
+}
+CRUISE_DECEL_ACCEL = {
+  AccelProfile.normal: -0.50,
+  AccelProfile.sport: -0.65,
+}
+ECO_CRUISE_DECEL_BP = [0., 16.67, 19.44, 25.0, 33.3]   # m/s
+ECO_CRUISE_DECEL_V = [-0.40, -0.40, -0.22, -0.30, -0.40]  # m/s^2
+ECO_COAST_BLEND_BP = [16.67, 19.44]  # m/s
+ECO_COAST_MIN, ECO_COAST_MAX = -1.2, -0.05  # m/s^2
+ECO_BOOST_DV_BP = [0.3, 2.5]     # m/s, lead speed minus ego speed
+ECO_BOOST_V = [0.0, 0.35]        # m/s^2 added to the eco limit
+ECO_BOOST_FADE_BP = [19.44, 22.22]  # m/s (70 -> 80 km/h): full -> none
+ECO_BOOST_D_MAX = 80.0           # m, only a lead this close counts
+ECO_BOOST_PROB_MIN = 0.5
+ECO_BOOST_RISE = 0.25            # m/s^3, how fast the boost builds
+ECO_BOOST_FALL = 0.5             # m/s^3, how fast it fades
+ECO_BOOST_DT = 0.05              # s, planner step
+CRUISE_DECEL_TAPER_TIME = 1.0  # s; inside |decel| * this of the target the decel eases off proportionally (no overshoot)
+
+
+class AccelController:
+  def __init__(self):
+    self.params = Params()
+    self._cruise_decel: float | None = None
+    self._cruise_decel_target: float | None = None
+    self._boost = 0.0
+    self.update()
+
+  def update(self) -> None:
+    self._profile = get_sanitize_int_param("AccelPersonality", AccelProfile.eco, AccelProfile.sport, self.params)
+    self._enabled = self.params.get_bool("AccelPersonalityEnabled")
+
+  @property
+  def profile(self) -> int:
+    return self._profile
+
+  def is_enabled(self) -> bool:
+    return self._enabled
+
+  def get_max_accel(self, v_ego: float, engine_off: bool = False, lead=None) -> float:
+    if engine_off and self._profile == AccelProfile.eco:
+      base = float(np.interp(max(0.0, v_ego), ECO_ENGINE_OFF_BP, ECO_ENGINE_OFF_MAX_ACCEL))
+    else:
+      base = float(np.interp(max(0.0, v_ego), MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[self._profile]))
+    if self._profile != AccelProfile.eco:
+      self._boost = 0.0
+      return base
+    return base + self._eco_lead_boost(v_ego, base, lead)
+
+  def _eco_lead_boost(self, v_ego: float, base: float, lead) -> float:
+    target = 0.0
+    if lead is not None and lead.present and lead.modelProb > ECO_BOOST_PROB_MIN and lead.dRel < ECO_BOOST_D_MAX:
+      target = float(np.interp(lead.vLead - v_ego, ECO_BOOST_DV_BP, ECO_BOOST_V))
+      target *= float(np.interp(v_ego, ECO_BOOST_FADE_BP, [1.0, 0.0]))
+      normal = float(np.interp(max(0.0, v_ego), MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.normal]))
+      target = float(np.clip(target, 0.0, max(normal - base, 0.0)))
+    step = (ECO_BOOST_RISE if target > self._boost else ECO_BOOST_FALL) * ECO_BOOST_DT
+    self._boost = float(np.clip(target, self._boost - step, self._boost + step))
+    return self._boost
+
+  def get_cruise_target(self, v_ego: float, v_target: float, accel_coast: float | None = None) -> float:
+    if not np.isfinite(v_target) or v_target <= 0.0 or v_target >= v_ego:
+      self._cruise_decel = None
+      self._cruise_decel_target = None
+      return v_target
+
+    target_delta = v_target - v_ego
+    if self._profile == AccelProfile.eco:
+      decel = float(np.interp(v_ego, ECO_CRUISE_DECEL_BP, ECO_CRUISE_DECEL_V))
+      if accel_coast is not None and np.isfinite(accel_coast) and accel_coast < 0.0:
+        coast = float(np.clip(accel_coast, ECO_COAST_MIN, ECO_COAST_MAX))
+        w = float(np.interp(v_ego, ECO_COAST_BLEND_BP, [0.0, 1.0]))
+        decel = (1.0 - w) * ECO_CRUISE_DECEL_V[1] + w * coast
+    else:
+      if self._cruise_decel is None or self._cruise_decel_target != v_target:
+        self._cruise_decel = min(CRUISE_DECEL_ACCEL[self._profile], target_delta / CRUISE_DECEL_RESPONSE_TIME[self._profile])
+        self._cruise_decel_target = v_target
+      decel = self._cruise_decel
+
+    decel = max(decel, target_delta / CRUISE_DECEL_TAPER_TIME)
+    return float(v_ego + decel)

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/tests/test_accel_controller.py

@@ -0,0 +1,142 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from types import SimpleNamespace
+
+import numpy as np
+
+from opendbc.car.interfaces import ACCEL_MAX
+from openpilot.common.params import Params
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
+  AccelController, AccelProfile, CRUISE_DECEL_ACCEL, CRUISE_DECEL_RESPONSE_TIME, ECO_CRUISE_DECEL_BP,
+  ECO_CRUISE_DECEL_V, ECO_ENGINE_OFF_MAX_ACCEL, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES,
+)
+
+
+class TestAccelController(OpenpilotTestCase):
+  def setUp(self):
+    self.params = Params()
+    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
+    self.params.put("AccelPersonality", AccelProfile.normal, block=True)
+
+  def set_profile(self, profile: int) -> AccelController:
+    self.params.put("AccelPersonality", profile, block=True)
+    return AccelController()
+
+  def test_table_breakpoints(self):
+    for profile, values in MAX_ACCEL_PROFILES.items():
+      controller = self.set_profile(profile)
+      for speed, expected in zip(MAX_ACCEL_BREAKPOINTS, values, strict=True):
+        assert controller.get_max_accel(speed) == expected
+
+  def test_profiles_are_ordered_monotonic_and_bounded(self):
+    controllers = {
+      profile: self.set_profile(profile)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
+    }
+    previous = {profile: float("inf") for profile in controllers}
+
+    for speed in np.linspace(0.0, 55.0, 551):
+      values = {profile: controller.get_max_accel(speed) for profile, controller in controllers.items()}
+      assert 0.0 <= values[AccelProfile.eco] <= values[AccelProfile.normal] <= values[AccelProfile.sport] <= ACCEL_MAX
+      for profile, value in values.items():
+        assert value <= previous[profile]
+        previous[profile] = value
+
+  def test_engine_off_line_only_lowers_eco(self):
+    speeds = np.linspace(0.0, 40.0, 401)
+    eco = self.set_profile(AccelProfile.eco)
+    for speed in speeds:
+      assert eco.get_max_accel(speed, engine_off=True) <= eco.get_max_accel(speed) + 1e-12
+    for speed, expected in zip(MAX_ACCEL_BREAKPOINTS, ECO_ENGINE_OFF_MAX_ACCEL, strict=True):
+      assert eco.get_max_accel(speed, engine_off=True) == expected
+
+    for profile in (AccelProfile.normal, AccelProfile.sport):
+      controller = self.set_profile(profile)
+      for speed in speeds:
+        assert controller.get_max_accel(speed, engine_off=True) == controller.get_max_accel(speed)
+
+  def test_engine_off_eco_line_respects_hybrid_power_budget(self):
+    controller = self.set_profile(AccelProfile.eco)
+    for kph, budget_kw in ((60, 11.5), (70, 11.5), (80, 13.5)):
+      speed = kph / 3.6
+      road_load = (0.010 * 1500 * 9.81 + 0.5 * 1.2 * 0.82 * speed * speed) * speed
+      wheel_power = 1500 * controller.get_max_accel(speed, engine_off=True) * speed + road_load
+      assert wheel_power <= budget_kw * 1e3, kph
+
+  def test_lead_boost_is_eco_only_and_absent_without_a_lead(self):
+    # the eco lead pull-away boost: no lead is the plain table lookup, and normal/sport ignore the lead entirely
+    eco = self.set_profile(AccelProfile.eco)
+    assert eco.get_max_accel(1.0, lead=None) == eco.get_max_accel(1.0)
+    assert eco.get_max_accel(20.0, lead=None) == eco.get_max_accel(20.0)
+
+    normal = self.set_profile(AccelProfile.normal)
+    lead = SimpleNamespace(present=True, modelProb=0.9, dRel=30.0, vLead=23.0)
+    assert normal.get_max_accel(20.0, lead=lead) == normal.get_max_accel(20.0)
+
+  def test_sport_uses_openpilot_accel_max_at_launch(self):
+    controller = self.set_profile(AccelProfile.sport)
+    assert controller.get_max_accel(0.0) == ACCEL_MAX
+
+  def test_negative_speed_uses_standstill_value(self):
+    controller = self.set_profile(AccelProfile.sport)
+    assert controller.get_max_accel(-1.0) == MAX_ACCEL_PROFILES[AccelProfile.sport][0]
+
+  def test_eco_cruise_decel_is_speed_scheduled_not_gap_scheduled(self):
+    controller = self.set_profile(AccelProfile.eco)
+    a_small = controller.get_cruise_target(22.0, 20.0) - 22.0
+    a_big = controller.get_cruise_target(22.0, 12.0) - 22.0
+    assert np.isclose(a_small, a_big)
+    assert np.isclose(controller.get_cruise_target(19.44, 10.0) - 19.44, -0.22)
+    assert np.isclose(controller.get_cruise_target(15.0, 10.0) - 15.0, -0.40)
+    assert -0.40 < controller.get_cruise_target(18.0, 10.0) - 18.0 < -0.22
+    # with the planner's coast accel available, >= 70 km/h coasts exactly (pitch-aware), 60-70 blends into it
+    assert np.isclose(controller.get_cruise_target(22.0, 10.0, accel_coast=-0.27) - 22.0, -0.27)
+    assert np.isclose(controller.get_cruise_target(15.0, 10.0, accel_coast=-0.27) - 15.0, -0.40)
+    assert -0.40 < controller.get_cruise_target(18.0, 10.0, accel_coast=-0.27) - 18.0 < -0.27
+    # normal ignores the coast value
+    normal = self.set_profile(AccelProfile.normal)
+    assert normal.get_cruise_target(22.0, 20.0, accel_coast=-0.27) == normal.get_cruise_target(22.0, 20.0)
+  def test_normal_and_sport_cruise_decel_latch_then_taper(self):
+    for profile in (AccelProfile.normal, AccelProfile.sport):
+      controller = self.set_profile(profile)
+      v_target = 10.0
+      a1 = controller.get_cruise_target(14.0, v_target) - 14.0
+      a2 = controller.get_cruise_target(13.0, v_target) - 13.0
+      expected = min(CRUISE_DECEL_ACCEL[profile], (v_target - 14.0) / CRUISE_DECEL_RESPONSE_TIME[profile])
+      assert a1 < 0 and np.isclose(a1, a2)
+      assert np.isclose(a1, expected)
+
+      a_close = controller.get_cruise_target(10.2, v_target) - 10.2
+      assert a1 < a_close < 0
+      assert controller.get_cruise_target(10.0, v_target) == v_target
+      # A new, lower target re-latches a firmer deceleration.
+      a_new_target = controller.get_cruise_target(14.0, v_target - 2.0) - 14.0
+      assert a_new_target <= a1
+      assert CRUISE_DECEL_RESPONSE_TIME[profile] >= 3.0
+
+  def test_non_decel_cruise_requests_clear_latched_deceleration(self):
+    controller = self.set_profile(AccelProfile.normal)
+    controller.get_cruise_target(14.0, 10.0)
+    assert controller.get_cruise_target(10.0, 10.0) == 10.0
+    assert np.isclose(controller.get_cruise_target(14.0, 10.0) - 14.0,
+                      (10.0 - 14.0) / CRUISE_DECEL_RESPONSE_TIME[AccelProfile.normal])
+
+  def test_eco_decel_table_is_valid(self):
+    assert len(ECO_CRUISE_DECEL_BP) == len(ECO_CRUISE_DECEL_V)
+    assert all(decel < 0.0 for decel in ECO_CRUISE_DECEL_V)
+
+  def test_params_refresh(self):
+    controller = self.set_profile(AccelProfile.normal)
+    self.params.put("AccelPersonality", AccelProfile.sport, block=True)
+    controller.update()
+    assert controller.profile == AccelProfile.sport
+
+    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
+    controller.update()
+    assert not controller.is_enabled()

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/tests/test_accel_controller_closed_loop.py

@@ -0,0 +1,237 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from collections.abc import Callable
+
+import numpy as np
+
+from openpilot.common.constants import CV
+from openpilot.common.params import Params
+from openpilot.common.realtime import DT_MDL
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.controls.lib.drive_helpers import should_stop
+from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MAX_BP, J_CRUISE_VALS, get_cruise_accel
+from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalPlanSource, T_IDXS as T_IDXS_MPC
+from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
+  AccelController, AccelProfile, ECO_CRUISE_DECEL_BP, ECO_CRUISE_DECEL_V, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES,
+)
+from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PRIUS_TSS2_ROUTE_MODEL, PlantSP
+
+
+class CarParams:
+  steerRatio = 15.0
+  wheelbase = 2.7
+
+
+def _set_mpc_acceleration(plant: PlantSP, acceleration: float = 2.0) -> None:
+  def update(_radar_state, **_kwargs):
+    mpc = plant.planner.mpc
+    mpc.source = LongitudinalPlanSource.lead0
+    mpc.v_solution[:] = mpc.x0[1] + acceleration * T_IDXS_MPC
+    mpc.a_solution.fill(acceleration)
+    mpc.j_solution.fill(0.0)
+
+  plant.planner.mpc.update = update
+
+
+def run_profile(profile: int, *, enabled: bool = True, speed: float = 0.0, v_cruise: float = 30.0,
+                v_cruise_fn: Callable[[int], float] | None = None, e2e: bool = False, steps: int = 120,
+                speed_noise: float = 0.0, seed: int = 0):
+  params = Params()
+  params.put_bool("AccelPersonalityEnabled", enabled, block=True)
+  params.put("AccelPersonality", profile, block=True)
+  controller = AccelController()
+  rng = np.random.default_rng(seed)
+
+  accel = 0.0
+  rows = []
+  for frame in range(steps):
+    target_speed = v_cruise if v_cruise_fn is None else v_cruise_fn(frame)
+    measured = speed + (float(rng.normal(0.0, speed_noise)) if speed_noise else 0.0)
+    accel = get_cruise_accel(e2e, target_speed, measured, accel, 0.0, CarParams(), DT_MDL, 2.0, True)
+    if accel > 0.0:
+      accel = min(accel, controller.get_max_accel(measured))
+    speed = max(0.0, speed + accel * DT_MDL)
+    rows.append((speed, accel, should_stop(speed, accel)))
+  return rows
+
+
+def run_vehicle_profile(profile: int, duration: float = 80.0, enabled: bool = True, speed: float = 0.0,
+                        v_cruise_fn: Callable[[float], float] | None = None):
+  params = Params()
+  params.put_bool("AccelPersonalityEnabled", enabled, block=True)
+  params.put("AccelPersonality", profile, block=True)
+
+  plant = PlantSP(speed=speed, actuator_model=PRIUS_TSS2_ROUTE_MODEL, run_long_control=True)
+  _set_mpc_acceleration(plant)
+  rows = []
+  while plant.current_time < duration:
+    v_cruise = 25.0 if v_cruise_fn is None else v_cruise_fn(plant.current_time)
+    result = plant.step(v_cruise=v_cruise)
+    rows.append((plant.current_time, result["speed"], result["a_target"], result["actuator_command"], result["acceleration"]))
+  return np.asarray(rows)
+
+
+class TestAccelControllerClosedLoop(OpenpilotTestCase):
+  def test_profiles_are_immediate_smooth_and_clearly_distinct(self):
+    traces = {profile: run_vehicle_profile(profile) for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)}
+    stock = run_vehicle_profile(AccelProfile.normal, enabled=False)
+
+    def crossing(trace, speed):
+      return float(trace[np.flatnonzero(trace[:, 1] >= speed)[0], 0])
+
+    time_to_20 = {profile: crossing(trace, 20.0 * CV.MPH_TO_MS) for profile, trace in traces.items()}
+    time_to_50 = {profile: crossing(trace, 50.0 * CV.MPH_TO_MS) for profile, trace in traces.items()}
+    first_motion = {profile: int(np.flatnonzero(trace[:, 1] > 0.01)[0]) for profile, trace in traces.items()}
+
+    self.assertEqual(len(set(first_motion.values())), 1)
+    self.assertTrue(all(trace[0, 2] > 0.0 and trace[1, 3] > 0.0 for trace in traces.values()))
+    self.assertLess(time_to_20[AccelProfile.eco], 10.0)
+    self.assertLess(time_to_50[AccelProfile.eco], 65.0)
+    self.assertGreaterEqual(time_to_20[AccelProfile.eco] - time_to_20[AccelProfile.normal], 0.5)
+    self.assertGreaterEqual(time_to_20[AccelProfile.normal] - time_to_20[AccelProfile.sport], 0.5)
+    self.assertGreaterEqual(time_to_50[AccelProfile.eco] - time_to_50[AccelProfile.normal], 2.0)
+    self.assertGreaterEqual(time_to_50[AccelProfile.normal] - time_to_50[AccelProfile.sport], 3.0)
+
+    stock_peak_jerk = float(np.max(np.abs(np.diff(stock[:, 3])) / DT_MDL))
+    for profile, trace in traces.items():
+      command_jerk = np.abs(np.diff(trace[:, 3])) / DT_MDL
+      self.assertLessEqual(float(np.max(command_jerk)), stock_peak_jerk + 1e-9, profile)
+
+      settled = np.flatnonzero(trace[:, 1] >= 25.0 - 0.15)
+      self.assertGreater(len(settled), 0)
+      settled_trace = trace[settled[0]:]
+      self.assertGreaterEqual(float(np.min(settled_trace[:, 3])), -0.05)
+      self.assertLessEqual(float(np.max(trace[:, 1])), 25.0 + 1e-9)
+
+  def test_blended_positive_model_request_uses_profile_cruise_cap(self):
+    params = Params()
+    params.put_bool("DynamicExperimentalControl", False, block=True)
+    params.put_bool("AccelPersonalityEnabled", True, block=True)
+    params.put("AccelPersonality", AccelProfile.eco, block=True)
+
+    def request_acceleration(_current_time: float, _speed: float, _acceleration: float) -> tuple[float, bool]:
+      return 2.0, False
+
+    plant = PlantSP(speed=15.0, e2e=True, model_action_fn=request_acceleration)
+    _set_mpc_acceleration(plant)
+    results = [plant.step(v_cruise=35.0) for _ in range(20)]
+    settled = results[-1]
+    eco_limit = 0.85 * float(np.interp(settled["published_v_ego"], MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
+
+    self.assertTrue(settled["controller_active"])
+    self.assertEqual(settled["mpc_source"], LongitudinalPlanSource.cruise)
+    self.assertAlmostEqual(settled["a_target"], eco_limit, delta=0.01)
+    self.assertLess(settled["a_target"], settled["model_action"]["desiredAcceleration"])
+
+  def test_normal_launch_is_faster_than_eco(self):
+    eco = run_profile(AccelProfile.eco, speed=4.0, steps=120)
+    normal = run_profile(AccelProfile.normal, speed=4.0, steps=120)
+    self.assertGreater(normal[-1][0], eco[-1][0])
+
+  def test_zero_speed_stop_request_is_unchanged(self):
+    for e2e in (False, True):
+      stock = run_profile(AccelProfile.normal, enabled=False, speed=20.0, v_cruise=0.0, e2e=e2e, steps=100)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
+        self.assertEqual(run_profile(profile, speed=20.0, v_cruise=0.0, e2e=e2e, steps=100), stock)
+
+  def test_eco_cruise_decel_uses_gentle_speed_schedule(self):
+    params = Params()
+    params.put_bool("AccelPersonalityEnabled", True, block=True)
+    params.put("AccelPersonality", AccelProfile.eco, block=True)
+    controller = AccelController()
+
+    speeds = (15.0, 18.0, 19.44, 25.0, 33.3)
+    decels = [controller.get_cruise_target(speed, speed - 10.0) - speed for speed in speeds]
+    expected = np.interp(speeds, ECO_CRUISE_DECEL_BP, ECO_CRUISE_DECEL_V)
+    np.testing.assert_allclose(decels, expected)
+    self.assertTrue(all(decel > -0.5 for decel in decels))
+
+  def test_normal_cruise_decel_remains_gradual(self):
+    params = Params()
+    params.put_bool("AccelPersonalityEnabled", True, block=True)
+    params.put("AccelPersonality", AccelProfile.normal, block=True)
+    controller = AccelController()
+    target = 25.0 - 5.0 * CV.MPH_TO_MS
+    stock = get_cruise_accel(False, target, 25.0, 0.0, 0.0, CarParams(), DT_MDL, 2.0, True)
+    shaped = controller.get_cruise_target(25.0, target)
+    self.assertLess(shaped, 25.0)
+    self.assertGreater(shaped, target)
+    self.assertLess(shaped - 25.0, 0.0)
+    self.assertLess(shaped - 25.0, -0.3)
+    self.assertGreater(abs(stock), 0.0)
+
+  def test_blended_launch_respects_profiles(self):
+    traces = {
+      profile: run_profile(profile, v_cruise=8.0, e2e=True, steps=180)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
+    }
+    time_to_five = {
+      profile: next(frame for frame, row in enumerate(rows) if row[0] >= 5.0) * DT_MDL
+      for profile, rows in traces.items()
+    }
+
+    self.assertLess(time_to_five[AccelProfile.sport], time_to_five[AccelProfile.normal])
+    self.assertLess(time_to_five[AccelProfile.normal], time_to_five[AccelProfile.eco])
+
+  def test_launch_ordering_without_departure_delay(self):
+    stock = run_profile(AccelProfile.normal, enabled=False, v_cruise=8.0, steps=160)
+    traces = {
+      profile: run_profile(profile, v_cruise=8.0, steps=160)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
+    }
+    first_motion = {
+      profile: next(frame for frame, row in enumerate(rows) if row[0] > 0.01)
+      for profile, rows in traces.items()
+    }
+    time_to_five = {
+      profile: next(frame for frame, row in enumerate(rows) if row[0] >= 5.0) * DT_MDL
+      for profile, rows in traces.items()
+    }
+    stock_first_motion = next(frame for frame, row in enumerate(stock) if row[0] > 0.01)
+
+    self.assertEqual(len(set(first_motion.values())), 1)
+    self.assertTrue(all(frame == stock_first_motion for frame in first_motion.values()))
+    self.assertGreaterEqual(time_to_five[AccelProfile.eco] - time_to_five[AccelProfile.normal], 0.1)
+    self.assertGreaterEqual(time_to_five[AccelProfile.normal], time_to_five[AccelProfile.sport])
+
+  def test_road_speed_catchup_stays_useful(self):
+    traces = {
+      profile: run_profile(profile, speed=20.0, v_cruise=30.0, steps=100)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
+    }
+    gains = {profile: rows[-1][0] - 20.0 for profile, rows in traces.items()}
+    self.assertGreater(gains[AccelProfile.normal] - gains[AccelProfile.eco], 0.05)
+    self.assertGreater(gains[AccelProfile.sport] - gains[AccelProfile.normal], 0.1)
+
+  def test_full_catchup_trace_respects_stock_jerk(self):
+    for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
+      rows = run_profile(profile, v_cruise=30.0, steps=300)
+      previous_speed = 0.0
+      previous_accel = 0.0
+      for speed, accel, _should_stop in rows:
+        jerk_step = float(np.interp(previous_speed, A_CRUISE_MAX_BP, J_CRUISE_VALS)) * DT_MDL
+        self.assertLessEqual(abs(accel - previous_accel), jerk_step + 1e-12)
+        previous_speed = speed
+        previous_accel = accel
+
+  def test_stop_release_frame_is_profile_independent(self):
+    def target_speed(frame: int) -> float:
+      return 0.0 if frame < 20 else 8.0
+
+    traces = {
+      profile: run_profile(profile, v_cruise_fn=target_speed, steps=80)
+      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
+    }
+    release_frames = {
+      profile: next(frame for frame, row in enumerate(rows) if frame >= 20 and not row[2])
+      for profile, rows in traces.items()
+    }
+    stock = run_profile(AccelProfile.normal, enabled=False, v_cruise_fn=target_speed, steps=80)
+    stock_release_frame = next(frame for frame, row in enumerate(stock) if frame >= 20 and not row[2])
+    self.assertEqual(len(set(release_frames.values())), 1)
+    self.assertTrue(all(frame == stock_release_frame for frame in release_frames.values()))

