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2 Commits

Author SHA1 Message Date
Jason Wen 43d0302e7b nah 2026-10-10 15:09:23 -04:00
Jason Wen 20bb311770 controls: decouple RELC from BSM blocking, allow nudge override 2026-10-10 15:02:45 -04:00
37 changed files with 882 additions and 368 deletions
+3 -34
View File
@@ -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 [ "${{ inputs.target }}" = "dm" ]; then
ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
HF_DEFAULTS_PATH="models/defaults/dm"
@@ -186,6 +185,7 @@ jobs:
- uses: actions/checkout@v4
with:
submodules: recursive
lfs: true
- name: Pull big PKL via LFS
run: git lfs pull -I "${{ env.BIG_PKL }}"
@@ -235,34 +235,6 @@ jobs:
print(f'Chunked into {len(targets)} files')
"
- name: Compile big warp
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
- name: Prepare output
env:
MODEL_NAME: ${{ needs.resolve.outputs.safe_model_name }}
@@ -277,7 +249,7 @@ jobs:
cp "$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" \
@@ -286,8 +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 }}" > "$OUTPUT_DIR/artifact_name.txt"
- name: Upload big model artifact
@@ -365,8 +335,6 @@ jobs:
--hf-defaults-path "${{ 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 }}"
@@ -546,3 +514,4 @@ jobs:
run: |
source ${UV_PROJECT_ENVIRONMENT}/bin/activate
PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
@@ -71,11 +71,6 @@ runs:
ENCODED_URL=$(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
}
+2 -5
View File
@@ -196,6 +196,7 @@ struct ModelManagerSP @0xaedffd8f31e7b55d {
}
struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
dec @0 :DynamicExperimentalControl;
longitudinalPlanSource @1 :LongitudinalPlanSource;
smartCruiseControl @2 :SmartCruiseControl;
speedLimit @3 :SpeedLimit;
@@ -204,11 +205,7 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
events @6 :List(OnroadEventSP.Event);
e2eAlerts @7 :E2eAlerts;
deprecated :group {
dec @0 :DynamicExperimentalControlDEPRECATED;
}
struct DynamicExperimentalControlDEPRECATED {
struct DynamicExperimentalControl {
state @0 :DynamicExperimentalControlState;
enabled @1 :Bool;
active @2 :Bool;
+1 -1
View File
@@ -240,6 +240,7 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"ToyotaEnforceStockLongitudinal", {PERSISTENT | BACKUP, BOOL, "0"}},
{"ToyotaStopAndGoHack", {PERSISTENT | BACKUP, BOOL, "0"}},
{"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
{"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
// sunnypilot model params
@@ -249,7 +250,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
{"LagdValueCache", {PERSISTENT, FLOAT, "0.2"}},
{"LaneTurnDesire", {PERSISTENT | BACKUP, BOOL, "0"}},
{"LaneTurnValue", {PERSISTENT | BACKUP, FLOAT, "19.0"}},
{"LanefulStrength", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
{"PlanplusControl", {PERSISTENT | BACKUP, FLOAT, "1.0"}},
// mapd
+5 -1
View File
@@ -127,6 +127,9 @@ class Car:
set_alternative_experience(self.CP, self.CP_SP, self.params)
set_car_specific_params(self.CP, self.CP_SP, self.params)
# Dynamic Experimental Control
self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
openpilot_enabled_toggle = self.params.get_bool("OpenpilotEnabledToggle")
controller_available = self.CI.CC is not None and openpilot_enabled_toggle and not self.CP.dashcamOnly
self.CP.passive = not controller_available or self.CP.dashcamOnly
@@ -211,7 +214,7 @@ class Car:
self.v_cruise_helper.update_v_cruise(CS, self.sm['carControl'].enabled, self.is_metric)
if self.sm['carControl'].enabled and not self.CC_prev.enabled:
# Use CarState w/ buttons from the step selfdrived enables on
self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.experimental_mode)
self.v_cruise_helper.initialize_v_cruise(self.CS_prev, self.experimental_mode, self.dynamic_experimental_control)