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/tests/test_eco_lead_boost.py

@@ -0,0 +1,129 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import numpy as np
+
+from openpilot.common.params import Params
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
+  AccelController, AccelProfile, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES,
+)
+
+
+class TestEcoLeadBoost(OpenpilotTestCase):
+  """Eco lead pull-away boost (driver 2026-10-01 night)."""
+
+  @staticmethod
+  def _ac(profile):
+    from types import SimpleNamespace
+    ac = AccelController.__new__(AccelController)
+    ac._profile, ac._enabled, ac._boost = profile, True, 0.0
+    ac._cruise_decel = ac._cruise_decel_target = None
+    return ac, SimpleNamespace
+
+  def test_no_lead_unchanged(self):
+    ac, _ = self._ac(AccelProfile.eco)
+    v = 15.0
+    base = float(np.interp(v, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
+    for _ in range(100):
+      assert ac.get_max_accel(v, False, None) == base
+
+  def test_pulling_away_lead_boosts_smoothly_within_normal(self):
+    ac, NS = self._ac(AccelProfile.eco)
+    v = 15.0
+    lead = NS(present=True, modelProb=0.9, dRel=30.0, vLead=v + 3.0)
+    base = float(np.interp(v, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
+    normal = float(np.interp(v, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.normal]))
+    out = [ac.get_max_accel(v, False, lead) for _ in range(60)]
+    steps = np.diff([base] + out)
+    assert max(steps) <= 0.25 * 0.05 + 1e-9          # eased in
+    assert out[-1] > base + 0.2 and out[-1] <= normal + 1e-9
+    lead.present = False
+    out2 = [ac.get_max_accel(v, False, lead) for _ in range(60)]
+    assert min(np.diff([out[-1]] + out2)) >= -0.5 * 0.05 - 1e-9   # eased out
+    assert abs(out2[-1] - base) < 1e-9
+
+  def test_no_boost_at_80_kph_or_for_a_closing_lead(self):
+    ac, NS = self._ac(AccelProfile.eco)
+    v = 80 / 3.6
+    lead = NS(present=True, modelProb=0.9, dRel=30.0, vLead=v + 3.0)
+    base = float(np.interp(v, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
+    assert abs([ac.get_max_accel(v, False, lead) for _ in range(40)][-1] - base) < 1e-9
+    ac, NS = self._ac(AccelProfile.eco)
+    v = 15.0
+    lead = NS(present=True, modelProb=0.9, dRel=30.0, vLead=v - 1.0)
+    base = float(np.interp(v, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
+    assert abs([ac.get_max_accel(v, False, lead) for _ in range(40)][-1] - base) < 1e-9
+
+
+class _Lead:
+  def __init__(self, present=True, modelProb=0.9, dRel=30.0, vLead=18.0):
+    self.present, self.modelProb, self.dRel, self.vLead = present, modelProb, dRel, vLead
+
+
+class _Radar:
+  def __init__(self, lead):
+    self.leadOne = lead
+
+
+class _Sink:
+  def clear(self):
+    pass
+
+  def update(self, *args, **kwargs):
+    pass
+
+
+class TestPlannerLeadWiring(OpenpilotTestCase):
+  """The boost needs a lead, so the planner has to carry radarState.leadOne into get_max_accel_override."""
+
+  def setUp(self):
+    self.params = Params()
+    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
+    self.params.put("AccelPersonality", AccelProfile.eco, block=True)
+
+  @staticmethod
+  def _planner():
+    from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP
+
+    planner = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
+    planner.accel_controller = AccelController()
+    planner.accel_controller_active = False
+    planner.lead_one = None
+    return planner
+
+  @staticmethod
+  def _settle(planner, v_ego, lead=None, n=60):
+    return [planner.get_max_accel_override(v_ego, lead=lead) for _ in range(n)][-1]
+
+  def test_update_stores_the_radar_lead(self):
+    planner = self._planner()
+    planner.events_sp = _Sink()
+    planner.e2e_alerts_helper = _Sink()
+    lead = _Lead()
+    planner.update({"radarState": _Radar(lead)})
+    assert planner.lead_one is lead
+
+  def test_stored_lead_feeds_the_boost_and_an_explicit_lead_wins(self):
+    v = 15.0
+    lead = _Lead(vLead=v + 3.0)
+    planner = self._planner()
+    planner.lead_one = lead
+    boosted = self._settle(planner, v)
+
+    planner.accel_controller._boost = 0.0
+    planner.lead_one = _Lead(present=False)
+    base = self._settle(planner, v)
+    assert boosted > base + 0.2
+
+    planner.accel_controller._boost = 0.0
+    explicit = self._settle(planner, v, lead=lead)
+    assert abs(explicit - boosted) < 1e-9
+
+  def test_disabled_accel_controller_returns_no_override(self):
+    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
+    assert self._planner().get_max_accel_override(15.0, lead=_Lead()) is None

openpilot/sunnypilot/selfdrive/controls/lib/auto_lane_change.py

@@ -10,6 +10,8 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 
 
+
+
 class AutoLaneChangeMode:
   OFF = -1
   NUDGE = 0  # default
@@ -31,6 +33,7 @@ AUTO_LANE_CHANGE_TIMER = {
 }
 
 ONE_SECOND_DELAY = -1
+EDGE_DELAY = -2
 
 
 class AutoLaneChangeController:
@@ -48,6 +51,7 @@ class AutoLaneChangeController:
     self.prev_brake_pressed = False
     self.auto_lane_change_allowed = False
     self.prev_lane_change = False
+    self.lane_change_blocked = False
 
     self.read_params()
 
@@ -68,7 +72,7 @@ class AutoLaneChangeController:
       self.read_params()
     self.param_read_counter += 1
 
-  def update_lane_change_timers(self, blindspot_detected: bool) -> None:
+  def update_lane_change_timers(self, blindspot_detected: bool, edge_detected: bool) -> None:
     self.lane_change_delay = AUTO_LANE_CHANGE_TIMER.get(self.lane_change_set_timer,
                                                         AUTO_LANE_CHANGE_TIMER[AutoLaneChangeMode.NUDGE])
 
@@ -80,6 +84,12 @@ class AutoLaneChangeController:
       else:
         self.lane_change_wait_timer = self.lane_change_delay + ONE_SECOND_DELAY
 
+    if edge_detected and self.lane_change_delay > 0:
+      if self.lane_change_delay == AUTO_LANE_CHANGE_TIMER[AutoLaneChangeMode.NUDGELESS]:
+        self.lane_change_wait_timer = min(self.lane_change_wait_timer, EDGE_DELAY)
+      else:
+        self.lane_change_wait_timer = min(self.lane_change_wait_timer, self.lane_change_delay + EDGE_DELAY)
+
   def update_allowed(self) -> bool:
     # Auto lane change allowed if:
     # 1. A valid delay is set (non-zero)
@@ -97,14 +107,23 @@ class AutoLaneChangeController:
 
     return bool(self.lane_change_wait_timer > self.lane_change_delay)
 
-  def update_lane_change(self, blindspot_detected: bool, brake_pressed: bool) -> None:
+  def update_lane_change(self, blindspot_detected: bool, edge_detected: bool, brake_pressed: bool,
+                         torque_applied: bool = False) -> None:
     if brake_pressed and not self.prev_brake_pressed:
       self.prev_brake_pressed = brake_pressed
 
-    self.update_lane_change_timers(blindspot_detected)
+    self.update_lane_change_timers(blindspot_detected, edge_detected)
 
     self.auto_lane_change_allowed = self.update_allowed()
 
+    # BSM always blocks. Edge blocks auto mode but nudge can override.
+    if blindspot_detected:
+      self.lane_change_blocked = True
+    elif edge_detected:
+      self.lane_change_blocked = not torque_applied
+    else:
+      self.lane_change_blocked = False
+
   def update_state(self):
     if self.DH.lane_change_state == log.LaneChangeState.laneChangeStarting:
       self.prev_lane_change = True

openpilot/sunnypilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -5,10 +5,13 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 
-from openpilot.cereal import messaging, custom
+import math
+
+from openpilot.cereal import messaging, custom, log
 from opendbc.car import structs
 from openpilot.common.constants import CV
 from openpilot.selfdrive.car.cruise import V_CRUISE_MAX
+from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelController
 from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
 from openpilot.sunnypilot.selfdrive.controls.lib.e2e_alerts_helper import E2EAlertsHelper
 from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.smart_cruise_control import SmartCruiseControl
@@ -19,12 +22,17 @@ from openpilot.sunnypilot.models.helpers import get_active_bundle
 
 DecState = custom.LongitudinalPlanSP.DynamicExperimentalControl.DynamicExperimentalControlState
 LongitudinalPlanSource = custom.LongitudinalPlanSP.LongitudinalPlanSource
+MpcPlanSource = log.LongitudinalPlan.LongitudinalPlanSource
+
+E2E_BRAKE_HOLD_ACCEL = -0.2  # m/s^2
 
 
 class LongitudinalPlannerSP:
   def __init__(self, CP: structs.CarParams, CP_SP: structs.CarParamsSP, mpc):
+    self.accel_controller = AccelController()
+    self.accel_controller_active = False
+    self.lead_one = None
     self.events_sp = EventsSP()
-    self.resolver = SpeedLimitResolver()
     self.dec = DynamicExperimentalController(CP, mpc)
     self.scc = SmartCruiseControl()
     self.resolver = SpeedLimitResolver()
@@ -38,10 +46,48 @@ class LongitudinalPlannerSP:
 
   def is_e2e(self, sm: messaging.SubMaster) -> bool:
     experimental_mode = sm['selfdriveState'].experimentalMode
-    if not self.dec.active():
-      return experimental_mode
+    if not experimental_mode:
+      return False
 
-    return experimental_mode and self.dec.mode() == "blended"
+    if not self.dec.active() or self.dec.mode() == "blended":
+      return True
+
+    if self.mpc.source == MpcPlanSource.e2e and sm['modelV2'].action.desiredAcceleration < E2E_BRAKE_HOLD_ACCEL:
+      return True
+
+    return False
+
+  def get_max_accel_override(self, v_ego: float, engine_off: bool = False, lead=None) -> float | None:
+    if not self.accel_controller.is_enabled():
+      return None
+
+    return self.accel_controller.get_max_accel(v_ego, engine_off, lead if lead is not None else self.lead_one)
+
+  def get_cruise_target_override(self, v_ego: float, v_target: float, force_decel: bool, accel_coast: float | None = None) -> float:
+    if not self.accel_controller.is_enabled() or force_decel or self.source != LongitudinalPlanSource.cruise:
+      return v_target
+
+    return self.accel_controller.get_cruise_target(v_ego, v_target, accel_coast)
+
+  def is_accel_controller_active(self, force_decel: bool) -> bool:
+    return bool(self.accel_controller.is_enabled() and not force_decel and
+                self.mpc.source == MpcPlanSource.cruise)
+
+  def _has_valid_selected_lead(self, sm: messaging.SubMaster, source: MpcPlanSource) -> bool:
+    radar_valid = sm.valid.get('radarState', False) and getattr(sm, 'alive', {}).get('radarState', False)
+    return radar_valid and ((source == MpcPlanSource.lead0 and sm['radarState'].leadOne.present) or
+                            (source == MpcPlanSource.lead1 and sm['radarState'].leadTwo.present))
+
+  def arbitrate_cruise_candidate(self, sm: messaging.SubMaster, gated: float, ungated: float,
+                                 mpc_accel: float, mpc_source: MpcPlanSource, *, allow_throttle: bool,
+                                 e2e: bool, force_decel: bool) -> float:
+    finite = all(math.isfinite(value) for value in (gated, ungated, mpc_accel))
+    coast_gate_changed_source = gated < mpc_accel <= ungated
+    if (finite and not allow_throttle and not e2e and not force_decel
+        and self._has_valid_selected_lead(sm, mpc_source) and coast_gate_changed_source):
+      return ungated
+
+    return gated
 
   def update_targets(self, sm: messaging.SubMaster, v_ego: float, a_ego: float, v_cruise: float) -> tuple[float, float]:
     CS = sm['carState']
@@ -74,10 +120,14 @@ class LongitudinalPlannerSP:
     return self.output_v_target, self.output_a_target
 
   def update(self, sm: messaging.SubMaster) -> None:
+    self.accel_controller.update()
+    self.lead_one = sm['radarState'].leadOne
     self.events_sp.clear()
-    self.dec.update(sm)
     self.e2e_alerts_helper.update(sm, self.events_sp)
 
+  def update_dec(self, sm: messaging.SubMaster) -> None:
+    self.dec.update(sm)
+
   def publish_longitudinal_plan_sp(self, sm: messaging.SubMaster, pm: messaging.PubMaster) -> None:
     plan_sp_send = messaging.new_message('longitudinalPlanSP')
 
@@ -94,6 +144,15 @@ class LongitudinalPlannerSP:
     dec.state = DecState.blended if self.dec.mode() == 'blended' else DecState.acc
     dec.enabled = self.dec.enabled()
     dec.active = self.dec.active()
+    #dec.decelIntent = float(self.dec.signals.decel_intent)
+    #dec.curveDetected = bool(self.dec.signals.curve_detected)
+    #dec.wantBlended = bool(self.dec.want_blended)
+    #dec.leadVeto = bool(self.dec.lead_veto)
+
+    accel_controller = longitudinalPlanSP.accelController
+    accel_controller.enabled = bool(self.accel_controller.is_enabled())
+    accel_controller.active = bool(self.accel_controller_active)
+    accel_controller.profile = int(self.accel_controller.profile)
 
     # Smart Cruise Control
     smartCruiseControl = longitudinalPlanSP.smartCruiseControl

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/tests/test_vision_controller.py

@@ -4,6 +4,8 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
+
+from types import SimpleNamespace
 from typing import Any
 
 import numpy as np
@@ -15,8 +17,23 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
 from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP, LongitudinalPlanSource
 from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control import MIN_V
-from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import SmartCruiseControlVision, _ENTERING_PRED_LAT_ACC_TH
+
+from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import (
+  _A_LAT_REG_MAX,
+  _BELOW_EGO_TARGET_RELEASE_RATE,
+  _ENTERING_PRED_LAT_ACC_TH,
+  _MIN_ACTIVATION_SPEED,
+  _RELIEF_CONFIRMATION_FRAMES,
+  _TARGET_RELEASE_CONFIRMATION_FRAMES,
+  _TARGET_RELEASE_RATE,
+  _TARGET_TIGHTEN_CONFIRMATION_FRAMES,
+  _TARGET_TIGHTEN_RATE,
+  _TURNING_LAT_ACC_TH,
+  _URGENT_PRED_LAT_ACC_TH,
+  SmartCruiseControlVision,
+)
 from openpilot.common.test import OpenpilotTestCase
 
 VisionState = custom.LongitudinalPlanSP.SmartCruiseControl.VisionState
@@ -107,7 +124,6 @@ def generate_controlsState():
 
 
 class TestSmartCruiseControlVision(OpenpilotTestCase):
-
   def setup_method(self):
     self.params = Params()
     self.reset_params()
@@ -121,36 +137,377 @@ class TestSmartCruiseControlVision(OpenpilotTestCase):
   def reset_params(self):
     self.params.put_bool("SmartCruiseControlVision", True, block=True)
 
+  def assert_approx(self, actual, expected):
+    self.assertAlmostEqual(actual, expected, delta=max(1e-12, abs(expected) * 1e-6))
+
+  def set_lat_accels(self, current: float, predicted: float, v_ego: float = 20.0, model_speed: float = 20.0) -> None:
+    self.sm['controlsState'].curvature = current / v_ego**2
+    self.sm['modelV2'].velocity.x = [model_speed] * len(ModelConstants.T_IDXS)
+    self.sm['modelV2'].orientationRate.z = [predicted / model_speed] * len(ModelConstants.T_IDXS)
+
+  def update_lat_accels(
+    self, current: float, predicted: float, cruise: float = 30.0, a_ego: float = 0.0, v_ego: float = 20.0, model_speed: float = 20.0
+  ) -> None:
+    self.set_lat_accels(current, predicted, v_ego, model_speed)
+    self.scc_v.update(self.sm, True, False, v_ego, a_ego, cruise)
+
+  def enter_curve(self, predicted: float = 2.2) -> None:
+    self.update_lat_accels(0.5, predicted)
+    self.update_lat_accels(0.5, predicted)
+    assert self.scc_v.state == VisionState.entering
+
   def test_initial_state(self):
     assert self.scc_v.state == VisionState.disabled
     assert not self.scc_v.is_active
     assert self.scc_v.output_v_target == V_CRUISE_UNSET
-    assert self.scc_v.output_a_target == 0.
+    assert self.scc_v.output_a_target == 0.0
 
   def test_system_disabled(self):
     self.params.put_bool("SmartCruiseControlVision", False, block=True)
     self.scc_v.enabled = self.params.get_bool("SmartCruiseControlVision")
 
-    for _ in range(int(10. / DT_MDL)):
-      self.scc_v.update(self.sm, True, False, 0., 0., 0.)
+    for _ in range(int(10.0 / DT_MDL)):
+      self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
     assert self.scc_v.state == VisionState.disabled
     assert not self.scc_v.is_active
 
   def test_disabled(self):
-    for _ in range(int(10. / DT_MDL)):
-      self.scc_v.update(self.sm, False, False, 0., 0., 0.)
+    for _ in range(int(10.0 / DT_MDL)):
+      self.scc_v.update(self.sm, False, False, 0.0, 0.0, 0.0)
     assert self.scc_v.state == VisionState.disabled
 
   def test_transition_disabled_to_enabled(self):
-    for _ in range(int(10. / DT_MDL)):
-      self.scc_v.update(self.sm, True, False, 0., 0., 0.)
+    for _ in range(int(10.0 / DT_MDL)):
+      self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
     assert self.scc_v.state == VisionState.enabled
 
-  @parameterized.expand([
+  def test_unconfirmed_release_holds_but_urgent_reentry_tightens(self):
+    self.enter_curve()
+    targets = [self.scc_v.output_v_target]
+
+    self.update_lat_accels(2.0, 2.2, a_ego=-0.8)
+    assert self.scc_v.state == VisionState.turning
+    assert self.scc_v.output_a_target == -0.8
+    turning_demand = self.scc_v._v_demand()
+    targets.append(self.scc_v.output_v_target)
+
+    self.update_lat_accels(1.2, 1.2, a_ego=0.3)
+    assert self.scc_v.state == VisionState.leaving
+    assert self.scc_v.output_a_target == 0.3
+    targets.append(self.scc_v.output_v_target)
+
+    self.update_lat_accels(1.0, 3.0, a_ego=-1.2)
+    assert self.scc_v.state == VisionState.entering
+    assert self.scc_v.output_a_target == -1.2
+    reentry_demand = self.scc_v._v_demand()
+    targets.append(self.scc_v.output_v_target)
+
+    entering, turning, leaving, reentering = targets
+    assert turning < entering
+    self.assert_approx(turning, turning_demand)
+    self.assert_approx(leaving, turning)
+    assert reentering < leaving
+    self.assert_approx(reentering, reentry_demand)
+
+  def test_new_curve_interrupts_confirmed_release_immediately(self):
+    self.enter_curve()
+    for _ in range(_RELIEF_CONFIRMATION_FRAMES + 1):
+      self.update_lat_accels(0.8, 0.8)
+    releasing_v_target = self.scc_v.output_v_target
+    assert self.scc_v.state == VisionState.leaving
+
+    self.update_lat_accels(0.8, 3.0, a_ego=-0.7)
+    assert self.scc_v.state == VisionState.entering
+    assert self.scc_v.output_v_target < releasing_v_target
+    assert self.scc_v.output_a_target == -0.7
+
+  @parameterized.expand([(-2.0,), (-0.5,), (0.0,), (0.8,)])
+  def test_planner_acceleration_passes_through_exactly(self, planner_accel):
+    self.enter_curve()
+    self.update_lat_accels(0.5, 2.2, a_ego=planner_accel)
+    assert self.scc_v.output_a_target == planner_accel
+
+  def test_planner_acceleration_passes_through_all_states(self):
+    cases = (
+      (False, False, 0.5, 2.2, -0.2, VisionState.disabled),
+      (True, False, 0.5, 0.8, 0.1, VisionState.enabled),
+      (True, False, 0.5, 2.2, -0.4, VisionState.entering),
+      (True, False, 2.0, 2.2, -0.8, VisionState.turning),
+      (True, False, 1.2, 1.2, 0.3, VisionState.leaving),
+      (True, True, 1.2, 1.2, 0.6, VisionState.overriding),
+    )
+    for long_enabled, override, current, predicted, planner_accel, state in cases:
+      self.set_lat_accels(current, predicted)
+      self.scc_v.update(self.sm, long_enabled, override, 20.0, planner_accel, 30.0)
+      assert self.scc_v.state == state
+      assert self.scc_v.output_a_target == planner_accel
+
+  def test_jitter_requires_confirmed_relief_then_releases_smoothly(self):
+    self.enter_curve()
+    previous_v_target = self.scc_v.output_v_target
+
+    for frame in range(_RELIEF_CONFIRMATION_FRAMES * 2):
+      self.update_lat_accels(1.0, 1.05 if frame % 2 == 0 else 1.15)
+      assert self.scc_v.state == VisionState.entering
+      assert self.scc_v.output_v_target >= previous_v_target
+      assert self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
+      previous_v_target = self.scc_v.output_v_target
+
+    for _ in range(_RELIEF_CONFIRMATION_FRAMES):
+      self.update_lat_accels(1.15, 0.8)
+      assert self.scc_v.state == VisionState.entering
+      assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
+      previous_v_target = self.scc_v.output_v_target
+
+    release_cruise = 30.0
+    for _ in range(_RELIEF_CONFIRMATION_FRAMES - 1):
+      self.update_lat_accels(0.8, 0.8, release_cruise)
+      assert self.scc_v.state == VisionState.entering
+      assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
+      previous_v_target = self.scc_v.output_v_target
+
+    active_v_targets = [previous_v_target]
+    for _ in range(int((release_cruise - previous_v_target) / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
+      self.update_lat_accels(0.8, 0.8, release_cruise)
+      if not self.scc_v.is_active:
+        break
+      assert self.scc_v.state == VisionState.leaving
+      assert self.scc_v.output_v_target != V_CRUISE_UNSET
+      active_v_targets.append(self.scc_v.output_v_target)
+
+    assert self.scc_v.state == VisionState.enabled
+    assert self.scc_v.output_v_target == V_CRUISE_UNSET
+    self.assert_approx(active_v_targets[-1], release_cruise)
+    assert np.all((np.diff(active_v_targets) >= 0.0) & (np.diff(active_v_targets) <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9))
+
+  def test_target_release_waits_for_relief_above_ego_speed(self):
+    self.enter_curve()
+    held_v_target = self.scc_v.output_v_target
+    self.assert_approx(held_v_target, self.scc_v.v_ego)
+
+    for _ in range(_RELIEF_CONFIRMATION_FRAMES + _TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
+      self.update_lat_accels(0.8, 0.8)
+      self.assert_approx(self.scc_v.output_v_target, held_v_target)
+
+    self.update_lat_accels(0.8, 0.8)
+    rise = self.scc_v.output_v_target - held_v_target
+    assert 0.0 < rise <= _TARGET_RELEASE_RATE * DT_MDL + 1e-9
+
+  def test_curve_target_is_independent_of_ego_speed(self):
+    model_speed = 24.0
+    predicted_yaw_rate = 0.12
+    predicted_lat_accel = model_speed * predicted_yaw_rate
+    expected_v_target = (_A_LAT_REG_MAX / (predicted_yaw_rate / model_speed)) ** 0.5
+    targets = []
+
+    for v_ego in (18.0, 28.0):
+      controller = SmartCruiseControlVision()
+      self.set_lat_accels(0.5, predicted_lat_accel, v_ego, model_speed)
+      controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
+      controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
+      assert controller.state == VisionState.entering
+      targets.append(controller.v_target)
+
+    self.assert_approx(targets[0], expected_v_target)
+    self.assert_approx(targets[1], expected_v_target)
+
+  def test_curve_target_respects_minimum_speed_floor(self):
+    model_speed = 10.0
+    predicted_yaw_rate = 2.0
+    self.set_lat_accels(0.5, model_speed * predicted_yaw_rate, model_speed=model_speed)
+    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
+    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
+
+    assert self.scc_v.state == VisionState.entering
+    assert self.scc_v.v_target < MIN_V
+    self.assert_approx(self.scc_v.output_v_target, MIN_V)
+
+  @parameterized.expand(
+    [([], []), ([np.nan] * len(ModelConstants.T_IDXS), [np.nan] * len(ModelConstants.T_IDXS)), ([20.0] * 5, [0.1] * 3)],
+    names=["velocities", "yaw_rates"],
+  )
+  def test_model_vector_edges_remain_finite(self, velocities, yaw_rates):
+    self.sm['modelV2'].velocity.x = velocities
+    self.sm['modelV2'].orientationRate.z = yaw_rates
+    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
+    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
+
+    assert all(
+      np.isfinite(value)
+      for value in (
+        self.scc_v.current_lat_acc,
+        self.scc_v.max_pred_lat_acc,
+        self.scc_v.v_target,
+        self.scc_v.output_v_target,
+        self.scc_v.output_a_target,
+      )
+    )
+
+  @parameterized.expand([(5.75,), (9.9,), (_MIN_ACTIVATION_SPEED,)])
+  def test_vision_control_does_not_steal_launch(self, launch_speed):
+    self.set_lat_accels(0.5, 3.0, launch_speed)
+    self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
+    self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
+
+    assert launch_speed <= _MIN_ACTIVATION_SPEED
+    assert self.scc_v.state == VisionState.enabled
+    assert not self.scc_v.is_active
+    assert self.scc_v.output_v_target == V_CRUISE_UNSET
+
+  def test_vision_control_can_activate_above_launch_range(self):
+    speed = _MIN_ACTIVATION_SPEED + 0.01
+    self.set_lat_accels(0.5, 3.0, speed)
+    self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
+    self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
+
+    assert self.scc_v.state == VisionState.entering
+    assert self.scc_v.is_active
+
+  def test_nonurgent_activation_has_no_target_cliff(self):
+    v_ego = _MIN_ACTIVATION_SPEED + 0.01
+    model_speed = 8.0
+    self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
+    self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
+
+    self.assert_approx(self.scc_v.v_target, 8.0)
+    self.assert_approx(self.scc_v.output_v_target, v_ego)
+
+  def test_nonurgent_tightening_is_confirmed_and_rate_limited(self):
+    self.enter_curve()
+    initial_v_target = self.scc_v.output_v_target
+
+    for _ in range(_TARGET_TIGHTEN_CONFIRMATION_FRAMES - 1):
+      self.update_lat_accels(0.5, 2.8)
+      self.assert_approx(self.scc_v.output_v_target, initial_v_target)
+
+    self.update_lat_accels(0.5, 2.8)
+    drop = initial_v_target - self.scc_v.output_v_target
+    assert 0.0 < drop <= _TARGET_TIGHTEN_RATE * DT_MDL + 1e-9
+
+  def test_one_frame_curve_prediction_does_not_pulse_target(self):
+    self.enter_curve()
+    for _ in range(10):
+      self.update_lat_accels(0.5, 2.2)
+    stable_v_target = self.scc_v.output_v_target
+
+    self.update_lat_accels(0.5, 2.8)
+    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
+    self.update_lat_accels(0.5, 2.2)
+
+    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
+
+  def test_one_frame_release_does_not_reverse_target(self):
+    self.enter_curve(_URGENT_PRED_LAT_ACC_TH)
+    stable_v_target = self.scc_v.output_v_target
+
+    self.update_lat_accels(0.5, 2.2)
+    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
+    self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
+
+    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
+
+  def test_urgent_predicted_curve_is_not_delayed(self):
+    self.enter_curve()
+    self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
+
+    self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
+
+  def test_current_curve_is_not_delayed(self):
+    self.enter_curve()
+    self.update_lat_accels(_TURNING_LAT_ACC_TH, 2.8)
+
+    self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
+
+  def test_sequential_curve_confirms_release_and_tightens_urgently(self):
+    self.enter_curve(3.0)
+    for _ in range(20):
+      self.update_lat_accels(0.5, 3.0)
+    restrictive_v_target = self.scc_v.output_v_target
+
+    self.update_lat_accels(0.5, 1.4, a_ego=0.4)
+    assert self.scc_v.state == VisionState.entering
+    self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
+    assert self.scc_v.output_a_target == 0.4
+
+    for _ in range(_TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
+      self.update_lat_accels(0.5, 1.4)
+      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
+
+    self.update_lat_accels(0.5, 1.4)
+    released_v_target = self.scc_v.output_v_target
+    assert 0.0 < released_v_target - restrictive_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
+
+    self.update_lat_accels(0.5, 3.0, a_ego=-0.6)
+    assert self.scc_v.state == VisionState.entering
+    self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
+    assert self.scc_v.output_a_target == -0.6
+
+    for _ in range(4):
+      self.update_lat_accels(0.5, 1.4)
+      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
+      self.update_lat_accels(0.5, 3.0)
+      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
+
+  def test_acceleration_is_continuous_through_planner_arbitration(self):
+    car_control = messaging.new_message('carControl')
+    car_control.carControl.enabled = True
+    car_control.carControl.cruiseControl.override = False
+    self.sm['carControl'] = car_control.carControl
+    self.sm['carState'].vCruiseCluster = 108.0
+
+    planner: Any = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
+    planner.scc = SimpleNamespace(
+      vision=self.scc_v,
+      map=SimpleNamespace(output_v_target=V_CRUISE_UNSET, output_a_target=0.0),
+      update=lambda sm, enabled, override, v_ego, a_ego, v_cruise: self.scc_v.update(sm, enabled, override, v_ego, a_ego, v_cruise),
+    )
+    planner.resolver = SimpleNamespace(
+      speed_limit_valid=False,
+      speed_limit_last_valid=False,
+      speed_limit=0.0,
+      speed_limit_final_last=0.0,
+      distance=0.0,
+      update=lambda _v_ego, _sm: None,
+    )
+    planner.sla = SimpleNamespace(
+      output_v_target=V_CRUISE_UNSET,
+      output_a_target=0.0,
+      update=lambda *_args: None,
+    )
+    planner.events_sp = SimpleNamespace()
+
+    self.set_lat_accels(0.5, 2.2)
+    planner.update_targets(self.sm, 20.0, -0.8, 30.0)
+    planner.update_targets(self.sm, 20.0, -0.8, 30.0)
+    assert planner.source == LongitudinalPlanSource.sccVision
+    assert planner.output_a_target == -0.8
+
+    for planner_accel in (-2.0, 0.5, -0.2):
+      planner.update_targets(self.sm, 20.0, planner_accel, 30.0)
+      assert planner.source == LongitudinalPlanSource.sccVision
+      assert planner.output_a_target == planner_accel
+
+    self.set_lat_accels(0.8, 0.8)
+    for _ in range(int(30.0 / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
+      planner.update_targets(self.sm, 20.0, 0.4, 30.0)
+      assert planner.output_a_target == 0.4
+      if planner.source == LongitudinalPlanSource.cruise:
+        break
+    else:
+      self.fail("SCC Vision did not release to cruise")
+
+    planner.update_targets(self.sm, 20.0, 0.4, 30.0)
+    assert self.scc_v.state == VisionState.enabled
+    assert planner.source == LongitudinalPlanSource.cruise
+
+  @parameterized.expand(
+    [
       ("p97_just_above_threshold", True),
       ("single_spike_filtered", False),
       ("persistent_high_values", True),
-    ], names=["case", "should_enter"])
+    ],
+    names=["case", "should_enter"],
+  )
   def test_max_pred_lat_acc_uses_p97_and_threshold(self, case, should_enter):
     n = len(ModelConstants.T_IDXS)
     th = float(_ENTERING_PRED_LAT_ACC_TH)

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/tests/test_vision_controller_closed_loop.py

@@ -0,0 +1,110 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import gc
+from contextlib import ExitStack
+from unittest import mock
+
+import numpy as np
+
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
+from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanSource
+from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import _A_LAT_REG_MAX
+
+
+def _run_constant_curve(*, scc_enabled: bool, cruise: float, duration: float = 70.0) -> dict[str, np.ndarray]:
+  gc.collect()
+  curvature = 0.005
+  plant = Plant(lead_relevancy=False, speed=30.0)
+  planner = plant.planner
+  planner.dec._enabled = False
+  planner.scc.map.enabled = False
+  planner.scc.vision.enabled = scc_enabled
+  solver_failures = 0
+
+  with ExitStack() as patches:
+    patches.enter_context(mock.patch.object(planner.dec, "_read_params", return_value=None))
+    patches.enter_context(mock.patch.object(planner.scc.map, "update_params", return_value=None))
+    patches.enter_context(mock.patch.object(planner.scc.vision, "_update_params", return_value=None))
+
+    original_mpc_reset = planner.mpc.reset
+
+    def record_mpc_reset(*args, **kwargs):
+      nonlocal solver_failures
+      solver_failures += int(planner.mpc.solution_status != 0)
+      return original_mpc_reset(*args, **kwargs)
+
+    patches.enter_context(mock.patch.object(planner.mpc, "reset", side_effect=record_mpc_reset))
+
+    if scc_enabled:
+      original_update_calculations = planner.scc.vision._update_calculations
+
+      def inject_constant_curvature(sm):
+        velocities = np.asarray(sm['modelV2'].velocity.x, dtype=float)
+        sm['modelV2'].orientationRate.z = (curvature * velocities).tolist()
+        sm['controlsState'].curvature = curvature
+        original_update_calculations(sm)
+
+      patches.enter_context(mock.patch.object(planner.scc.vision, "_update_calculations", side_effect=inject_constant_curvature))
+
+    original_update = planner.update
+
+    def enable_longitudinal(sm):
+      sm['carControl'].enabled = True
+      sm['carControl'].longActive = True
+      original_update(sm)
+
+    patches.enter_context(mock.patch.object(planner, "update", side_effect=enable_longitudinal))
+    rows = []
+    while plant.current_time < duration:
+      output = plant.step(v_cruise=cruise)
+      rows.append(
+        (
+          plant.current_time,
+          output['speed'],
+          output['should_stop'],
+          planner.scc.vision.is_active,
+          planner.source == LongitudinalPlanSource.sccVision,
+          planner.scc.vision.output_v_target,
+        )
+      )
+
+  data = np.asarray(rows, dtype=float)
+  gc.collect()
+  return {
+    'time': data[:, 0],
+    'speed': data[:, 1],
+    'should_stop': data[:, 2],
+    'active': data[:, 3],
+    'scc_source': data[:, 4],
+    'target': data[:, 5],
+    'solver_failures': np.asarray(solver_failures),
+  }
+
+
+class TestVisionControllerClosedLoop(OpenpilotTestCase):
+  def test_constant_curve_recovers_like_stock_speed_cap(self):
+    target = (_A_LAT_REG_MAX / 0.005) ** 0.5
+    scc = _run_constant_curve(scc_enabled=True, cruise=30.0)
+    stock = _run_constant_curve(scc_enabled=False, cruise=target)
+    scc_final = scc['speed'][scc['time'] >= 60.0]
+    stock_final = stock['speed'][stock['time'] >= 60.0]
+
+    # The generated solver can report platform-specific failures for the
+    # synthetic no-lead plant. The feature must not make that stock baseline
+    # worse; requiring an absolute zero would hide a harness difference as a
+    # controller regression.
+    assert scc['solver_failures'] <= stock['solver_failures']
+    assert not scc['should_stop'].any()
+    assert np.all(scc['active'][scc['time'] >= 60.0])
+    assert np.all(scc['scc_source'][scc['time'] >= 60.0])
+    assert np.allclose(scc['target'][scc['time'] >= 60.0], target)
+    assert scc_final.min() >= target - 1.0
+    assert abs(scc_final.mean() - stock_final.mean()) < 0.5
+    assert abs(scc_final.min() - stock_final.min()) < 1.0
+    assert abs(scc_final.max() - stock_final.max()) < 1.0

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/vision_controller.py

@@ -23,25 +23,21 @@ _ENTERING_PRED_LAT_ACC_TH = 1.3  # Predicted Lat Acc threshold to trigger enteri
 _ABORT_ENTERING_PRED_LAT_ACC_TH = 1.1  # Predicted Lat Acc threshold to abort entering state if speed drops.
 
 _TURNING_LAT_ACC_TH = 1.6  # Lat Acc threshold to trigger turning state.
+_URGENT_PRED_LAT_ACC_TH = 3.  # Predicted Lat Acc threshold that requires an immediate speed reduction.
 
 _LEAVING_LAT_ACC_TH = 1.3  # Lat Acc threshold to trigger leaving turn state.
 _FINISH_LAT_ACC_TH = 1.1  # Lat Acc threshold to trigger the end of the turn cycle.
 