# TODO: mirror the carState.cruiseState struct?
CS.vCruise = float(self.v_cruise_helper.v_cruise_kph)
@@ -299,6 +302,7 @@ class Car:
self.experimental_mode = self.params.get_bool("ExperimentalMode") and self.CP.openpilotLongitudinalControl
# sunnypilot
self.dynamic_experimental_control = self.params.get_bool("DynamicExperimentalControl")
self.v_cruise_helper.read_custom_set_speed_params()
time.sleep(0.1)
+3 -2
View File
@@ -138,12 +138,13 @@ class VCruiseHelper(VCruiseHelperSP):
self.button_timers[b.type.raw] = 1 if b.pressed else 0
self.button_change_states[b.type.raw] = {"standstill": CS.cruiseState.standstill, "enabled": enabled}
def initialize_v_cruise(self, CS, experimental_mode: bool) -> None:
def initialize_v_cruise(self, CS, experimental_mode: bool, dynamic_experimental_control: bool) -> None:
# initializing is handled by the PCM
if self.CP.pcmCruise:
return
initial = V_CRUISE_INITIAL_EXPERIMENTAL_MODE if experimental_mode else V_CRUISE_INITIAL
initial_experimental_mode = experimental_mode and not dynamic_experimental_control
initial = V_CRUISE_INITIAL_EXPERIMENTAL_MODE if initial_experimental_mode else V_CRUISE_INITIAL
if any(b.type in (ButtonType.accelCruise, ButtonType.resumeCruise) for b in CS.buttonEvents) and self.v_cruise_initialized:
self.v_cruise_kph = self.v_cruise_kph_last
@@ -59,16 +59,16 @@ class TestVCruiseHelper(OpenpilotTestCase):
for _ in range(2):
self.v_cruise_helper.update_v_cruise(car.CarState(cruiseState={"available": False}), enabled=False, is_metric=False)
def enable(self, v_ego, experimental_mode):
def enable(self, v_ego, experimental_mode, dynamic_experimental_control):
# Simulates user pressing set with a current speed
self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), experimental_mode)
self.v_cruise_helper.initialize_v_cruise(car.CarState(vEgo=v_ego), experimental_mode, dynamic_experimental_control)
def test_adjust_speed(self):
"""
Asserts speed changes on falling edges of buttons.
"""
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
for btn in (ButtonType.accelCruise, ButtonType.decelCruise):
for pressed in (True, False):
@@ -92,7 +92,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
CS.buttonEvents = [ButtonEvent(type=ButtonType.decelCruise, pressed=pressed)]
self.v_cruise_helper.update_v_cruise(CS, enabled=enabled, is_metric=False)
if pressed:
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
# Expected diff on enabling. Speed should not change on falling edge of pressed
assert (not pressed) == (self.v_cruise_helper.v_cruise_kph == self.v_cruise_helper.v_cruise_kph_last)
@@ -102,7 +102,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
Asserts we don't increment set speed if user presses resume/accel to exit cruise standstill.