 _A_LAT_REG_MAX = 2.  # Maximum lateral acceleration
 
-_NO_OVERSHOOT_TIME_HORIZON = 4.  # s. Time to use for velocity desired based on a_target when not overshooting.
-
-# Lookup table for the minimum smooth deceleration during the ENTERING state
-# depending on the actual maximum absolute lateral acceleration predicted on the turn ahead.
-_ENTERING_SMOOTH_DECEL_V = [-0.2, -1.]  # min decel value allowed on ENTERING state
-_ENTERING_SMOOTH_DECEL_BP = [1.3, 3.]  # absolute value of lat acc ahead
-
-# Lookup table for the acceleration for the TURNING state
-# depending on the current lateral acceleration of the vehicle.
-_TURNING_ACC_V = [0.5, 0., -0.4]  # acc value
-_TURNING_ACC_BP = [1.5, 2.3, 3.]  # absolute value of current lat acc
-
-_LEAVING_ACC = 0.5  # Conformable acceleration to regain speed while leaving a turn.
+_RELIEF_CONFIRMATION_FRAMES = max(1, int(round(0.5 / DT_MDL)))
+_TARGET_TIGHTEN_CONFIRMATION_FRAMES = max(1, int(round(0.1 / DT_MDL)))
+_TARGET_RELEASE_CONFIRMATION_FRAMES = max(1, int(round(0.15 / DT_MDL)))
+_TARGET_TIGHTEN_RATE = 5.  # m/s^2
+_TARGET_RELEASE_RATE = 1.  # m/s^2
+_BELOW_EGO_TARGET_RELEASE_RATE = 3.  # m/s^2
+_MIN_PRED_SPEED = 1.  # m/s
+_MIN_ACTIVATION_SPEED = 10.  # m/s
 
 
 class SmartCruiseControlVision:
@@ -65,14 +61,62 @@ class SmartCruiseControlVision:
     self.state = VisionState.disabled
     self.current_lat_acc = 0.
     self.max_pred_lat_acc = 0.
+    self.relief_frames = 0
+    self.tighten_frames = 0
+    self.release_frames = 0
+
+  def _v_demand(self) -> float:
+    return max(MIN_V, min(self.v_target, self.v_cruise_setpoint))
+
+  def _curve_is_urgent(self) -> bool:
+    return self.current_lat_acc >= _TURNING_LAT_ACC_TH or self.max_pred_lat_acc >= _URGENT_PRED_LAT_ACC_TH
+
+  def _filtered_v_target(self) -> float:
+    demand = self._v_demand()
+
+    if self.output_v_target == V_CRUISE_UNSET:
+      self.tighten_frames = 0
+      self.release_frames = 0
+      if self._curve_is_urgent():
+        return demand
+      return max(demand, min(self.v_ego, self.v_cruise_setpoint))
+
+    if demand < self.output_v_target:
+      self.release_frames = 0
+      if self._curve_is_urgent():
+        self.tighten_frames = 0
+        return demand
+
+      self.tighten_frames += 1
+      if self.tighten_frames < _TARGET_TIGHTEN_CONFIRMATION_FRAMES:
+        return self.output_v_target
+      return max(demand, self.output_v_target - _TARGET_TIGHTEN_RATE * DT_MDL)
+
+    self.tighten_frames = 0
+    releasing_brake = self.output_v_target < min(self.v_ego, demand)
+    if not releasing_brake and self.relief_frames < _RELIEF_CONFIRMATION_FRAMES:
+      self.release_frames = 0
+      return self.output_v_target
+
+    if demand > self.output_v_target:
+      self.release_frames += 1
+      if self.release_frames < _TARGET_RELEASE_CONFIRMATION_FRAMES:
+        return self.output_v_target
+    else:
+      self.release_frames = 0
+
+    release_rate = _BELOW_EGO_TARGET_RELEASE_RATE if releasing_brake else _TARGET_RELEASE_RATE
+    return min(demand, self.output_v_target + release_rate * DT_MDL)
 
   def get_a_target_from_control(self) -> float:
-    return self.a_target
+    return self.a_ego
 
   def get_v_target_from_control(self) -> float:
     if self.is_active:
-      return max(self.v_target, MIN_V) + self.a_target * _NO_OVERSHOOT_TIME_HORIZON
+      return self._filtered_v_target()
 
+    self.tighten_frames = 0
+    self.release_frames = 0
     return V_CRUISE_UNSET
 
   def _update_params(self) -> None:
@@ -82,25 +126,27 @@ class SmartCruiseControlVision:
   def _update_calculations(self, sm: messaging.SubMaster) -> None:
     if not self.long_enabled:
       return
-    else:
-      rate_plan = np.array(np.abs(sm['modelV2'].orientationRate.z))
-      vel_plan = np.array(sm['modelV2'].velocity.x)
 
-      self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
+    rate_plan = np.asarray(np.abs(sm['modelV2'].orientationRate.z), dtype=float)
+    vel_plan = np.asarray(sm['modelV2'].velocity.x, dtype=float)
+    size = min(len(rate_plan), len(vel_plan))
+    rate_plan, vel_plan = rate_plan[:size], vel_plan[:size]
+    valid = np.isfinite(rate_plan) & np.isfinite(vel_plan) & (vel_plan >= _MIN_PRED_SPEED)
 
-      # get the maximum lat accel from the model
-      predicted_lat_accels = rate_plan * vel_plan
-      self.max_pred_lat_acc = np.percentile(predicted_lat_accels, 97)
-
-      # get the maximum curve based on the current velocity
-      v_ego = max(self.v_ego, 0.1)  # ensure a value greater than 0 for calculations
-      max_curve = self.max_pred_lat_acc / (v_ego**2)
-
-      # Get the target velocity for the maximum curve
-      self.v_target = (_A_LAT_REG_MAX / max_curve) ** 0.5
+    self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
+    self.max_pred_lat_acc = 0.
+    self.v_target = V_CRUISE_UNSET
+    if np.any(valid):
+      self.max_pred_lat_acc = float(np.percentile(rate_plan[valid] * vel_plan[valid], 97))
+      max_pred_curvature = float(np.percentile(rate_plan[valid] / vel_plan[valid], 97))
+      if max_pred_curvature > 0.:
+        self.v_target = min(float((_A_LAT_REG_MAX / max_pred_curvature) ** 0.5), V_CRUISE_UNSET)
 
   def _update_state_machine(self) -> tuple[bool, bool]:
     # ENABLED, ENTERING, TURNING, LEAVING, OVERRIDING
+    relief = self.current_lat_acc < _FINISH_LAT_ACC_TH and self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH
+    self.relief_frames = self.relief_frames + 1 if self.state in ACTIVE_STATES and relief else 0
+
     if self.state != VisionState.disabled:
       # longitudinal and feature disable always have priority in a non-disabled state
       if not self.long_enabled or not self.enabled:
@@ -112,7 +158,7 @@ class SmartCruiseControlVision:
         # ENABLED
         if self.state == VisionState.enabled:
           # Do not enter a turn control cycle if the speed is low.
-          if self.v_ego <= MIN_V:
+          if self.v_ego <= _MIN_ACTIVATION_SPEED:
             pass
           # If significant lateral acceleration is predicted ahead, then move to Entering turn state.
           elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
@@ -128,23 +174,26 @@ class SmartCruiseControlVision:
           # Transition to Turning if current lateral acceleration is over the threshold.
           if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
             self.state = VisionState.turning
-          # Abort if the predicted lateral acceleration drops
-          elif self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH:
-            self.state = VisionState.enabled
+          # Begin releasing only after both current and predicted lateral acceleration stay clear.
+          elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES:
+            self.state = VisionState.leaving
 
         # TURNING
         elif self.state == VisionState.turning:
-          # Transition to Leaving if current lateral acceleration drops below a threshold.
+          # Transition out of Turning if current lateral acceleration drops below a threshold.
           if self.current_lat_acc <= _LEAVING_LAT_ACC_TH:
-            self.state = VisionState.leaving
+            self.state = VisionState.entering if self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH else VisionState.leaving
 
         # LEAVING
         elif self.state == VisionState.leaving:
           # Transition back to Turning if current lateral acceleration goes back over the threshold.
           if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
             self.state = VisionState.turning
-          # Finish if current lateral acceleration goes below a threshold.
-          elif self.current_lat_acc < _FINISH_LAT_ACC_TH:
+          # Start a new turn cycle immediately if another curve is predicted.
+          elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
+            self.state = VisionState.entering
+          # Finish after confirmed relief and a gradual release to the cruise setpoint.
+          elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES and self.output_v_target >= self.v_cruise_setpoint:
             self.state = VisionState.enabled
 
     # DISABLED
@@ -157,32 +206,11 @@ class SmartCruiseControlVision:
 
     enabled = self.state in ENABLED_STATES
     active = self.state in ACTIVE_STATES
+    if not active:
+      self.relief_frames = 0
 
     return enabled, active
 
-  def _update_solution(self) -> float:
-    # DISABLED, ENABLED, OVERRIDING
-    if self.state not in ACTIVE_STATES:
-      # when not overshooting, calculate v_turn as the speed at the prediction horizon when following
-      # the smooth deceleration.
-      a_target = self.a_ego
-    # ENTERING
-    elif self.state == VisionState.entering:
-      # when not overshooting, target a smooth deceleration in preparation for a sharp turn to come.
-      a_target = np.interp(self.max_pred_lat_acc, _ENTERING_SMOOTH_DECEL_BP, _ENTERING_SMOOTH_DECEL_V)
-    # TURNING
-    elif self.state == VisionState.turning:
-      # When turning, we provide a target acceleration that is comfortable for the lateral acceleration felt.
-      a_target = np.interp(self.current_lat_acc, _TURNING_ACC_BP, _TURNING_ACC_V)
-    # LEAVING
-    elif self.state == VisionState.leaving:
-      # When leaving, we provide a comfortable acceleration to regain speed.
-      a_target = _LEAVING_ACC
-    else:
-      raise NotImplementedError(f"SCC-V state not supported: {self.state}")
-
-    return a_target
-
   def update(self, sm: messaging.SubMaster, long_enabled: bool, long_override: bool, v_ego: float, a_ego: float,
              v_cruise_setpoint: float) -> None:
     self.long_enabled = long_enabled
@@ -195,7 +223,7 @@ class SmartCruiseControlVision:
     self._update_calculations(sm)
 
     self.is_enabled, self.is_active = self._update_state_machine()
-    self.a_target = self._update_solution()
+    self.a_target = self.a_ego
 
     self.output_v_target = self.get_v_target_from_control()
     self.output_a_target = self.get_a_target_from_control()

openpilot/sunnypilot/selfdrive/controls/lib/stopping_controller.py

@@ -0,0 +1,251 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import math
+
+import numpy as np
+
+from openpilot.common.realtime import DT_CTRL
+from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
+
+
+STOP_LEVEL_V = 0.4  # m/s
+STOP_LEVEL_TAU = 0.2  # s
+STOP_CONFIRM_RISE = 0.2  # m/s^2
+STOP_CONFIRM_DELAY = 0.2  # s
+
+
+class StopConfirm:
+  def __init__(self):
+    self.reset()
+
+  def reset(self):
+    self.level: float | None = None
+    self.collapsed = False
+    self.confirmed_t = -1.0
+
+  def update(self, standstill: bool, v_ego: float, a_long: float | None) -> bool:
+    """returns True once the stop is confirmed and STOP_CONFIRM_DELAY has passed"""
+    if a_long is None or not math.isfinite(a_long):
+      self.reset()
+      return False
+    if v_ego > STOP_LEVEL_V and not standstill:
+      alpha = DT_CTRL / (STOP_LEVEL_TAU + DT_CTRL)
+      self.level = a_long if self.level is None else self.level + alpha * (a_long - self.level)
+      self.collapsed = False
+      self.confirmed_t = -1.0
+      return False
+    if self.level is not None and a_long >= self.level + STOP_CONFIRM_RISE:
+      self.collapsed = True
+    if standstill and self.collapsed:
+      self.confirmed_t = 0.0 if self.confirmed_t < 0.0 else self.confirmed_t + DT_CTRL
+    elif not standstill:
+      self.confirmed_t = -1.0
+    return self.confirmed_t >= STOP_CONFIRM_DELAY - 1e-9
+
+
+class StoppingController:
+  """Optional terminal-stop policy applied after stock LongControl.update()."""
+
+  STOPPING_DECEL_RATE = 0.3  # m/s^2/s
+  STANDSTILL_HOLD_RATE = 1.0  # m/s^2/s
+  STANDSTILL_HOLD_DELAY_LEAD = 1.0  # s
+  STANDSTILL_HOLD_DELAY_NO_LEAD = 1.0  # s
+  STOPPING_FREEZE_MAX = 2.0  # s
+  STOPPING_EXIT_DEBOUNCE = 0.2  # s
+  ENGAGE_STANDSTILL_GRACE = 0.6  # s
+  STOPPING_FOLLOW_MIN = -0.10  # m/s^2
+  STOPPING_FOLLOW_RATE = 2.0  # m/s^3
+  CREEP_V_MIN = 0.03  # m/s
+  CREEP_RATE_GROWTH = 1.5  # m/s^2/s
+  CREEP_RATE_MAX = 1.0  # m/s^2/s
+
+  BLEND_V = 10.0 / 3.6  # m/s:
+  END_V_HI = 5.0 / 3.6  # m/s
+  END_HI = -0.65  # m/s^2
+  END_LO = -0.35  # m/s^2
+  END_CURVE_V = [0.0, 1.0 / 3.6, 2.0 / 3.6, 3.0 / 3.6, 4.0 / 3.6, 5.0 / 3.6]  # m/s
+  END_CURVE_A = [END_LO, (END_LO + -0.56) / 2, -0.56, -0.60, -0.65, END_HI]  # m/s^2
+  END_PLAN_MIN = -0.25  # m/s^2
+  END_RATE = 2.0  # m/s^3
+  END_CAP_RATE = 1.0  # m/s^3
+
+  RELEASE_FAST = 4.0  # m/s^3
+  RELEASE_SLOW = 1.5  # m/s^3
+  RELEASE_BAND_LO = -0.6  # m/s^2
+  RELEASE_BAND_HI = 0.4  # m/s^2
+
+  LAUNCH_RATE = 1.0  # m/s^3
+  REROLL_ACCEL = -0.6  # m/s^2
+  REROLL_JERK = 6.0  # m/s^3
+
+  FLAT_HOLD_ACCEL = -1.2  # m/s^2
+  FLAT_PITCH_DEG = 1.0  # deg
+  SLOPE_PITCH_DEG = 2.0  # deg
+  CF_WINDOW = 10.0  # s
+  CF_V_MAX = 8.0 / 3.6  # m/s
+  CF_TRIGGER = -0.15  # m/s^2
+  CF_END = -0.24  # m/s^2
+  CF_PLAN_SOFT = -0.45  # m/s^2
+  CF_PLAN_FIRM = -0.70  # m/s^2
+  CF_RATE = 0.9  # m/s^3
+
+  CF_SETTLE_ACCEL = -0.6  # m/s^2
+  CF_SETTLE_JERK = 0.72  # m/s^3
+  CF_HOLD_RATE = 0.3  # m/s^2/s
+
+  def __init__(self, stop_accel):
+    self.stop_accel = stop_accel
+    self.stop_confirm = StopConfirm()
+    self.cf_t: float | None = None
+    self.cf_vmax = 0.0
+    self.cf_stopping = False
+    self.cf_stopped = False
+    self.standstill_t = 0.0
+    self.stopping_t = 0.0
+    self.go_t = 0.0
+    self.engaged_t = 0.0
+    self.stopped_once = False
+    self.creep_t = 0.0
+    self.end_active = False
+    self.a_entry = self.END_HI
+    self.releasing = False
+
+  def _blend(self, v_ego):
+    if v_ego < self.END_V_HI:
+      return float(np.interp(max(v_ego, 0.0), self.END_CURVE_V, self.END_CURVE_A))
+    return float(np.interp(v_ego, [self.END_V_HI, self.BLEND_V], [self.END_HI, self.a_entry]))
+
+  def _end_request(self, a_target, prev_accel, v_ego, has_lead=True):
+    line = self._blend(v_ego)
+    target = min(a_target, line)  # the firmer of the plan and the line
+    if not has_lead and v_ego < self.END_V_HI and target < line:
+      return float(min(line, prev_accel + self.END_CAP_RATE * DT_CTRL))
+    step = self.END_RATE * DT_CTRL
+    return float(np.clip(target, prev_accel - step, prev_accel + step))
+
+  def _hold_floor(self, pitch, creeping):
+    if creeping or pitch is None or not math.isfinite(pitch):
+      return self.stop_accel
+    if abs(math.degrees(pitch) - self.FLAT_PITCH_DEG) >= self.SLOPE_PITCH_DEG:
+      return self.stop_accel
+    return max(self.stop_accel, self.FLAT_HOLD_ACCEL)
+
+  def _cf_request(self, a_target, prev_accel):
+    target = float(np.interp(a_target, [self.CF_PLAN_FIRM, self.CF_PLAN_SOFT], [self.CF_PLAN_FIRM, self.CF_END]))
+    target = min(target, a_target) if a_target < self.CF_PLAN_FIRM else target
+    if target < prev_accel:
+      return max(target, min(prev_accel, 0.0) - self.CF_RATE * DT_CTRL)
+    return min(target, prev_accel + self.END_RATE * DT_CTRL)
+
+  def _update_creep_follow(self, state, CS, a_target):
+    if state == LongCtrlState.off:
+      self.cf_t, self.cf_stopping, self.cf_stopped = None, False, False
+      return False
+    if CS.standstill:
+      if self.cf_stopping:
+        self.cf_stopped = True
+      self.cf_t = 0.0 if self.standstill_t > 0.5 else self.cf_t
+      self.cf_vmax, self.cf_stopping = 0.0, False
+      return False
+    self.cf_stopped = False
+    if self.cf_t is None:
+      return False
+    self.cf_t += DT_CTRL
+    self.cf_vmax = max(self.cf_vmax, CS.vEgo)
+    if self.cf_t > self.CF_WINDOW or self.cf_vmax >= self.CF_V_MAX or a_target > 0.0 and self.cf_stopping:
+      self.cf_t, self.cf_stopping = None, False
+      return False
+    if a_target <= self.CF_TRIGGER:
+      self.cf_stopping = True
+    return self.cf_stopping
+
+  def update(self, prev_state, state, CS, a_target, prev_accel, stock_accel, accel_limits, has_lead=False, pitch=None,
+             a_long=None):
+    if prev_state == LongCtrlState.stopping and state == LongCtrlState.pid and CS.standstill:
+      self.go_t += DT_CTRL
+      if self.go_t < self.STOPPING_EXIT_DEBOUNCE:
+        state = LongCtrlState.stopping
+    else:
+      self.go_t = 0.0
+
+    self.standstill_t = self.standstill_t + DT_CTRL if CS.standstill else 0.0
+    self.engaged_t = 0.0 if state == LongCtrlState.off else self.engaged_t + DT_CTRL
+    self.stopping_t = self.stopping_t + DT_CTRL if state == LongCtrlState.stopping else 0.0
+    if state != LongCtrlState.stopping:
+      self.stopped_once = False
+    elif CS.standstill:
+      self.stopped_once = True
+
+    creeping = self.stopped_once and not CS.standstill and CS.vEgo > self.CREEP_V_MIN
+    self.creep_t = self.creep_t + DT_CTRL if creeping else 0.0
+    cf_stop = self._update_creep_follow(state, CS, a_target)
+    stop_confirmed = self.stop_confirm.update(CS.standstill, CS.vEgo, a_long)
+
+    rolling = not CS.standstill and not self.stopped_once
+    if state == LongCtrlState.off or not rolling or CS.vEgo >= self.BLEND_V or a_target > 0.0:
+      self.end_active = False
+    elif not self.end_active and a_target <= self.END_PLAN_MIN:
+      self.end_active = True
+      self.a_entry = min(prev_accel, self.END_HI)
+
+    if state != LongCtrlState.stopping:
+      if cf_stop:
+        return state, float(np.clip(self._cf_request(a_target, prev_accel), accel_limits[0], accel_limits[1]))
+      if self.end_active:
+        return state, float(np.clip(self._end_request(a_target, prev_accel, CS.vEgo, has_lead), accel_limits[0], accel_limits[1]))
+      if prev_state == LongCtrlState.stopping and state == LongCtrlState.pid and prev_accel < self.RELEASE_BAND_HI:
+        self.releasing = True
+      if self.releasing:
+        if stock_accel <= prev_accel or state == LongCtrlState.off:
+          self.releasing = False
+          return state, stock_accel
+        if prev_accel < self.RELEASE_BAND_LO:
+          rate = self.RELEASE_FAST
+        elif prev_accel < self.RELEASE_BAND_HI:
+          rate = self.RELEASE_SLOW
+        else:
+          rate = self.LAUNCH_RATE
+        return state, float(min(stock_accel, prev_accel + rate * DT_CTRL))
+      return state, stock_accel
+
+    output_accel = prev_accel
+    hold_floor = self._hold_floor(pitch, creeping)
+    if output_accel > hold_floor:
+      output_accel = min(output_accel, 0.0)
+      if not CS.standstill and not self.stopped_once and a_target < self.STOPPING_FOLLOW_MIN and a_target > output_accel:
+        output_accel = min(a_target, output_accel + self.STOPPING_FOLLOW_RATE * DT_CTRL)
+      if cf_stop:
+        output_accel = self._cf_request(a_target, prev_accel)
+      elif self.end_active:
+        output_accel = self._end_request(a_target, prev_accel, CS.vEgo, has_lead)
+
+      hold_delay = self.STANDSTILL_HOLD_DELAY_LEAD if has_lead else self.STANDSTILL_HOLD_DELAY_NO_LEAD
+      if CS.standstill and not has_lead and self.engaged_t < self.ENGAGE_STANDSTILL_GRACE:
+        rate = 0.0
+      elif self.cf_stopped and CS.standstill and output_accel > self.CF_SETTLE_ACCEL:
+        output_accel = max(self.CF_SETTLE_ACCEL, output_accel - self.CF_SETTLE_JERK * DT_CTRL)
+        rate = 0.0
+      elif self.cf_stopped and CS.standstill:
+        rate = self.CF_HOLD_RATE  # H: then the rest of the hold, slowly
+      elif self.standstill_t >= hold_delay or stop_confirmed:
+        rate = self.STANDSTILL_HOLD_RATE
+      elif creeping and output_accel > self.REROLL_ACCEL:
+        output_accel = max(self.REROLL_ACCEL, output_accel - self.REROLL_JERK * DT_CTRL)
+        rate = 0.0
+      elif creeping:
+        rate = min(self.STOPPING_DECEL_RATE + self.CREEP_RATE_GROWTH * self.creep_t, self.CREEP_RATE_MAX)
+      elif self.stopping_t >= self.STOPPING_FREEZE_MAX:
+        rate = self.STOPPING_DECEL_RATE
+      else:
+        rate = 0.0
+      if hold_floor != self.stop_accel:
+        output_accel = max(output_accel - rate * DT_CTRL, min(hold_floor, output_accel))
+      else:
+        output_accel -= rate * DT_CTRL
+
+    return state, float(np.clip(output_accel, accel_limits[0], accel_limits[1]))

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_auto_lane_change.py

@@ -8,7 +8,7 @@ from openpilot.common.parameterized import parameterized
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper, LaneChangeState, LaneChangeDirection
 from openpilot.sunnypilot.selfdrive.controls.lib.auto_lane_change import AutoLaneChangeController, AutoLaneChangeMode, \
-  AUTO_LANE_CHANGE_TIMER, ONE_SECOND_DELAY
+  AUTO_LANE_CHANGE_TIMER, ONE_SECOND_DELAY, EDGE_DELAY
 from openpilot.common.test import OpenpilotTestCase
 
 AUTO_LANE_CHANGE_TIMER_COMBOS = [
@@ -61,7 +61,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     # Update controller
     num_updates = int(5.0 / DT_MDL)
     for _ in range(num_updates):  # Run for 5 seconds
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Mode should not allow lane change immediately
     assert not self.alc.auto_lane_change_allowed
@@ -74,11 +74,11 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     self.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGELESS
 
     # Update controller once to read params
-    self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Update multiple times to exceed the timer threshold
     for _ in range(1):  # Should exceed 0.1s with multiple DT_MDL updates
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Now lane change should be allowed
     assert self.alc.lane_change_wait_timer > self.alc.lane_change_delay
@@ -91,7 +91,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     self.alc.lane_change_set_timer = timer_state
 
     # Update controller once
-    self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # The timer should still be below the threshold after one update
     assert not self.alc.auto_lane_change_allowed
@@ -99,7 +99,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     # Update enough times to exceed the threshold (seconds / DT_MDL)
     num_updates = int(timer_delay / DT_MDL) + 1  # Add one extra updates to ensure we exceed the threshold
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Now lane change should be allowed
     assert self.alc.lane_change_wait_timer > self.alc.lane_change_delay
@@ -116,7 +116,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
 
     # Update with brake pressed for 1 second
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=True)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=True)
 
     # Even though it is an auto lane change mode, lane change should be disallowed due to brake pressed prior initiating lane change
     assert not self.alc.auto_lane_change_allowed
@@ -126,7 +126,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
 
     # Even releasing brake shouldn't allow auto lane change
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     assert not self.alc.auto_lane_change_allowed
 
@@ -139,13 +139,13 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     self.alc.lane_change_set_timer = timer_state
 
     # Update with blindspot detected - this should prevent auto lane change
-    self.alc.update_lane_change(blindspot_detected=True, brake_pressed=False)
+    self.alc.update_lane_change(blindspot_detected=True, edge_detected=False, brake_pressed=False)
     assert not self.alc.auto_lane_change_allowed
 
     # Keep updating with blindspot detected - should still prevent auto lane change
     num_updates = int(timer_delay / DT_MDL) + 1  # Add one extra updates to ensure we exceed the threshold
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=True, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=True, edge_detected=False, brake_pressed=False)
     assert not self.alc.auto_lane_change_allowed
 
   @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
@@ -157,13 +157,13 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     self.alc.lane_change_set_timer = timer_state
 
     # First update with blindspot detected to set the negative timer
-    self.alc.update_lane_change(blindspot_detected=True, brake_pressed=False)
+    self.alc.update_lane_change(blindspot_detected=True, edge_detected=False, brake_pressed=False)
     assert not self.alc.auto_lane_change_allowed
 
     # Now update with blindspot cleared - should start incrementing timer from negative value
     num_updates = int((timer_delay + abs(ONE_SECOND_DELAY)) / DT_MDL) + 1
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # After sufficient updates with no blindspot, auto lane change should be allowed
     assert self.alc.auto_lane_change_allowed
@@ -177,7 +177,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
 
     # Update enough times to exceed the threshold (seconds / DT_MDL)
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Now lane change should be allowed
     assert self.alc.lane_change_wait_timer > self.alc.lane_change_delay
@@ -193,7 +193,7 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
 
     # Update enough times to exceed the threshold (seconds / DT_MDL)
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     assert not self.alc.auto_lane_change_allowed
 
@@ -206,7 +206,86 @@ class TestAutoLaneChangeController(OpenpilotTestCase):
     # Simulate updates for a long period of time (e.g., 10 seconds)
     num_updates = int(10.0 / DT_MDL)
     for _ in range(num_updates):
-      self.alc.update_lane_change(blindspot_detected=False, brake_pressed=False)
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
 
     # Lane change should never be allowed
     assert not self.alc.auto_lane_change_allowed
+
+  @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
+  def test_edge_detected_delays_auto_lane_change(self, timer_state, timer_delay):
+    """Test that road edge detection adds delay to auto lane change."""
+    self._reset_states()
+    self.alc.lane_change_bsm_delay = False
+    self.alc.lane_change_set_timer = timer_state
+
+    # Update with edge detected - should prevent auto lane change
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=True, brake_pressed=False)
+    assert not self.alc.auto_lane_change_allowed
+
+    # Keep updating with edge detected - timer keeps resetting, should stay disallowed
+    num_updates = int(timer_delay / DT_MDL) + 1
+    for _ in range(num_updates):
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=True, brake_pressed=False)
+    assert not self.alc.auto_lane_change_allowed
+
+  @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
+  def test_edge_detected_then_cleared_allows_after_delay(self, timer_state, timer_delay):
+    """Test that auto lane change is allowed after edge clears plus extra delay."""
+    self._reset_states()
+    self.alc.lane_change_bsm_delay = False
+    self.alc.lane_change_set_timer = timer_state
+
+    # First update with edge detected to set the negative timer
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=True, brake_pressed=False)
+    assert not self.alc.auto_lane_change_allowed
+
+    # Now update with edge cleared - should start incrementing timer from negative value
+    num_updates = int((timer_delay + abs(EDGE_DELAY)) / DT_MDL) + 1
+    for _ in range(num_updates):
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
+
+    # After sufficient updates with no edge, auto lane change should be allowed
+    assert self.alc.auto_lane_change_allowed
+
+  @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
+  def test_edge_and_bsm_combined_uses_worst_delay(self, timer_state, timer_delay):
+    """Test that when both BSM and edge are detected, the worst (longest) delay wins."""
+    self._reset_states()
+    self.alc.lane_change_bsm_delay = True
+    self.alc.lane_change_set_timer = timer_state
+
+    # Update with both blindspot and edge detected
+    self.alc.update_lane_change(blindspot_detected=True, edge_detected=True, brake_pressed=False)
+    assert not self.alc.auto_lane_change_allowed
+
+    # Clear both - need to wait out the worst delay
+    worst_delay = max(abs(ONE_SECOND_DELAY), abs(EDGE_DELAY))
+    num_updates = int((timer_delay + worst_delay) / DT_MDL) + 1
+    for _ in range(num_updates):
+      self.alc.update_lane_change(blindspot_detected=False, edge_detected=False, brake_pressed=False)
+
+    assert self.alc.auto_lane_change_allowed
+
+  @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
+  def test_nudge_overrides_edge_in_lane_change_blocked(self, timer_state, timer_delay):
+    """Test that lane_change_blocked is False when nudge applied with edge-only."""
+    self._reset_states()
+    self.alc.lane_change_set_timer = timer_state
+
+    # Edge detected, no nudge - should be blocked
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=True, brake_pressed=False, torque_applied=False)
+    assert self.alc.lane_change_blocked
+
+    # Edge detected, nudge applied - should NOT be blocked
+    self.alc.update_lane_change(blindspot_detected=False, edge_detected=True, brake_pressed=False, torque_applied=True)
+    assert not self.alc.lane_change_blocked
+
+  @parameterized.expand(AUTO_LANE_CHANGE_TIMER_COMBOS)
+  def test_nudge_does_not_override_bsm_in_lane_change_blocked(self, timer_state, timer_delay):
+    """Test that lane_change_blocked stays True when BSM detected even with nudge."""
+    self._reset_states()
+    self.alc.lane_change_set_timer = timer_state
+
+    # BSM detected with nudge - should still be blocked
+    self.alc.update_lane_change(blindspot_detected=True, edge_detected=False, brake_pressed=False, torque_applied=True)
+    assert self.alc.lane_change_blocked

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_lane_turn_desire.py

@@ -113,12 +113,56 @@ class TestDesireHelperIntegration(OpenpilotTestCase):
                 left_edge_detected=False, right_edge_detected=False)
     assert dh.desire == expected_desire
 
-  def test_edge_blocks_lane_change(self, set_lane_turn_params):
+  def test_nudge_overrides_edge_detection(self, set_lane_turn_params):
+    """Manual steering nudge should override road edge detection and allow lane change."""
     dh = DesireHelper()
     dh.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGE
     carstate = DummyCarState(vEgo=15, leftBlinker=True, steeringPressed=True, steeringTorque=1)
     for _ in range(10):
       dh.update(carstate, True, 1.0, left_edge_detected=True, right_edge_detected=False)
-    assert dh.lane_change_state == LaneChangeState.preLaneChange
+    assert dh.lane_change_state == LaneChangeState.laneChangeStarting
     assert dh.lane_change_direction == LaneChangeDirection.left
+    assert dh.desire == log.Desire.laneChangeLeft
+
+  def test_nudge_does_not_override_bsm(self, set_lane_turn_params):
+    """Manual steering nudge must NOT override BSM blindspot detection."""
+    dh = DesireHelper()
+    dh.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGE
+    carstate = DummyCarState(vEgo=15, leftBlinker=True, leftBlindspot=True, steeringPressed=True, steeringTorque=1)
+    for _ in range(10):
+      dh.update(carstate, True, 1.0, left_edge_detected=False, right_edge_detected=False)
+    assert dh.lane_change_state == LaneChangeState.preLaneChange
     assert dh.desire == log.Desire.none
+
+  def test_edge_blocks_auto_lane_change(self, set_lane_turn_params):
+    """Road edge detection should still block auto (nudgeless) lane changes."""
+    dh = DesireHelper()
+    dh.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGELESS
+    dh.alc.param_read_counter = 1
+    carstate = DummyCarState(vEgo=15, leftBlinker=True)
+    for _ in range(10):
+      dh.update(carstate, True, 1.0, left_edge_detected=True, right_edge_detected=False)
+    assert dh.lane_change_state == LaneChangeState.preLaneChange
+    assert dh.desire == log.Desire.none
+
+  def test_auto_lane_change_allowed_without_edge(self, set_lane_turn_params):
+    """Auto lane change should proceed when no edge and no BSM detected."""
+    dh = DesireHelper()
+    dh.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGELESS
+    dh.alc.param_read_counter = 1
+    carstate = DummyCarState(vEgo=15, leftBlinker=True)
+    for _ in range(10):
+      dh.update(carstate, True, 1.0, left_edge_detected=False, right_edge_detected=False)
+    assert dh.lane_change_state == LaneChangeState.laneChangeStarting
+    assert dh.desire == log.Desire.laneChangeLeft
+
+  def test_right_edge_does_not_block_left_lane_change(self, set_lane_turn_params):
+    """Edge on opposite side should not affect lane change direction."""
+    dh = DesireHelper()
+    dh.alc.lane_change_set_timer = AutoLaneChangeMode.NUDGELESS
+    dh.alc.param_read_counter = 1
+    carstate = DummyCarState(vEgo=15, leftBlinker=True)
+    for _ in range(10):
+      dh.update(carstate, True, 1.0, left_edge_detected=False, right_edge_detected=True)
+    assert dh.lane_change_state == LaneChangeState.laneChangeStarting
+    assert dh.desire == log.Desire.laneChangeLeft

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_stopping_controller.py

@@ -0,0 +1,314 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+import math
+from types import SimpleNamespace
+
+from openpilot.common.realtime import DT_CTRL
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
+from openpilot.sunnypilot.selfdrive.controls.lib.stopping_controller import StoppingController
+
+LIMITS = (-3.5, 2.0)
+PID, STOPPING, OFF = LongCtrlState.pid, LongCtrlState.stopping, LongCtrlState.off
+END_LO, END_HI = StoppingController.END_LO, StoppingController.END_HI
+
+
+def cs(v_kph, standstill=False):
+  return SimpleNamespace(vEgo=v_kph / 3.6, standstill=standstill)
+
+
+def run(sc, state, car, a_target, prev, secs, stock=None):
+  """step the controller for secs with a fixed plan; returns the last output"""
+  out = prev
+  for _ in range(int(secs / DT_CTRL)):
+    _, out = sc.update(state, state, car, a_target, out, a_target if stock is None else stock, LIMITS, has_lead=True)
+  return out
+
+
+def blend(sc, v_kph):
+  return sc._blend(v_kph / 3.6)
+
+
+class TestEndOfStop(OpenpilotTestCase):
+  def test_the_line_runs_from_the_entry_request_through_5kph_to_the_rest_value(self):
+    sc = StoppingController(-2.0)
+    out = run(sc, PID, cs(9.9), -1.20, -1.20, 0.2)
+    assert sc.end_active and abs(sc.a_entry - (-1.20)) < 1e-6
+    # 7.5 km/h: halfway between the entry request and END_HI; the planner has eased to -0.30, the line is sent
+    out = run(sc, PID, cs(7.5), -0.30, out, 0.6)
+    assert abs(blend(sc, 7.5) - (-1.20 + (END_HI - -1.20) * 0.5)) < 1e-6
+    assert abs(out - blend(sc, 7.5)) < 1e-6
+    # 5 km/h: END_HI; below it a parabola: steep first, flat toward the rest value; the wheel stop: END_LO
+    out = run(sc, PID, cs(5.0), -0.20, out, 0.4)
+    assert abs(out - END_HI) < 1e-6
+    out = run(sc, PID, cs(2.5), -0.20, out, 0.4)
+    assert abs(out - (-0.48 + -0.60) / 2) < 1e-6
+    assert abs(blend(sc, 4.0) - (-0.65)) < 1e-6 and abs(blend(sc, 1.0) - (-0.30)) < 1e-6
+    assert abs(blend(sc, 0.5) - (-0.30)) < 1e-6   # 1-0 km/h unchanged
+    out = run(sc, PID, cs(0.0), -0.20, out, 0.4)
+    assert abs(out - END_LO) < 1e-6
+
+  def test_the_line_is_a_floor_a_firmer_plan_still_passes(self):
+    sc = StoppingController(-2.0)
+    out = run(sc, PID, cs(9.9), -1.20, -1.20, 0.2)
+    out = run(sc, PID, cs(5.0), -1.10, out, 0.5)
+    assert abs(out - (-1.10)) < 1e-6
+    out = run(sc, PID, cs(2.5), -1.8, out, 0.6)
+    assert abs(out - (-1.8)) < 1e-6
+
+  def test_a_light_plan_at_entry_starts_the_line_at_end_hi(self):
+    sc = StoppingController(-2.0)
+    light = END_HI + 0.1
+    out = run(sc, PID, cs(7.0), light, light, 0.5)
+    assert abs(sc.a_entry - END_HI) < 1e-6
+    assert abs(out - END_HI) < 1e-6
+    # the planner's own curve eases off below 5 km/h: the request follows the line, never the plan
+    out = run(sc, PID, cs(2.5), -0.10, out, 0.5)
+    assert abs(out - blend(sc, 2.5)) < 1e-6
+
+  def test_entry_is_rate_limited(self):
+    sc = StoppingController(-2.0)
+    light = END_HI + 0.2
+    _, out = sc.update(PID, PID, cs(7.0), light, light, light, LIMITS, has_lead=True)
+    assert out > END_HI
+    assert abs(out - (light - StoppingController.END_RATE * DT_CTRL)) < 1e-6
+
+  def test_an_emergency_plan_still_passes(self):
+    sc = StoppingController(-2.0)
+    out = run(sc, PID, cs(2.5), -1.8, -0.40, 0.8)
+    assert abs(out - (-1.8)) < 1e-6
+
+  def test_crawl_follow_is_untouched(self):
+    sc = StoppingController(-2.0)
+    out = run(sc, PID, cs(2.0), -0.10, -0.10, 0.5)
+    assert abs(out - (-0.10)) < 1e-6
+    assert not sc.end_active
+
+  def test_above_blend_v_nothing_changes(self):
+    sc = StoppingController(-2.0)
+    out = run(sc, PID, cs(12.0), -0.40, -0.40, 0.5)
+    assert abs(out - (-0.40)) < 1e-6
+    assert not sc.end_active
+
+  def test_lead_moving_off_releases_the_hold(self):
+    sc = StoppingController(-2.0)
+    run(sc, PID, cs(2.0), -0.60, -0.60, 0.5)
+    assert sc.end_active
+    _, out = sc.update(PID, PID, cs(1.5), 0.50, END_LO, 0.50, LIMITS, has_lead=True)
+    assert not sc.end_active and abs(out - 0.50) < 1e-6
+
+  def test_stopping_state_keeps_the_line_until_the_wheels_stop_then_holds(self):
+    sc = StoppingController(-1.0)
+    run(sc, PID, cs(2.0), END_HI, END_HI, 0.5)
+    # 1 km/h, stopping state, the planner's curve has eased to -0.10: Kumar's lighter-follow would ease the request
+    out = run(sc, STOPPING, cs(1.0), -0.10, blend(sc, 2.0), 0.4)
+    assert abs(out - blend(sc, 1.0)) < 1e-6
+    # wheels stop: the last value of the line is held until the hold delay, then ramps to stopAccel at the hold rate
+    out_at_stop = run(sc, STOPPING, cs(0.0, standstill=True), -0.10, out, 0.9)
+    assert abs(out_at_stop - out) < 1e-6 and END_HI < out_at_stop <= END_LO + 1e-6
+    out_held = run(sc, STOPPING, cs(0.0, standstill=True), -0.10, out_at_stop, 1.0)
+    assert out_held < out_at_stop - 0.3
+    assert out_held >= -1.0 - 1e-6
+
+
+class TestHoldRelease(OpenpilotTestCase):
+  """2026-10-04 14:43: leaving the hold is fast while the request is far below zero, then linear and slow through the
+  hand-over band, and the plan is never exceeded."""
+
+  def test_release_is_slow_through_the_handover_band(self):
+    sc = StoppingController(-2.0)
+    out = -2.0
+    t = 0.0
+    t_lo = t_hi = None
+    state = STOPPING  # controlsd feeds the returned state back as prev_state (the 0.2 s exit debounce lives there)
+    for _ in range(300):
+      state, out = sc.update(state, PID, cs(0.0, standstill=True), 0.8, out, 0.8, LIMITS, has_lead=True)
+      t += DT_CTRL
+      if t_lo is None and out >= StoppingController.RELEASE_BAND_LO:
+        t_lo = t
+      if t_hi is None and out >= StoppingController.RELEASE_BAND_HI:
+        t_hi = t
+      assert out <= 0.8 + 1e-9
+    assert t_lo is not None and t_lo < 0.6           # 0.2 s debounce, then -2.0 -> -0.6 at the fast rate (0.35 s)
+    assert t_hi is not None and 1.15 < t_hi < 1.3    # then -0.6 -> +0.4 at 1.5 m/s^3 (0.67 s)
+    assert abs(out - 0.8) < 1e-9 and not sc.releasing
+
+  def test_a_plan_that_drops_again_ends_the_release(self):
+    sc = StoppingController(-2.0)
+    state, out = STOPPING, -2.0
+    for _ in range(30):  # through the exit debounce
+      state, out = sc.update(state, PID, cs(0.0, standstill=True), 0.5, out, 0.5, LIMITS, has_lead=True)
+    assert sc.releasing and -2.0 < out < 0.5
+    _, out = sc.update(state, PID, cs(0.0, standstill=True), -2.0, out, -2.0, LIMITS, has_lead=True)
+    assert abs(out - (-2.0)) < 1e-9 and not sc.releasing
+
+
+class TestEngageAtStandstill(OpenpilotTestCase):
+  def _engage(self, has_lead, secs):
+    sc = StoppingController(-2.0)
+    car = cs(0.0, standstill=True)
+    for _ in range(300):  # standing in the auto hold, openpilot not engaged
+      sc.update(OFF, OFF, car, 0.0, 0.0, 0.0, LIMITS, has_lead=has_lead)
+    out = 0.0
+    for _ in range(int(secs / DT_CTRL)):
+      _, out = sc.update(STOPPING, STOPPING, car, 0.0, out, 0.0, LIMITS, has_lead=has_lead)
+    return out, sc
+
+  def test_no_brake_pulse_right_after_engaging_without_lead(self):
+    # route 0000010a 23:58:49: the hold ramp reached -0.21 in 0.2 s and the PCM braked 1600 N before the launch
+    out, sc = self._engage(False, 0.5)
+    assert out == 0.0
+
+  def test_the_hold_ramp_follows_after_the_grace(self):
+    out, sc = self._engage(False, StoppingController.ENGAGE_STANDSTILL_GRACE + 0.3)
+    assert out < -0.2
+
+  def test_with_a_lead_the_hold_starts_at_once(self):
+    out, _ = self._engage(True, 0.3)
+    assert out < -0.2
+
+
+def stand(sc, secs, out=StoppingController.END_LO, pitch=None, a_target=-0.1):
+  state = STOPPING
+  for _ in range(int(secs / DT_CTRL)):
+    state, out = sc.update(state, STOPPING, cs(0.0, standstill=True), a_target, out, a_target, LIMITS, has_lead=True, pitch=pitch)
+  return out
+
+
+FLAT = math.radians(1.0)
+SLOPE = math.radians(-4.0)
+
+
+class TestRerollHold(OpenpilotTestCase):
+  """route 0000010e 17:38:48: stood at -0.30, rolled at 0.8 km/h for 1.1 s inside the hold delay"""
+
+  def _reroll(self, sc):
+    out = stand(sc, 0.9)
+    state = STOPPING
+    outs = []
+    for _ in range(20):
+      state, out = sc.update(state, STOPPING, cs(0.8), -0.05, out, -0.05, LIMITS, has_lead=True)
+      outs.append(out)
+    return outs
+
+  def test_steps_to_the_reroll_request_within_0_1s(self):
+    outs = self._reroll(StoppingController(-2.0))
+    assert outs[4] <= StoppingController.REROLL_ACCEL + 1e-9   # 0.05 s
+    assert all(b - a >= -StoppingController.REROLL_JERK * DT_CTRL - 1e-9 for a, b in zip(outs, outs[1:], strict=False))
+
+
+class TestFlatHold(OpenpilotTestCase):
+  def test_flat_hold_stops_at_minus_1_2(self):
+    out = stand(StoppingController(-2.0), 4.0, pitch=FLAT)
+    assert abs(out - StoppingController.FLAT_HOLD_ACCEL) < 1e-9
+
+  def test_slope_or_no_pitch_keeps_stop_accel(self):
+    assert stand(StoppingController(-2.0), 4.0, pitch=SLOPE) <= -2.0 + 1e-6
+    assert stand(StoppingController(-2.0), 4.0, pitch=None) <= -2.0 + 1e-6
+
+  def test_a_creep_on_the_flat_hold_goes_deeper(self):
+    sc = StoppingController(-2.0)
+    out = stand(sc, 4.0, pitch=FLAT)
+    state = STOPPING
+    for _ in range(150):
+      state, out = sc.update(state, STOPPING, cs(0.8), -0.1, out, -0.1, LIMITS, has_lead=True, pitch=FLAT)
+    assert out < StoppingController.FLAT_HOLD_ACCEL - 0.5
+
+
+class TestCreepFollowStop(OpenpilotTestCase):
+  """route 0000010d 23:56:59: lead moved ~2 m, the car followed at 2.5 km/h and the brake bit at -0.88"""
+
+  def _creep(self, sc, plan, v_kph=2.0, secs=2.0, out=0.4):
+    stand(sc, 2.0)
+    outs = []
+    for _ in range(int(secs / DT_CTRL)):
+      _, out = sc.update(PID, PID, cs(v_kph), plan, out, plan, LIMITS, has_lead=True)
+      outs.append(out)
+    return outs
+
+  def test_stops_with_minus_0_24_not_the_end_line(self):
+    outs = self._creep(StoppingController(-2.0), -0.40)
+    assert outs[0] <= 0.0                       # a positive request is dropped at once
+    assert abs(outs[-1] - StoppingController.CF_END) < 1e-9
+    steps = [a - b for a, b in zip(outs, outs[1:], strict=False)]
+    assert max(steps) <= StoppingController.CF_RATE * DT_CTRL + 1e-9
+
+  def test_a_firm_plan_still_wins(self):
+    outs = self._creep(StoppingController(-2.0), -1.0)
+    assert abs(outs[-1] - (-1.0)) < 1e-9
+
+  def test_light_plan_keeps_minus_0_24_to_the_stop(self):
+    sc = StoppingController(-2.0)
+    outs = self._creep(sc, -0.40, secs=1.0)
+    _, out = sc.update(PID, PID, cs(1.0), -0.10, outs[-1], -0.10, LIMITS, has_lead=True)
+    assert abs(out - StoppingController.CF_END) < 1e-9
+
+  def test_not_after_a_real_launch(self):
+    sc = StoppingController(-2.0)
+    stand(sc, 2.0)
+    out = 0.5
+    for _ in range(300):
+      _, out = sc.update(PID, PID, cs(15.0), 0.3, out, 0.3, LIMITS, has_lead=True)
+    _, out = sc.update(PID, PID, cs(6.0), -0.40, out, -0.40, LIMITS, has_lead=True)
+    assert sc.cf_t is None
+
+  def test_lead_moving_off_ends_it(self):
+    sc = StoppingController(-2.0)
+    outs = self._creep(sc, -0.40, secs=0.5)
+    _, out = sc.update(PID, PID, cs(2.0), 0.5, outs[-1], 0.5, LIMITS, has_lead=True)
+    assert out == 0.5 and not sc.cf_stopping
+
+  def test_after_the_creep_stop_a_little_brake_at_once_then_the_hold_slowly(self):
+    """route 00000112 23:16:57: -0.24 for the 1.0 s hold delay, then -1.2 within ~1 s felt like a second brake"""
+    sc = StoppingController(-2.0)
+    outs = self._creep(sc, -0.40)
+    out, state, trace = outs[-1], STOPPING, []
+    for _ in range(300):
+      state, out = sc.update(state, STOPPING, cs(0.0, standstill=True), -0.05, out, -0.05, LIMITS, has_lead=True,
+                             pitch=FLAT)
+      trace.append(out)
+    assert trace[50] <= StoppingController.CF_SETTLE_ACCEL + 1e-9          # -0.6 within 0.5 s, no hold delay
+    assert trace[10] > StoppingController.CF_SETTLE_ACCEL                    # but gradually
+    assert abs(trace[150] - (StoppingController.CF_SETTLE_ACCEL - 1.0 * StoppingController.CF_HOLD_RATE)) < 0.02
+    assert abs(trace[-1] - StoppingController.FLAT_HOLD_ACCEL) < 1e-9       # the flat hold after ~2.5 s
+    steps = [a - b for a, b in zip(trace, trace[1:], strict=False)]
+    assert max(steps) <= StoppingController.CF_SETTLE_JERK * DT_CTRL + 1e-9
+
+  def test_an_ordinary_stop_keeps_the_hold_delay(self):
+    sc = StoppingController(-2.0)
+    out = stand(sc, 0.9, pitch=FLAT)
+    assert abs(out - END_LO) < 1e-9
+
+
+class TestConfirmedStopEarlyHold(OpenpilotTestCase):
+  """hold 0.2 s after a CONFIRMED stop (standstill flag + the body's deceleration collapsing), else the 1.0 s delay"""
+
+  def _stop(self, sc, collapse):
+    out, state = -0.40, PID
+    for k in range(100):  # rolling to the stop at -0.45 m/s^2 (body)
+      state, out = sc.update(state, STOPPING, cs(2.0 - 0.019 * k), -0.3, out, -0.3, LIMITS, has_lead=True, pitch=FLAT, a_long=-0.45)
+    trace = []
+    for k in range(150):  # standing: the body pitches back (deceleration collapses) after 0.1 s, or not
+      a = -0.05 if (collapse and k >= 10) else -0.45
+      state, out = sc.update(state, STOPPING, cs(0.0, True), -0.05, out, -0.05, LIMITS, has_lead=True, pitch=FLAT, a_long=a)
+      trace.append(out)
+    return trace
+
+  def test_confirmed_stop_holds_after_0_2s(self):
+    sc = StoppingController(-2.0)
+    tr = self._stop(sc, True)
+    assert tr[25] == tr[0]                 # 0.1 s to the pitch-back + 0.2 s: nothing yet at 0.25 s
+    assert tr[40] < tr[0] - 0.05           # holding by 0.4 s
+
+  def test_no_confirmation_keeps_the_1s_delay(self):
+    sc = StoppingController(-2.0)
+    tr = self._stop(sc, False)
+    assert tr[90] == tr[0] and tr[110] < tr[0]
+
+  def test_no_pose_keeps_the_1s_delay(self):
+    sc = StoppingController(-2.0)
+    assert not sc.stop_confirm.update(True, 0.0, None)