"""
self.enable(0, False)
self.enable(0, False, False)
for standstill in (True, False):
for pressed in (True, False):
@@ -122,7 +122,7 @@ class TestVCruiseHelper(OpenpilotTestCase):
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
# first decrement speed, then perform gas pressed logic
expected_v_cruise_kph = self.v_cruise_helper.v_cruise_kph - IMPERIAL_INCREMENT
@@ -144,10 +144,11 @@ class TestVCruiseHelper(OpenpilotTestCase):
"""
for experimental_mode in (True, False):
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
assert not self.v_cruise_helper.v_cruise_initialized
for dynamic_experimental_control in (True, False):
for v_ego in np.linspace(0, 100, 101):
self.reset_cruise_speed_state()
assert not self.v_cruise_helper.v_cruise_initialized
self.enable(float(v_ego), experimental_mode)
assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
assert self.v_cruise_helper.v_cruise_initialized
self.enable(float(v_ego), experimental_mode, dynamic_experimental_control)
assert V_CRUISE_INITIAL <= self.v_cruise_helper.v_cruise_kph <= V_CRUISE_MAX
assert self.v_cruise_helper.v_cruise_initialized
@@ -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
@@ -138,16 +138,16 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
output_should_stop_e2e = sm['modelV2'].action.shouldStop
experimental_mode = sm['selfdriveState'].experimentalMode
is_e2e = self.is_e2e(sm)
self.a_cruise = get_cruise_accel(experimental_mode, v_cruise, v_ego,
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)
cruise_should_stop = should_stop(v_ego, self.a_cruise)
candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
(self.a_cruise, LongitudinalPlanSource.cruise, cruise_should_stop)]
if experimental_mode:
if is_e2e:
candidates.append((output_a_target_e2e, LongitudinalPlanSource.e2e, output_should_stop_e2e))
output_a_target, self.mpc.source, _ = min(candidates, key=lambda c: c[0])
+1 -1
View File
@@ -577,7 +577,7 @@ class SelfdriveD(CruiseHelper):
clear_event_types = set()
if ET.WARNING not in self.state_machine.current_alert_types:
clear_event_types.add(ET.WARNING)
if self.enabled or (ET.NO_ENTRY not in (c := self.state_machine.current_alert_types) and (ET.ENABLE in c or ET.USER_DISABLE in c)):
if self.enabled:
clear_event_types.add(ET.NO_ENTRY)
pers = LONGITUDINAL_PERSONALITY_MAP[self.personality]
@@ -181,8 +181,6 @@ class AugmentedRoadView(CameraView):
def _handle_mouse_release(self, mouse_pos: MousePos):
# Don't trigger click callback if bookmark was triggered
if not self._bookmark_icon.interacting():
if self._model_renderer.laneful.handle_tap(mouse_pos):
return
super()._handle_mouse_release(mouse_pos)
def _render(self, _):
@@ -153,7 +153,6 @@ class ModelRenderer(Widget, ModelRendererSP):
if ui_state.status != UIStatus.DISENGAGED:
self._draw_lane_lines()
self._draw_path(sm)
self.laneful.draw(self._rect)
# if render_lead_indicator and radar_state:
# self._draw_lead_indicator()
@@ -205,7 +204,6 @@ class ModelRenderer(Widget, ModelRendererSP):
# Update road edges using raw points
for road_edge in self._road_edges:
road_edge.projected_points = self._map_line_to_polygon(road_edge.raw_points, line_width_factor, 0.0, max_idx)
self.laneful.update(self, max_idx)
# Update path using raw points
if lead and lead.present:
@@ -82,8 +82,14 @@ class CruiseLayout(Widget):
callback=lambda: self._set_current_panel(PanelType.SLA)
)
self.dec_toggle = toggle_item_sp(
title=tr("Enable Dynamic Experimental Control"),
description=tr("Enable toggle to allow the model to determine when to use sunnypilot ACC or sunnypilot End to End Longitudinal."),
param="DynamicExperimentalControl")
items = [
self.icbm_toggle,
self.dec_toggle,
self.scc_v_toggle,
self.scc_m_toggle,
self.custom_acc_toggle,
@@ -138,13 +144,16 @@ class CruiseLayout(Widget):
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())
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)
else:
ui_state.params.remove("CustomAccIncrementsEnabled")
ui_state.params.remove("DynamicExperimentalControl")
ui_state.params.remove("SmartCruiseControlVision")
ui_state.params.remove("SmartCruiseControlMap")
self.custom_acc_toggle.action_item.set_enabled(False)
self.dec_toggle.action_item.set_enabled(False)
self.scc_v_toggle.action_item.set_enabled(False)
self.scc_m_toggle.action_item.set_enabled(False)
@@ -1,39 +0,0 @@
"""
Copyright (c) 2021-, 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.widgets.button import BigMultiToggle
from openpilot.selfdrive.ui.ui_state import ui_state
from openpilot.system.ui.widgets.scroller import NavScroller
# above 1.0 the pull overshoots lane center and ping-pongs
STRENGTHS = {"off": 0.0, "gentle": 0.5, "firm": 1.0}
class LanefulStrengthToggle(BigMultiToggle):
"""Tap to cycle LanefulStrength, like the driving personality toggle."""