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -0,0 +1,433 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+from collections import deque
+from collections.abc import Callable
+from dataclasses import asdict, dataclass
+import math
+import time
+from typing import Any
+
+import numpy as np
+
+from openpilot.cereal import log, messaging
+from opendbc.car.interfaces import ACCEL_MAX, ACCEL_MIN
+from openpilot.common.realtime import DT_CTRL, DT_MDL, Ratekeeper
+from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState
+from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanner
+from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
+from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant, PlannerSM
+
+
+LeadObservation = dict[str, Any]
+LeadObservationFn = Callable[[float, str, LeadObservation], LeadObservation | None]
+ModelActionFn = Callable[[float, float, float], tuple[float, bool]]
+EgoObservationFn = Callable[[float, float, float], tuple[float, float]]
+ModelPlanFn = Callable[[float, float, float], list[float]]
+ModelMetaFn = Callable[[float], tuple[list[float], bool, float]]
+LeadFutureProbsFn = Callable[[float], tuple[float, float, float]]
+PositionYFn = Callable[[float], list[float]]
+ExperimentalModeFn = Callable[[float], bool]
+
+
+@dataclass(frozen=True)
+class ActuatorModel:
+  planner_delay: float
+  transport_delay: float
+  actuator_lag: float
+  command_rate_limit: float
+  stopping_acceleration: float
+  standstill_breakaway_acceleration: float
+  standstill_breakaway_time: float
+
+  def __post_init__(self):
+    nonnegative_fields = {
+      "planner_delay": self.planner_delay,
+      "transport_delay": self.transport_delay,
+      "actuator_lag": self.actuator_lag,
+      "standstill_breakaway_acceleration": self.standstill_breakaway_acceleration,
+      "standstill_breakaway_time": self.standstill_breakaway_time,
+    }
+    if any(not math.isfinite(value) or value < 0.0 for value in nonnegative_fields.values()):
+      raise ValueError(f"ActuatorModel fields must be finite and non-negative: {nonnegative_fields}")
+    if not math.isfinite(self.command_rate_limit) or self.command_rate_limit <= 0.0:
+      raise ValueError("command_rate_limit must be finite and positive")
+    if not math.isfinite(self.stopping_acceleration) or self.stopping_acceleration > 0.0:
+      raise ValueError("stopping_acceleration must be finite and non-positive")
+
+
+# Conservative Prius TSS2 actuator model.
+PRIUS_TSS2_ROUTE_MODEL = ActuatorModel(
+  planner_delay=0.05,
+  transport_delay=0.0,
+  actuator_lag=0.20,
+  command_rate_limit=4.0,
+  stopping_acceleration=-2.0,
+  standstill_breakaway_acceleration=1.0,
+  standstill_breakaway_time=0.05,
+)
+
+
+class PlantSP(Plant):
+  """Closed-loop plant with configurable observations and actuator response."""
+
+  def __init__(
+    self,
+    lead_relevancy=False,
+    speed=0.0,
+    distance_lead=2.0,
+    enabled=True,
+    only_lead2=False,
+    only_radar=False,
+    e2e=False,
+    personality=0,
+    force_decel=False,
+    lead_observation_fn: LeadObservationFn | None = None,
+    model_action_fn: ModelActionFn | None = None,
+    ego_observation_fn: EgoObservationFn | None = None,
+    model_plan_fn: ModelPlanFn | None = None,
+    model_meta_fn: ModelMetaFn | None = None,
+    lead_future_probs_fn: LeadFutureProbsFn | None = None,
+    position_y_fn: PositionYFn | None = None,
+    experimental_mode_fn: ExperimentalModeFn | None = None,
+    actuator_delay: float | None = None,
+    actuator_lag: float = 0.0,
+    actuator_model: ActuatorModel | None = None,
+    run_long_control: bool = False,
+  ):
+    if actuator_delay is not None and (not math.isfinite(actuator_delay) or actuator_delay < 0.0):
+      raise ValueError("actuator_delay must be finite and non-negative")
+    if not math.isfinite(actuator_lag) or actuator_lag < 0.0:
+      raise ValueError("actuator_lag must be finite and non-negative")
+
+    self.rate = 1.0 / DT_MDL
+
+    if not Plant.messaging_initialized:
+      Plant.radar = messaging.pub_sock('radarState')
+      Plant.controls_state = messaging.pub_sock('controlsState')
+      Plant.selfdrive_state = messaging.pub_sock('selfdriveState')
+      Plant.car_state = messaging.pub_sock('carState')
+      Plant.plan = messaging.sub_sock('longitudinalPlan')
+      Plant.messaging_initialized = True
+
+    self.v_lead_prev = 0.0
+
+    self.distance = 0.0
+    self.speed = speed
+    self.should_stop = False
+    self.acceleration = 0.0
+    self.a_target = 0.0
+    self.actuator_command = 0.0
+    self.applied_actuator_command = 0.0
+    self.breakaway_confirmed = False
+    self._breakaway_timer = 0.0
+
+    # lead car
+    self.lead_relevancy = lead_relevancy
+    self.distance_lead = distance_lead
+    self.enabled = enabled
+    self.only_lead2 = only_lead2
+    self.only_radar = only_radar
+    self.e2e = e2e
+    self.personality = personality
+    self.force_decel = force_decel
+    self.lead_observation_fn = lead_observation_fn
+    self.model_action_fn = model_action_fn
+    self.ego_observation_fn = ego_observation_fn
+    self.model_plan_fn = model_plan_fn
+    self.model_meta_fn = model_meta_fn
+    self.lead_future_probs_fn = lead_future_probs_fn
+    self.position_y_fn = position_y_fn
+    self.experimental_mode_fn = experimental_mode_fn
+    self.actuator_model = actuator_model
+    self.actuator_delay = actuator_model.planner_delay if actuator_model is not None else actuator_delay
+    self.transport_delay = actuator_model.transport_delay if actuator_model is not None else actuator_delay
+    self.actuator_lag = actuator_model.actuator_lag if actuator_model is not None else actuator_lag
+    self.publish_realized_a_ego = any((lead_observation_fn is not None, model_action_fn is not None, ego_observation_fn is not None,
+                                      actuator_delay is not None, actuator_lag > 0.0, actuator_model is not None, run_long_control))
+
+    self.rk = Ratekeeper(self.rate, print_delay_threshold=100.0)
+    self.ts = 1.0 / self.rate
+    time.sleep(0.1)
+    self.sm = messaging.SubMaster(['longitudinalPlan'])
+
+    from opendbc.car.honda.values import CAR
+    from opendbc.car.honda.interface import CarInterface
+
+    CP = CarInterface.get_non_essential_params(CAR.HONDA_CIVIC)
+    if self.actuator_delay is not None:
+      CP.longitudinalActuatorDelay = self.actuator_delay
+    CP_SP = CarInterface.get_non_essential_params_sp(CP, CAR.HONDA_CIVIC)
+    self.planner = LongitudinalPlanner(CP, CP_SP, init_v=self.speed)
+    self.long_control = LongControl(CP, CP_SP) if run_long_control else None
+
+    if self.actuator_model is not None and self.speed >= 0.01:
+      self.breakaway_confirmed = True
+    self.integration_dt = DT_CTRL if run_long_control else self.ts
+    delay_steps = 0 if self.transport_delay is None else round(self.transport_delay / self.integration_dt)
+    self._actuator_delay_queue = deque([self.acceleration] * delay_steps)
+
+  @staticmethod
+  def _lead_message(observation: LeadObservation):
+    lead = log.RadarState.LeadData.new_message()
+    for field, value in observation.items():
+      setattr(lead, field, value)
+    return lead
+
+  def _observe_lead(self, lead_name: str, truth: LeadObservation, present_by_default: bool) -> LeadObservation | None:
+    if self.lead_observation_fn is None:
+      return dict(truth) if present_by_default else None
+
+    observed = self.lead_observation_fn(self.current_time, lead_name, dict(truth))
+    if observed is None:
+      return None
+
+    complete_observation = dict(truth)
+    complete_observation.update(observed)
+    return complete_observation
+
+  def _update_actuator(self, command: float) -> tuple[float, float]:
+    if self._actuator_delay_queue:
+      self._actuator_delay_queue.append(command)
+      delayed_command = self._actuator_delay_queue.popleft()
+    else:
+      delayed_command = command
+
+    if self.actuator_model is not None:
+      max_command_delta = self.actuator_model.command_rate_limit * self.integration_dt
+      self.applied_actuator_command = float(np.clip(delayed_command,
+                                                   self.applied_actuator_command - max_command_delta,
+                                                   self.applied_actuator_command + max_command_delta))
+
+      if self.speed < 0.01:
+        if self.applied_actuator_command <= 0.0:
+          self.breakaway_confirmed = False
+          self._breakaway_timer = 0.0
+        elif not self.breakaway_confirmed:
+          breakaway_ready = self.applied_actuator_command + 1e-9 >= self.actuator_model.standstill_breakaway_acceleration
+          if breakaway_ready:
+            self._breakaway_timer += self.integration_dt
+          else:
+            self._breakaway_timer = 0.0
+
+          self.breakaway_confirmed = breakaway_ready and self._breakaway_timer + 1e-9 >= self.actuator_model.standstill_breakaway_time
+        if not self.breakaway_confirmed:
+          self.acceleration = 0.0
+          return delayed_command, self.acceleration
+      else:
+        self.breakaway_confirmed = True
+
+      response_command = self.applied_actuator_command
+    else:
+      self.applied_actuator_command = delayed_command
+      response_command = delayed_command
+
+    if self.actuator_lag > 0.0:
+      alpha = 1.0 - math.exp(-self.integration_dt / self.actuator_lag)
+      self.acceleration += alpha * (response_command - self.acceleration)
+    else:
+      self.acceleration = response_command
+    return delayed_command, self.acceleration
+
+  def _integrate_ego(self, dt: float, stop_at_standstill: bool = False) -> None:
+    self.speed += self.acceleration * dt
+    if self.speed <= 0.0 or stop_at_standstill and self.speed < 0.01 and self.actuator_command <= 0.0:
+      self.speed = self.acceleration = 0.0
+    self.distance += self.speed * dt
+
+  def step(self, v_lead=0.0, prob_lead=1.0, v_cruise=50.0, pitch=0.0, prob_throttle=1.0):
+    # ******** publish a fake model going straight and fake calibration ********
+    # note that this is worst case for MPC, since model will delay long mpc by one time step
+    radar = messaging.new_message('radarState')
+    control = messaging.new_message('controlsState')
+    ss = messaging.new_message('selfdriveState')
+    car_state = messaging.new_message('carState')
+    vehicle_parameters = messaging.new_message('vehicleParameters')
+    car_control = messaging.new_message('carControl')
+    model = messaging.new_message('modelV2')
+    car_state_sp = messaging.new_message('carStateSP')
+    live_map_data_sp = messaging.new_message('liveMapDataSP')
+    gps_data = messaging.new_message('gpsLocation')
+    a_lead = (v_lead - self.v_lead_prev) / self.ts
+    self.v_lead_prev = v_lead
+
+    if self.lead_relevancy:
+      d_rel = np.maximum(0.0, self.distance_lead - self.distance)
+      v_rel = v_lead - self.speed
+      if self.only_radar:
+        status = True
+      elif prob_lead > 0.5:
+        status = True
+      else:
+        status = False
+    else:
+      d_rel = 200.0
+      v_rel = 0.0
+      prob_lead = 0.0
+      status = False
+
+    truth_lead: LeadObservation = {
+      "dRel": float(d_rel),
+      "yRel": 0.0,
+      "vRel": float(v_rel),
+      "vLead": float(v_lead),
+      "vLeadK": float(v_lead),
+      "aLeadK": float(a_lead),
+      "present": bool(status),
+      # TODO use real radard logic for this
+      "aLeadTau": float(_LEAD_ACCEL_TAU),
+      "modelProb": float(prob_lead),
+      "radar": bool(self.only_radar),
+      "radarTrackId": -1,
+    }
+    lead_one_observation = self._observe_lead("leadOne", truth_lead, not self.only_lead2)
+    lead_two_observation = self._observe_lead("leadTwo", truth_lead, True)
+    if lead_one_observation is not None:
+      radar.radarState.leadOne = self._lead_message(lead_one_observation)
+    if lead_two_observation is not None:
+      radar.radarState.leadTwo = self._lead_message(lead_two_observation)
+
+    # Simulate model predicting slightly faster speed
+    # this is to ensure lead policy is effective when model
+    # does not predict slowdown in e2e mode
+    position = log.XYZTData.new_message()
+    position.x = [float(x) for x in (self.speed + 0.5) * np.array(ModelConstants.T_IDXS)]
+    if self.position_y_fn is None:
+      position.y = [0.0] * len(ModelConstants.T_IDXS)
+    else:
+      position.y = [float(y) for y in self.position_y_fn(self.current_time)]
+    model.modelV2.position = position
+    if self.model_action_fn is None:
+      model_acceleration, model_should_stop = self.acceleration + 0.5, False
+    else:
+      model_acceleration, model_should_stop = self.model_action_fn(self.current_time, self.speed, self.acceleration)
+    model.modelV2.action.desiredAcceleration = float(model_acceleration)
+    model.modelV2.action.shouldStop = bool(model_should_stop)
+    velocity = log.XYZTData.new_message()
+    if self.model_plan_fn is None:
+      velocity_plan = [float(x) for x in (self.speed + 0.5) * np.ones_like(ModelConstants.T_IDXS)]
+      velocity_plan[0] = float(self.speed)  # always start at current speed
+    else:
+      velocity_plan = [float(x) for x in self.model_plan_fn(self.current_time, self.speed, self.acceleration)]
+    velocity.x = velocity_plan
+    model.modelV2.velocity = velocity
+    acceleration = log.XYZTData.new_message()
+    acceleration.x = [float(x) for x in np.zeros_like(ModelConstants.T_IDXS)]
+    model.modelV2.acceleration = acceleration
+    model.modelV2.meta.disengagePredictions.gasPressProbs = [float(prob_throttle) for _ in range(6)]
+    if self.model_meta_fn is None:
+      brake3_probs, hard_brake_predicted, frame_drop_perc = [0.0] * 5, False, 0.0
+    else:
+      brake3_probs, hard_brake_predicted, frame_drop_perc = self.model_meta_fn(self.current_time)
+    model.modelV2.meta.disengagePredictions.brake3MetersPerSecondSquaredProbs = [float(p) for p in brake3_probs]
+    model.modelV2.meta.hardBrakePredicted = bool(hard_brake_predicted)
+    model.modelV2.frameDropPerc = float(frame_drop_perc)
+    if self.lead_future_probs_fn is not None:
+      model.modelV2.init('leadsV3', 3)
+      lead_future_probs = self.lead_future_probs_fn(self.current_time)
+      for i, (prob, prob_time) in enumerate(zip(lead_future_probs, (0.0, 2.0, 4.0), strict=True)):
+        model.modelV2.leadsV3[i].prob = float(prob)
+        model.modelV2.leadsV3[i].probTime = prob_time
+
+    control.controlsState.longControlState = self.long_control.long_control_state if self.long_control is not None else (
+      LongCtrlState.pid if self.enabled else LongCtrlState.off)
+    ss.selfdriveState.experimentalMode = self.e2e if self.experimental_mode_fn is None else bool(self.experimental_mode_fn(self.current_time))
+    ss.selfdriveState.personality = self.personality
+    control.controlsState.forceDecel = self.force_decel
+    true_v_ego = self.speed
+    true_a_ego = self.acceleration
+    published_v_ego = true_v_ego
+    published_a_ego = true_a_ego if self.publish_realized_a_ego else 0.0
+    if self.ego_observation_fn is not None:
+      published_v_ego, published_a_ego = self.ego_observation_fn(self.current_time, true_v_ego, true_a_ego)
+    car_state.carState.vEgo = float(published_v_ego)
+    car_state.carState.aEgo = float(published_a_ego)
+    car_state.carState.standstill = bool(self.speed < 0.01)
+    car_state.carState.vCruise = float(v_cruise * 3.6)
+    car_control.carControl.orientationNED = [0.0, float(pitch), 0.0]
+
+    # ******** get controlsState messages for plotting ***
+    sm = PlannerSM(self.rk.frame, {
+      'radarState': radar.radarState,
+      'carState': car_state.carState,
+      'carControl': car_control.carControl,
+      'controlsState': control.controlsState,
+      'selfdriveState': ss.selfdriveState,
+      'vehicleParameters': vehicle_parameters.vehicleParameters,
+      'modelV2': model.modelV2,
+      'carStateSP': car_state_sp.carStateSP,
+      'liveMapDataSP': live_map_data_sp.liveMapDataSP,
+      'gpsLocation': gps_data.gpsLocation,
+    })
+    self.planner.update(sm)
+    self.a_target = self.planner.output_a_target
+    if self.long_control is None:
+      self.actuator_command = self.a_target
+      if self.planner.output_should_stop:
+        stopping_acceleration = -0.5 if self.actuator_model is None else self.actuator_model.stopping_acceleration
+        self.actuator_command = min(stopping_acceleration, self.actuator_command)
+      self._update_actuator(self.actuator_command)
+      self._integrate_ego(self.ts)
+    else:
+      for _ in range(round(self.ts / DT_CTRL)):
+        car_state.carState.vEgo = self.speed
+        car_state.carState.aEgo = self.acceleration
+        car_state.carState.standstill = self.speed < 0.01
+        self.actuator_command = self.long_control.update(
+          self.enabled, car_state.carState, self.a_target, self.planner.output_should_stop, (ACCEL_MIN, ACCEL_MAX),
+        )
+        self._update_actuator(self.actuator_command)
+        self._integrate_ego(DT_CTRL, stop_at_standstill=True)
+    self.should_stop = self.planner.output_should_stop
+    fcw = self.planner.fcw
+    self.distance_lead = self.distance_lead + v_lead * self.ts
+
+    # *** radar model ***
+    if self.lead_relevancy:
+      d_rel = np.maximum(0.0, self.distance_lead - self.distance)
+      v_rel = v_lead - self.speed
+    else:
+      d_rel = 200.0
+      v_rel = 0.0
+
+    # print at 5hz
+    # if (self.rk.frame % (self.rate // 5)) == 0:
+    #   print("%2.2f sec   %6.2f m  %6.2f m/s  %6.2f m/s2   lead_rel: %6.2f m  %6.2f m/s"
+    #         % (self.current_time, self.distance, self.speed, self.acceleration, d_rel, v_rel))
+
+    # ******** update prevs ********
+    self.rk.monitor_time()
+
+    return {
+      "distance": self.distance,
+      "speed": self.speed,
+      "acceleration": self.acceleration,
+      "realized_acceleration": self.acceleration,
+      "a_target": self.a_target,
+      "actuator_command": self.actuator_command,
+      "published_a_ego": published_a_ego,
+      "published_v_ego": published_v_ego,
+      "should_stop": self.should_stop,
+      "long_control_state": (int(self.long_control.long_control_state) if self.long_control is not None
+                             else control.controlsState.longControlState.raw),
+      "distance_lead": self.distance_lead,
+      "fcw": fcw,
+      "mpc_source": self.planner.mpc.source,
+      "dec_mode": self.planner.dec.mode(),
+      "dec_want_blended": self.planner.dec.want_blended,
+      "dec_signals": asdict(self.planner.dec.signals),
+      "dec_lead_veto": self.planner.dec.lead_veto,
+      "controller_active": self.planner.accel_controller_active,
+      "model_action": {
+        "desiredAcceleration": float(model_acceleration),
+        "shouldStop": bool(model_should_stop),
+      },
+      "truth_lead": dict(truth_lead),
+      "lead_one_observation": None if lead_one_observation is None else dict(lead_one_observation),
+      "lead_two_observation": None if lead_two_observation is None else dict(lead_two_observation),
+    }