def __init__(self):
super().__init__("laneful strength", list(STRENGTHS), select_callback=self._on_select,
description="Nudges the car toward lane center.\n" +
"Firm centers faster than gentle.")
self.refresh()
def refresh(self):
strength = ui_state.params.get("LanefulStrength", return_default=True)
self.set_value(min(STRENGTHS, key=lambda k: abs(STRENGTHS[k] - strength)))
def _on_select(self, value: str):
ui_state.params.put("LanefulStrength", STRENGTHS[value])
class LanefulLayoutMici(NavScroller):
def __init__(self):
super().__init__()
self._strength = LanefulStrengthToggle()
self._scroller.add_widget(self._strength)
def show_event(self):
super().show_event()
self._strength.refresh()
@@ -11,7 +11,6 @@ from openpilot.selfdrive.ui.mici.widgets.button import BigCircleButton
from openpilot.selfdrive.ui.mici.widgets.dialog import BigConfirmationDialog, BigDialog
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.sunnylink import SunnylinkLayoutMici
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.models import ModelsLayoutMici
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.laneful import LanefulLayoutMici
from openpilot.selfdrive.ui.ui_state import ui_state
from openpilot.system.ui.lib.application import gui_app, FontWeight
from openpilot.system.ui.lib.multilang import tr
@@ -51,10 +50,6 @@ class SettingsLayoutSP(OP.SettingsLayout):
models_btn = SettingsBigButton(tr("models"), "", gui_app.texture("../../sunnypilot/selfdrive/assets/offroad/icon_models.png", ICON_SIZE, ICON_SIZE))
models_btn.set_click_callback(lambda: gui_app.push_widget(models_panel))
laneful_panel = LanefulLayoutMici()
laneful_btn = SettingsBigButton(tr("laneful"), "", gui_app.texture("icons_mici/settings/device/lkas.png", ICON_SIZE, ICON_SIZE))
laneful_btn.set_click_callback(lambda: gui_app.push_widget(laneful_panel))
# onroad: enable button sits at the front (left of toggles)
self._enable_offroad_btn_onroad = BigCircleButton(self.icon_offroad_enable, red=True)
self._enable_offroad_btn_onroad.set_click_callback(lambda: self._handle_always_offroad(True))
@@ -72,8 +67,7 @@ class SettingsLayoutSP(OP.SettingsLayout):
items = self._scroller._items.copy()
items.insert(1, models_btn)
items.insert(2, laneful_btn)
items.insert(6, sunnylink_btn)
items.insert(5, sunnylink_btn)
# front slots (only one ever visible at a time): exit-always-offroad, then enable-onroad
items.insert(0, self._enable_offroad_btn_onroad)
@@ -8,24 +8,17 @@ import pyray as rl
from openpilot.selfdrive.ui.mici.onroad.hud_renderer import HudRenderer
from openpilot.selfdrive.ui.sunnypilot.onroad.blind_spot_indicators import BlindSpotIndicators
from openpilot.selfdrive.ui.ui_state import ui_state
class HudRendererSP(HudRenderer):
def __init__(self):
super().__init__()
self.blind_spot_indicators = BlindSpotIndicators()
self._sp_engaged: bool = False
def _update_state(self) -> None:
super()._update_state()
self.blind_spot_indicators.update()
sp_engaged = ui_state.engaged
if sp_engaged != self._sp_engaged:
self._chestnut_fade_time = rl.get_time() if sp_engaged else 0
self._sp_engaged = sp_engaged
def _render(self, rect: rl.Rectangle) -> None:
super()._render(rect)
self.blind_spot_indicators.render(rect)
@@ -1,122 +0,0 @@
"""
Copyright (c) 2021-, 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.