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/tests/test_dec_maneuvers.py

@@ -0,0 +1,186 @@
+import numpy as np
+
+from openpilot.common.params import Params
+from openpilot.common.realtime import DT_MDL
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import ENTER_FRAMES, MIN_BLENDED_FRAMES
+from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP
+
+T_IDXS = np.array(ModelConstants.T_IDXS)
+
+
+def decel_plan(a):
+  def fn(_current_time, speed, _acceleration):
+    return [float(max(0.0, speed + a * t)) for t in T_IDXS]
+  return fn
+
+
+def flat_plan():
+  def fn(_current_time, speed, _acceleration):
+    return [float(speed)] * len(T_IDXS)
+  return fn
+
+
+def alternating_plan(a):
+  def fn(current_time, speed, _acceleration):
+    frame_a = a if round(current_time / DT_MDL) % 2 == 0 else 0.0
+    return [float(max(0.0, speed + frame_a * t)) for t in T_IDXS]
+  return fn
+
+
+def persistent_lead_probs(_current_time):
+  return (1.0, 0.95, 0.9)
+
+
+def _run(plant, steps, v_lead=0.0, v_cruise=50.0):
+  solver_failures = 0
+  original_reset = plant.planner.mpc.reset
+
+  def counting_reset(*args, **kw):
+    nonlocal solver_failures
+    if plant.planner.mpc.solution_status != 0:
+      solver_failures += 1
+    return original_reset(*args, **kw)
+
+  plant.planner.mpc.reset = counting_reset
+  return [plant.step(v_lead=v_lead, v_cruise=v_cruise) for _ in range(steps)], solver_failures
+
+
+def mode_changes(results):
+  modes = [r["dec_mode"] for r in results]
+  return sum(a != b for a, b in zip(modes, modes[1:], strict=False))
+
+
+class TestDecManeuvers(OpenpilotTestCase):
+  def setUp(self):
+    super().setUp()
+    self.params = Params()
+    self.params.put_bool("DynamicExperimentalControl", True, block=True)
+
+  def test_s1_lead_clears_with_underlying_slowdown_blends_quickly(self):
+    clear_t = 1.0
+
+    def lead_obs(current_time, _lead_name, truth):
+      return None if current_time >= clear_t else dict(truth)
+
+    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
+                     lead_observation_fn=lead_obs, model_plan_fn=decel_plan(-2.5),
+                     lead_future_probs_fn=persistent_lead_probs)
+    clear_frame = round(clear_t / DT_MDL)
+    results, _ = _run(plant, steps=clear_frame + ENTER_FRAMES + 5, v_lead=20.0, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "acc" for r in results[:clear_frame])
+    assert all(r["dec_lead_veto"] for r in results[:clear_frame])
+    post_clear = [r["dec_mode"] for r in results[clear_frame:clear_frame + ENTER_FRAMES + 2]]
+    assert "blended" in post_clear
+
+  def test_s1b_lead_clears_with_no_underlying_slowdown_stays_acc(self):
+    clear_t = 1.0
+
+    def lead_obs(current_time, _lead_name, truth):
+      return None if current_time >= clear_t else dict(truth)
+
+    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
+                     lead_observation_fn=lead_obs, model_plan_fn=flat_plan(),
+                     lead_future_probs_fn=persistent_lead_probs)
+    clear_frame = round(clear_t / DT_MDL)
+    results, _ = _run(plant, steps=clear_frame + MIN_BLENDED_FRAMES, v_lead=20.0, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s2_steady_highway_following_never_blends(self):
+    v = 80.0 / 3.6
+    plant = PlantSP(lead_relevancy=True, speed=v, distance_lead=40.0, e2e=True, only_radar=True,
+                     model_plan_fn=flat_plan(), lead_future_probs_fn=persistent_lead_probs)
+    results, failures = _run(plant, steps=100, v_lead=v, v_cruise=v)
+
+    assert failures <= 1
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s3_low_speed_cruise_no_lead_never_blends(self):
+    v = 15.0 / 3.6
+    plant = PlantSP(lead_relevancy=False, speed=v, e2e=True, model_plan_fn=flat_plan())
+    results, _ = _run(plant, steps=100, v_cruise=v)
+
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s4_highway_slowdown_without_lead_blends(self):
+    v0 = 110.0 / 3.6
+    a = (70.0 / 3.6 - v0) / 6.0
+    plant = PlantSP(lead_relevancy=False, speed=v0, e2e=True, model_plan_fn=decel_plan(a))
+    results, _ = _run(plant, steps=10, v_cruise=v0)
+
+    assert any(r["dec_mode"] == "blended" for r in results)
+
+  def test_s5_stop_then_depart_with_lead_present_stays_acc_throughout(self):
+    def departing_lead(current_time):
+      return 0.0 if current_time < 1.0 else min(15.0, 3.0 * (current_time - 1.0))
+
+    plant = PlantSP(lead_relevancy=True, speed=0.0, distance_lead=6.0, e2e=True)
+    results = []
+    solver_failures = 0
+    original_reset = plant.planner.mpc.reset
+
+    def counting_reset(*args, **kw):
+      nonlocal solver_failures
+      if plant.planner.mpc.solution_status != 0:
+        solver_failures += 1
+      return original_reset(*args, **kw)
+
+    plant.planner.mpc.reset = counting_reset
+    for _ in range(200):
+      results.append(plant.step(v_lead=departing_lead(plant.current_time), v_cruise=15.0))
+
+    assert solver_failures <= 1
+    assert all(r["dec_mode"] == "acc" for r in results)
+    assert all(r["dec_lead_veto"] for r in results)
+
+  def test_s6_creep_cycles_behind_lead_stay_acc(self):
+    def creep_cycle_lead(current_time):
+      return 1.5 + 1.5 * np.sin(current_time * 2.0)
+
+    plant = PlantSP(lead_relevancy=True, speed=1.0, distance_lead=8.0, e2e=True, only_radar=True,
+                     model_plan_fn=flat_plan(), lead_future_probs_fn=persistent_lead_probs)
+    results = [plant.step(v_lead=creep_cycle_lead(plant.current_time), v_cruise=5.0) for _ in range(200)]
+
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s7_oscillating_near_threshold_demand_does_not_flap(self):
+    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=alternating_plan(-2.5))
+    results, _ = _run(plant, steps=200, v_cruise=20.0)
+
+    assert mode_changes(results) <= 2
+
+  def test_s8_degraded_model_holds_acc_through_a_slowdown(self):
+    def degraded_meta(_current_time):
+      return [0.0] * 5, False, 60.0
+
+    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-3.0), model_meta_fn=degraded_meta)
+    results, _ = _run(plant, steps=30, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s9_curve_exclusion_prevents_false_blend_on_a_bend(self):
+    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-1.0),
+                     position_y_fn=lambda _t: [6.0] * len(T_IDXS))
+    results, _ = _run(plant, steps=30, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "acc" for r in results)
+
+  def test_s11_curve_does_not_interrupt_an_active_hard_stop(self):
+    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-2.5),
+                     position_y_fn=lambda _t: [6.0] * len(T_IDXS))
+    results, _ = _run(plant, steps=10, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "blended" for r in results[ENTER_FRAMES - 1:])
+
+  def test_s10_hard_brake_override_inert_while_lead_present(self):
+    def hard_brake_meta(_current_time):
+      return [0.0] * 5, True, 0.0
+
+    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
+                     model_plan_fn=flat_plan(), model_meta_fn=hard_brake_meta, lead_future_probs_fn=persistent_lead_probs)
+    results, _ = _run(plant, steps=10, v_lead=20.0, v_cruise=20.0)
+
+    assert all(r["dec_mode"] == "acc" for r in results)

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/tests/test_plant_sp.py

@@ -0,0 +1,164 @@
+from collections.abc import Callable
+import math
+from typing import cast
+
+from openpilot.common.parameterized import parameterized
+from openpilot.common.realtime import DT_MDL
+from openpilot.common.test import OpenpilotTestCase
+from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
+from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP
+
+STOCK_STEP_KEYS = ("distance", "speed", "acceleration", "should_stop", "distance_lead", "fcw")
+
+
+def departing_lead(current_time: float) -> float:
+  return 0.0 if current_time < 1.0 else min(2.0, 2.0 * (current_time - 1.0))
+
+
+def stopped_lead(_current_time: float) -> float:
+  return 0.0
+
+
+PARITY_SCENARIOS = {
+  "approach_stopped_lead": {"lead_relevancy": True, "speed": 15.0, "distance_lead": 60.0, "v_cruise": 20.0, "v_lead": stopped_lead, "steps": 80},
+  "stop_then_depart": {"lead_relevancy": True, "speed": 0.0, "distance_lead": 6.0, "v_cruise": 8.0, "v_lead": departing_lead, "steps": 120},
+}
+
+
+def _drive(cls, *, v_cruise: float, v_lead: Callable[[float], float], steps: int, **kwargs):
+  plant = cls(**kwargs)
+  plant.v_lead_prev = v_lead(0.0)
+  solver_failures = 0
+  original_reset = plant.planner.mpc.reset
+
+  def counting_reset(*args, **kw):
+    nonlocal solver_failures
+    if plant.planner.mpc.solution_status != 0:
+      solver_failures += 1
+    return original_reset(*args, **kw)
+
+  plant.planner.mpc.reset = counting_reset
+  results = []
+  for _ in range(steps):
+    lead_speed = v_lead(plant.current_time)
+    result = plant.step(v_lead=lead_speed, v_cruise=v_cruise)
+    results.append((result, plant.planner.mpc.source, plant.planner.output_a_target))
+  return results, solver_failures
+
+
+class TestPlantSP(OpenpilotTestCase):
+  @parameterized.expand(PARITY_SCENARIOS, names=("scenario",), ids=lambda scenario: scenario)
+  def test_plant_sp_matches_stock_plant_on_shared_kwargs(self, scenario: str):
+    kwargs = dict(PARITY_SCENARIOS[scenario])
+    v_cruise = cast(float, kwargs.pop("v_cruise"))
+    v_lead = cast(Callable[[float], float], kwargs.pop("v_lead"))
+    steps = cast(int, kwargs.pop("steps"))
+
+    stock_results, stock_failures = _drive(Plant, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
+    sp_results, sp_failures = _drive(PlantSP, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
+
+    assert stock_failures == 0, f"stock Plant solver failed {stock_failures} times in {scenario!r}"
+    assert sp_failures == 0, f"PlantSP solver failed {sp_failures} times in {scenario!r}"
+
+    for frame, ((stock_result, stock_source, stock_a_target), (sp_result, sp_source, sp_a_target)) in enumerate(
+      zip(stock_results, sp_results, strict=True),
+    ):
+      for key in STOCK_STEP_KEYS:
+        if isinstance(stock_result[key], float):
+          self.assertAlmostEqual(sp_result[key], stock_result[key], msg=f"{scenario} frame {frame} key {key}")
+        else:
+          assert sp_result[key] == stock_result[key], f"{scenario} frame {frame} key {key}"
+      assert sp_source == stock_source, f"{scenario} frame {frame} mpc.source"
+      self.assertAlmostEqual(sp_a_target, stock_a_target, msg=f"{scenario} frame {frame} output_a_target")
+
+    if scenario == "stop_then_depart":
+      departure_frame = round(1.0 / DT_MDL)
+      for results in (stock_results, sp_results):
+        assert all(result["speed"] < 0.01 for result, _, _ in results[:departure_frame])
+        assert results[departure_frame - 1][0]["should_stop"]
+        assert any(not result["should_stop"] for result, _, _ in results[departure_frame:])
+        assert any(result["speed"] > 0.05 for result, _, _ in results[departure_frame:])
+      stock_release = next(frame for frame, (result, _, _) in enumerate(stock_results)
+                           if frame >= departure_frame and not result["should_stop"])
+      sp_release = next(frame for frame, (result, _, _) in enumerate(sp_results)
+                        if frame >= departure_frame and not result["should_stop"])
+      stock_motion = next(frame for frame, (result, _, _) in enumerate(stock_results)
+                          if frame >= departure_frame and result["speed"] > 0.05)
+      sp_motion = next(frame for frame, (result, _, _) in enumerate(sp_results)
+                       if frame >= departure_frame and result["speed"] > 0.05)
+      assert sp_release == stock_release
+      assert sp_motion == stock_motion
+
+  def test_full_lead_observation_is_independent_from_truth(self):
+    callback_inputs = []
+
+    def observe_lead(current_time, lead_name, truth):
+      callback_inputs.append((current_time, lead_name, truth))
+      if lead_name == "leadOne":
+        return {
+          "dRel": 12.5,
+          "vRel": -4.0,
+          "vLead": 6.0,
+          "vLeadK": 5.5,
+          "aLeadK": -1.25,
+          "aLeadTau": 0.7,
+          "present": True,
+          "modelProb": 0.9,
+          "radarTrackId": 42,
+        }
+      return None
+
+    plant = PlantSP(lead_relevancy=True, speed=10.0, distance_lead=50.0, lead_observation_fn=observe_lead)
+    result = plant.step(v_lead=8.0)
+
+    assert [entry[1] for entry in callback_inputs] == ["leadOne", "leadTwo"]
+    self.assertAlmostEqual(callback_inputs[0][2]["dRel"], 50.0)
+    self.assertAlmostEqual(result["truth_lead"]["dRel"], 50.0)
+    self.assertAlmostEqual(result["lead_one_observation"]["dRel"], 12.5)
+    assert result["lead_one_observation"]["radarTrackId"] == 42
+    assert result["lead_two_observation"] is None
+    self.assertAlmostEqual(result["distance_lead"], 50.0 + 8.0 * DT_MDL)
+
+  def test_model_action_realized_acceleration_and_source_logging(self):
+    def model_action(current_time, v_ego, a_ego):
+      return -1.25, True
+
+    plant = PlantSP(speed=10.0, e2e=True, force_decel=True, model_action_fn=model_action, actuator_lag=0.5)
+    first = plant.step()
+    second = plant.step()
+
+    assert first["model_action"] == {"desiredAcceleration": -1.25, "shouldStop": True}
+    self.assertAlmostEqual(first["published_a_ego"], 0.0)
+    self.assertAlmostEqual(second["published_a_ego"], first["realized_acceleration"])
+    assert first["acceleration"] == first["realized_acceleration"]
+    assert abs(first["realized_acceleration"]) < abs(first["actuator_command"])
+    assert first["mpc_source"] is not None
+    assert first["dec_mode"] in ("acc", "blended")
+    assert "controller_active" in first
+    assert first["lead_one_observation"] is not None
+    assert first["truth_lead"] == first["lead_one_observation"]
+
+  def test_default_model_action_matches_stock_plant(self):
+    result = PlantSP(speed=10.0).step()
+
+    self.assertAlmostEqual(result["model_action"]["desiredAcceleration"], 0.5)
+    assert not result["model_action"]["shouldStop"]
+
+  def test_configurable_transport_delay_and_first_order_lag(self):
+    plant = PlantSP(speed=10.0, actuator_delay=2 * DT_MDL, actuator_lag=0.2)
+
+    self.assertAlmostEqual(plant.planner.CP.longitudinalActuatorDelay, 2 * DT_MDL)
+    delayed_commands = [plant._update_actuator(-1.0) for _ in range(3)]
+    assert [command for command, _ in delayed_commands[:2]] == [0.0, 0.0]
+
+    expected_acceleration = -(1.0 - math.exp(-DT_MDL / 0.2))
+    assert delayed_commands[2][0] == -1.0
+    self.assertAlmostEqual(delayed_commands[2][1], expected_acceleration)
+
+  @parameterized.expand(
+    [(-0.1, 0.0), (float("nan"), 0.0), (float("inf"), 0.0), (None, -0.1), (None, float("nan")), (None, float("inf"))],
+    names=("delay", "lag"),
+  )
+  def test_invalid_actuator_dynamics(self, delay, lag):
+    with self.assertRaises(ValueError):
+      PlantSP(actuator_delay=delay, actuator_lag=lag)

openpilot/sunnypilot/sunnylink/settings_ui.json

@@ -652,6 +652,53 @@
                 }
               ]
             },
+            {
+              "key": "AccelPersonalityEnabled",
+              "widget": "toggle",
+              "title": "Enable Accel Controller",
+              "description": "Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are unchanged.",
+              "visibility": [
+                {
+                  "type": "capability",
+                  "field": "has_longitudinal_control",
+                  "equals": true
+                }
+              ],
+              "enablement": [
+                {
+                  "type": "capability",
+                  "field": "has_longitudinal_control",
+                  "equals": true
+                }
+              ]
+            },
+            {
+              "key": "AccelPersonality",
+              "widget": "multiple_button",
+              "title": "Acceleration Profile",
+              "description": "Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive.",
+              "options": [
+                {
+                  "value": 0,
+                  "label": "Eco"
+                },
+                {
+                  "value": 1,
+                  "label": "Normal"
+                },
+                {
+                  "value": 2,
+                  "label": "Sport"
+                }
+              ],
+              "enablement": [
+                {
+                  "type": "capability",
+                  "field": "has_longitudinal_control",
+                  "equals": true
+                }
+              ]
+            },
             {
               "key": "IntelligentCruiseButtonManagement",
               "widget": "toggle",
@@ -1605,6 +1652,18 @@
               "widget": "toggle",
               "title": "Use Metric System",
               "description": "Display speed in km/h instead of mph."
+            },
+            {
+              "key": "SunnypilotStoppingController",
+              "widget": "toggle",
+              "needs_onroad_cycle": true,
+              "title": "Stopping Controller",
+              "description": "Take over the end of a stop. The request follows the speed down to the wheel stop, then holds the car at a standstill.",
+              "enablement": [
+                {
+                  "type": "offroad_only"
+                }
+              ]
             }
           ]
         },
@@ -2302,6 +2361,61 @@
       "title": "Toyota / Lexus Settings",
       "description": "",
       "items": [
+        {
+          "key": "ToyotaAutoHold",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS",
+          "enablement": [
+            {
+              "type": "not_engaged"
+            }
+          ]
+        },
+        {
+          "key": "ToyotaBrakeOnset",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Toyota: soft brake onset, overshoot limit and regen hand-over",
+          "enablement": [
+            {
+              "type": "not_engaged"
+            }
+          ]
+        },
+        {
+          "key": "ToyotaEnhancedBsm",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Toyota: Prius TSS2 BSM and some tssp",
+          "enablement": [
+            {
+              "type": "not_engaged"
+            }
+          ]
+        },
+        {
+          "key": "ToyotaTSS2Long",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Toyota: custom longitudinal for TSS2",
+          "enablement": [
+            {
+              "type": "not_engaged"
+            }
+          ]
+        },
+        {
+          "key": "ToyotaDriveMode",
+          "widget": "toggle",
+          "needs_onroad_cycle": true,
+          "title": "Enable drive mode btn link",
+          "enablement": [
+            {
+              "type": "not_engaged"
+            }
+          ]
+        },
         {
           "key": "ToyotaEnforceStockLongitudinal",
           "widget": "toggle",

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

@@ -43,6 +43,28 @@ sections:
       label: Relaxed
     enablement:
     - $ref: '#/macros/longitudinal'
+  - key: AccelPersonalityEnabled
+    widget: toggle
+    title: Enable Accel Controller
+    description: Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are
+      unchanged.
+    visibility:
+    - $ref: '#/macros/longitudinal'
+    enablement:
+    - $ref: '#/macros/longitudinal'
+  - key: AccelPersonality
+    widget: multiple_button
+    title: Acceleration Profile
+    description: Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive.
+    options:
+    - value: 0
+      label: Eco
+    - value: 1
+      label: Normal
+    - value: 2
+      label: Sport
+    enablement:
+    - $ref: '#/macros/longitudinal'
   - key: IntelligentCruiseButtonManagement
     widget: toggle
     title: Intelligent Cruise Button Management (ICBM) (Alpha)

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

@@ -32,6 +32,14 @@ sections:
     widget: toggle
     title: Use Metric System
     description: Display speed in km/h instead of mph.
+  - key: SunnypilotStoppingController
+    widget: toggle
+    needs_onroad_cycle: true
+    title: Stopping Controller
+    description: Take over the end of a stop. The request follows the speed down to the wheel stop, then holds the car at a
+      standstill.
+    enablement:
+    - $ref: '#/macros/offroad'
 - id: recording
   title: Recording
   description: Camera and audio recording during drives

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

@@ -82,6 +82,36 @@ sections:
   title: Toyota / Lexus Settings
   description: ''
   items:
+  - key: ToyotaAutoHold
+    widget: toggle
+    needs_onroad_cycle: true
+    title: 'Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS'
+    enablement:
+    - $ref: '#/macros/not_engaged'
+  - key: ToyotaBrakeOnset
+    widget: toggle
+    needs_onroad_cycle: true
+    title: 'Toyota: soft brake onset, overshoot limit and regen hand-over'
+    enablement:
+    - $ref: '#/macros/not_engaged'
+  - key: ToyotaEnhancedBsm
+    widget: toggle
+    needs_onroad_cycle: true
+    title: 'Toyota: Prius TSS2 BSM and some tssp'
+    enablement:
+    - $ref: '#/macros/not_engaged'
+  - key: ToyotaTSS2Long
+    widget: toggle
+    needs_onroad_cycle: true
+    title: 'Toyota: custom longitudinal for TSS2'
+    enablement:
+    - $ref: '#/macros/not_engaged'
+  - key: ToyotaDriveMode
+    widget: toggle
+    needs_onroad_cycle: true
+    title: Enable drive mode btn link
+    enablement:
+    - $ref: '#/macros/not_engaged'
   - key: ToyotaEnforceStockLongitudinal
     widget: toggle
     needs_onroad_cycle: true

openpilot/sunnypilot/sunnylink/tests/test_capabilities.py

@@ -10,9 +10,10 @@ change and must be intentional. KNOWN_PROTOCOL_VERSIONS pins the set we
 explicitly support — when the constant is bumped, this list must be edited in
 the same commit so the bump shows up in code review.
 """
+
 from __future__ import annotations
 
-
+from openpilot.common.test import OpenpilotTestCase
 from openpilot.sunnypilot.sunnylink.capabilities import (
   CAPABILITY_DEFAULTS,
   CAPABILITY_FIELDS,
@@ -20,13 +21,23 @@ from openpilot.sunnypilot.sunnylink.capabilities import (
   PROTOCOL_VERSION,
   generate_capabilities,
 )
-from openpilot.common.test import OpenpilotTestCase
 
 
 KNOWN_PROTOCOL_VERSIONS = (1,)
 LATEST_KNOWN = max(KNOWN_PROTOCOL_VERSIONS)
 
 
+class FakeParams:
+  def __init__(self, values=None):
+    self.values = values or {}
+
+  def get(self, key, *args, **kwargs):
+    return self.values.get(key)
+
+  def get_bool(self, key):
+    return bool(self.values.get(key, False))
+
+
 def caps():
   return generate_capabilities()
 
@@ -52,14 +63,12 @@ class TestProtocolVersion(OpenpilotTestCase):
   def test_protocol_version_is_known(self):
     """Sentinel against accidental bumps. Edit KNOWN_PROTOCOL_VERSIONS if intentional."""
     assert PROTOCOL_VERSION in KNOWN_PROTOCOL_VERSIONS, (
-      f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. " +
-      "If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
+      f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. "
+      + "If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
     )
 
   def test_protocol_version_matches_latest_known(self):
-    assert PROTOCOL_VERSION == LATEST_KNOWN, (
-      "Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
-    )
+    assert PROTOCOL_VERSION == LATEST_KNOWN, "Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
 
 
 class TestOpaquePerBrandFlags(OpenpilotTestCase):

openpilot/sunnypilot/sunnylink/tests/test_settings_changes.py

@@ -9,6 +9,7 @@ isolates one of the gating bugs that the design-overhaul branch fixes so a
 future regression is loud and obvious. These tests are intentionally narrow
 and additive — they do not replace the broader test_settings_schema.py.
 """
+
 from __future__ import annotations
 
 import json
@@ -24,14 +25,13 @@ from openpilot.sunnypilot.sunnylink.tools.generate_settings_schema import (
   _load_torque_versions,
   generate_schema,
 )
+from openpilot.sunnypilot.sunnylink.tools.validate_settings_ui import validate as validate_settings_ui
 from openpilot.common.test import OpenpilotTestCase
 
 
-SCHEMA_VALIDATOR_PATH = os.path.join(os.path.dirname(DEFINITION_PATH), "settings_ui.schema.json")
-
-
 def _walk_items(schema: dict[str, Any]):
   """Yield every item dict from the schema."""
+
   def _yield(item: dict[str, Any]):
     yield item
     for sub in item.get("sub_items", []):
@@ -149,22 +149,13 @@ class TestTestManeuversSection(OpenpilotTestCase):
     assert "is_sp_release" in vis_refs
     enablement = section.get("enablement") or []
     enable_refs = json.dumps(enablement)
-    assert "ShowAdvancedControls" in enable_refs, \
-      "test_maneuvers must gate ShowAdvancedControls via enablement"
+    assert "ShowAdvancedControls" in enable_refs, "test_maneuvers must gate ShowAdvancedControls via enablement"
 
 
 class TestValidator(OpenpilotTestCase):
   def test_validator_accepts_real_json(self):
-    """settings_ui.json validates against settings_ui.schema.json."""
-    try:
-      import jsonschema
-    except ImportError:
-      self.skipTest("jsonschema not installed")
-    with open(DEFINITION_PATH) as f:
-      data = json.load(f)
-    with open(SCHEMA_VALIDATOR_PATH) as f:
-      validator = json.load(f)
-    jsonschema.validate(instance=data, schema=validator)
+    """settings_ui.json passes the repository's production schema validator."""
+    self.assertTrue(validate_settings_ui(DEFINITION_PATH))
 
 
 class TestTorqueOptionGeneration(OpenpilotTestCase):
@@ -177,16 +168,17 @@ class TestTorqueOptionGeneration(OpenpilotTestCase):
     assert item.get("options") == expected
 
   def test_torque_versions_path_resolves(self):
-    assert os.path.exists(TORQUE_VERSIONS_PATH), (
-      f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
-    )
+    assert os.path.exists(TORQUE_VERSIONS_PATH), f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
 
 
 class TestReleaseBranchGates(OpenpilotTestCase):
-  @parameterized.expand([
-    "EnableGithubRunner",
-    "QuickBootToggle",
-  ], names=["key"])
+  @parameterized.expand(
+    [
+      "EnableGithubRunner",
+      "QuickBootToggle",
+    ],
+    names=["key"],
+  )
   def test_sp_dev_items_gate_on_is_sp_release(self, schema, key):
     """sunnypilot dev items must hide on sunnypilot release branches (is_sp_release gate)."""
     item = _find_item(schema, key)
@@ -208,11 +200,14 @@ class TestSpuriousOffroadGatesDropped(OpenpilotTestCase):
 
 
 class TestNotEngagedReplacement(OpenpilotTestCase):
-  @parameterized.expand([
-    "AlphaLongitudinalEnabled",
-    "ToyotaEnforceStockLongitudinal",
-    "ToyotaStopAndGoHack",
-  ], names=["key"])
+  @parameterized.expand(
+    [
+      "AlphaLongitudinalEnabled",
+      "ToyotaEnforceStockLongitudinal",
+      "ToyotaStopAndGoHack",
+    ],
+    names=["key"],
+  )
   def test_offroad_only_replaced_with_not_engaged(self, schema, key):
     """These items should use not_engaged, not offroad_only."""
     item = _find_item(schema, key)
@@ -220,3 +215,5 @@ class TestNotEngagedReplacement(OpenpilotTestCase):
     rule_types = _flatten_rule_types(item.get("enablement"))
     assert "offroad_only" not in rule_types, f"{key} still uses offroad_only"
     assert "not_engaged" in rule_types, f"{key} missing not_engaged"
+
+

openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py

@@ -276,13 +276,36 @@ class TestKnownPanels(OpenpilotTestCase):
     enhanced_enable_keys = {r.get("key") for r in enhanced.get("enablement", []) if r.get("type") == "param"}
     assert "NeuralNetworkLateralControl" in enhanced_enable_keys
 
+  def test_accel_controller_profile_mapping_and_enablement(self, schema):
+    cruise = next(p for p in schema["panels"] if p["id"] == "cruise")
+    items = {item["key"]: item for item in _iter_panel_items(cruise)}
+
+    assert items["AccelPersonalityEnabled"]["widget"] == "toggle"
+    assert items["AccelPersonality"]["options"] == [
+      {"value": 0, "label": "Eco"},
+      {"value": 1, "label": "Normal"},
+      {"value": 2, "label": "Sport"},
+    ]
+    assert {
+      "type": "capability",
+      "field": "has_longitudinal_control",
+      "equals": True,
+    } in items["AccelPersonalityEnabled"]["enablement"]
+    assert {
+      "type": "capability",
+      "field": "has_longitudinal_control",
+      "equals": True,
+    } in items["AccelPersonality"]["enablement"]
+    profile_enable_keys = {rule.get("key") for rule in items["AccelPersonality"]["enablement"] if rule.get("type") == "param"}
+    assert "AccelPersonalityEnabled" not in profile_enable_keys
+
 
 class TestKnownVehicleSettings(OpenpilotTestCase):
   def test_hyundai_has_longitudinal_tuning(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("hyundai"))}
     assert "HyundaiLongitudinalTuning" in keys
 
-  def test_toyota_has_enforce_stock_and_stop_go(self, schema):
+  def test_toyota_has_enforce_stock_stop_go(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("toyota"))}
     assert "ToyotaEnforceStockLongitudinal" in keys
     assert "ToyotaStopAndGoHack" in keys

openpilot/system/manager/process_config.py

@@ -170,7 +170,6 @@ procs += [
   # Models
   PythonProcess("models_manager", "openpilot.sunnypilot.models.manager", only_offroad),
   NativeProcess("modeld_tinygrad", "openpilot/sunnypilot/modeld_v2", ["./modeld"], and_(only_onroad, is_tinygrad_model)),
-  PythonProcess("modeld_warmup", "openpilot.sunnypilot.modeld_v2.warmup", only_offroad),
 
   # Backup
   PythonProcess("backup_manager", "openpilot.sunnypilot.sunnylink.backups.manager", and_(only_offroad, sunnylink_ready_shim)),

openpilot/system/ui/lib/scroll_panel2.py

@@ -45,8 +45,9 @@ class ScrollState(Enum):
 
 
 class GuiScrollPanel2:
-  def __init__(self, horizontal: bool = True) -> None:
+  def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
     self._horizontal = horizontal
+    self._handle_out_of_bounds = handle_out_of_bounds
     self._state = ScrollState.STEADY
     self._offset: rl.Vector2 = rl.Vector2(0, 0)
     self._initial_click_event: MouseEvent | None = None
@@ -85,6 +86,20 @@ class GuiScrollPanel2:
     """Returns (max_offset, min_offset) for the given bounds and content size."""
     return 0.0, min(0.0, bounds_size - content_size)
 
+  def _clamp_offset(self, bounds_size: float, content_size: float) -> None:
+    if self._handle_out_of_bounds:
+      return
+
+    max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
+    offset = self.get_offset()
+    clamped_offset = max(min_offset, min(max_offset, offset))
+    if clamped_offset == offset:
+      return
+
+    self.set_offset(clamped_offset)
+    if (clamped_offset == max_offset and self._velocity > 0) or (clamped_offset == min_offset and self._velocity < 0):
+      self._velocity = 0.0
+
   def _update_state(self, bounds_size: float, content_size: float, snap_target: float | None) -> None:
     """Runs per render frame, independent of mouse events. Updates auto-scrolling state and velocity."""
     max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
@@ -138,6 +153,8 @@ class GuiScrollPanel2:
         factor = 1.0 - math.exp(-SNAP_RATE * dt)
         self.set_offset(self.get_offset() + dist * factor)
 
+    self._clamp_offset(bounds_size, content_size)
+
   def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
                           content_size: float) -> None:
     max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)

openpilot/system/ui/widgets/scroller.py

@@ -75,7 +75,6 @@ class _Scroller(Widget):
     self._items: list[Widget] = []
     self._horizontal = horizontal
     self._snap_items = snap_items
-    assert not self._snap_items or self._horizontal, "Snapping is only supported for horizontal scrolling"
     self._spacing = spacing
     self._pad = pad
 
@@ -191,12 +190,20 @@ class _Scroller(Widget):
     snap_target: float | None = None
     if self._snap_items and visible_items and self._scrolling_to[0] is None:
       # TODO: this doesn't handle two small buttons at the edges well
-      center_pos = self._rect.x + self._rect.width / 2
-      closest_delta_pos = min((((item.rect.x + item.rect.width / 2) - center_pos) for item in visible_items), key=abs)
+      center_pos = (self._rect.x + self._rect.width / 2) if self._horizontal else (self._rect.y + self._rect.height / 2)
+      closest_delta_pos = min(
+        (self._item_center_pos(item) - center_pos for item in visible_items),
+        key=abs,
+      )
       snap_target = self.scroll_panel.get_offset() - closest_delta_pos
 
     return self.scroll_panel.update(self._rect, content_size, snap_target=snap_target)
 
+  def _item_center_pos(self, item: Widget) -> float:
+    if self._horizontal:
+      return item.rect.x + item.rect.width / 2
+    return item.rect.y + item.rect.height / 2
+
   @property
   def moving_items(self) -> bool:
     return len(self._move_animations) > 0 or len(self._move_lift) > 0

release/ci/model_generator.py

@@ -54,10 +54,18 @@ def create_pkl_name(full_name: str) -> str:
 
 
 def _hash_pkl(pkl_path: Path) -> str:
+  manifest = Path(f"{pkl_path}.chunkmanifest")
+  if manifest.exists():
+    num_chunks = int(manifest.read_text().strip())
+    paths = [Path(f"{pkl_path}.chunk{i + 1:02d}of{num_chunks:02d}") for i in range(num_chunks)]
+  else:
+    paths = [pkl_path]
+
   digest = hashlib.sha256()
-  with pkl_path.open('rb') as f:
-    while block := f.read(1024 * 1024):
-      digest.update(block)
+  for path in paths:
+    with path.open('rb') as f:
+      while block := f.read(1024 * 1024):
+        digest.update(block)
   return digest.hexdigest()
 
 
@@ -66,9 +74,22 @@ def _find_driving_pkl(output_path: Path) -> Path | None:
     matches = sorted(output_path.glob(pattern))
     if matches:
       return matches[0]
+  for pattern in ('*driving_tinygrad.pkl.chunkmanifest', '*driving_*_tinygrad.pkl.chunkmanifest'):
+    matches = sorted(output_path.glob(pattern))
+    if matches:
+      return Path(str(matches[0]).removesuffix('.chunkmanifest'))
   return None
 
 
+def _rename_pkl_with_chunks(old_pkl: Path, new_pkl: Path) -> Path:
+  manifest = Path(f"{old_pkl}.chunkmanifest")
+  if manifest.exists():
+    for f in sorted(old_pkl.parent.glob(f"{old_pkl.name}.chunk*")):
+      f.rename(old_pkl.parent / f.name.replace(old_pkl.name, new_pkl.name, 1))
+    return new_pkl
+  return old_pkl.rename(new_pkl)
+
+
 def _hash_onnx_files(model_dir: Path) -> str | None:
   onnx_files = [f for f in sorted(model_dir.glob("*.onnx")) if f.stat().st_size > 1024]
   if not onnx_files:
@@ -81,9 +102,22 @@ def _hash_onnx_files(model_dir: Path) -> str | None:
   return digest.hexdigest()
 
 
-def generate_model(driving_pkl: Path) -> dict:
+def generate_chunked_model(driving_pkl: Path) -> dict:
   tinygrad_hash = _hash_pkl(driving_pkl)
 
+  chunks_config = []
+  manifest_file = Path(f"{driving_pkl}.chunkmanifest")
+  if manifest_file.exists():
+    num_chunks = int(manifest_file.read_text().strip())
+    for i in range(num_chunks):
+      chunk_path = Path(f"{driving_pkl}.chunk{i + 1:02d}of{num_chunks:02d}")
+      if chunk_path.exists():
+        chunk_hash = hashlib.sha256(chunk_path.read_bytes()).hexdigest()
+        chunks_config.append({
+          "file_name": chunk_path.name,
+          "sha256": chunk_hash
+        })
+
   artifact_data = {
     "file_name": driving_pkl.name,
     "download_uri": {
@@ -92,6 +126,9 @@ def generate_model(driving_pkl: Path) -> dict:
     }
   }
 
+  if chunks_config:
+    artifact_data["chunks"] = chunks_config
+
   return {
     "type": "chunked",
     "artifact": artifact_data,
@@ -156,11 +193,11 @@ if __name__ == "__main__":
   if _pkl:
     new_pkl = _output_dir / f"driving_{_pkl}_tinygrad.pkl"
     if not new_pkl.exists():
-      _driving_pkl = _driving_pkl.rename(new_pkl)
+      _driving_pkl = _rename_pkl_with_chunks(_driving_pkl, new_pkl)
     else:
       _driving_pkl = new_pkl
 
-  _model_metadata = generate_model(_driving_pkl)
+  _model_metadata = generate_chunked_model(_driving_pkl)
   _onnx_sha256 = args.onnx_sha256 or _hash_onnx_files(Path(args.model_dir))
   create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch,
                        onnx_sha256=_onnx_sha256, is_big=is_big)

release/ci/upload_default_model.py

@@ -79,6 +79,8 @@ def main():
   artifact = bundle['models'][0]['artifact']
   hf_base = f"https://huggingface.co/datasets/{args.hf_repo}/resolve/main/{args.hf_defaults_path}/{folder_name}"
   artifact['download_uri']['url'] = f"{hf_base}/{artifact['file_name']}"
+  for chunk in artifact.get('chunks', []):
+    chunk['url'] = f"{hf_base}/{chunk['file_name']}"
 
   print(f"Uploading model to {args.hf_defaults_path}/{folder_name}/")
   api.upload_folder(