Laneful visuals: cyan lane-center target, thin white "after" path (model path bent by laneful's nudge),
and a top-center readout of the pull. Mirrors the math in sunnypilot/modeld_v2/laneful.py.
"""
import numpy as np
import pyray as rl
from openpilot.common.filter_simple import FirstOrderFilter
from openpilot.common.realtime import DT_MDL
from openpilot.selfdrive.ui.ui_state import ui_state
from openpilot.system.ui.lib.application import gui_app, FontWeight
from openpilot.system.ui.lib.shader_polygon import draw_polygon
from openpilot.system.ui.lib.text_measure import measure_text_cached
CENTER_COLOR = (0, 200, 255)
AFTER_COLOR = (255, 255, 255)
# keep in sync with sunnypilot/modeld_v2/laneful.py
LOOKAHEAD_TIME = 1.5
MIN_LOOKAHEAD = 10.0
MAX_ERROR = 0.5
class LanefulRenderer:
def __init__(self):
self._center_points = np.empty((0, 2), dtype=np.float32)
self._after_points = np.empty((0, 2), dtype=np.float32)
self._trust = 0.0
self._strength = 0.0
self._frame = 0
self._font = gui_app.font(FontWeight.BOLD)
# smoothed copies for the readout so the numbers don't flicker
self._pull_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
self._trust_display = FirstOrderFilter(0.0, 0.5, DT_MDL)
self._readout_rect: rl.Rectangle | None = None
self._settings_page = None
def update(self, renderer, max_idx: int) -> None:
"""Called from the model renderer's update with its lane lines and path already in raw points."""
if self._frame % 60 == 0:
self._strength = ui_state.params.get("LanefulStrength", return_default=True)
self._frame += 1
left, right = renderer._lane_lines[1].raw_points, renderer._lane_lines[2].raw_points
stds = list(ui_state.sm['modelV2'].laneLineStds)
if self._strength <= 0.0 or len(left) == 0 or len(right) != len(left) or len(stds) < 3:
self._center_points = np.empty((0, 2), dtype=np.float32)
self._after_points = np.empty((0, 2), dtype=np.float32)
return
probs = renderer._lane_line_probs
l_prob = float(probs[1] * np.interp(stds[1], [0.15, 0.3], [1.0, 0.0]))
r_prob = float(probs[2] * np.interp(stds[2], [0.15, 0.3], [1.0, 0.0]))
width = np.clip(right[:, 1] - left[:, 1], 2.8, 4.5) if l_prob * r_prob > 0.5 else 3.7
center = left.copy()
center[:, 1] = (l_prob * (left[:, 1] + width / 2) + r_prob * (right[:, 1] - width / 2)) / (l_prob + r_prob + 1e-4)
self._trust = l_prob + r_prob - l_prob * r_prob
self._center_points = renderer._map_line_to_polygon(center, 0.1, 0.0, max_idx)
# "after" path: model path bent toward center the way laneful's pure-pursuit term steers, ending at the lookahead
path = renderer._path.raw_points
lookahead = max(ui_state.sm['carState'].vEgo * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
error = float(np.clip(np.interp(lookahead, center[:, 0], center[:, 1]) - np.interp(lookahead, path[:, 0], path[:, 1]),
-MAX_ERROR, MAX_ERROR))
self._pull_display.update(self._trust * error) # what laneful actually pulls, 0 when lines are untrusted
self._trust_display.update(self._trust)
after = path.copy()
after[:, 1] += self._strength * self._trust * error * (path[:, 0] / lookahead) ** 2
self._after_points = renderer._map_line_to_polygon(after, 0.15, renderer._path_offset_z,
renderer._get_path_length_idx(path[:, 0], lookahead))
def draw(self, rect: rl.Rectangle) -> None:
if self._center_points.size and self._trust > 0.05:
draw_polygon(rect, self._center_points, rl.Color(*CENTER_COLOR, int(np.clip(self._trust, 0.2, 1.0) * 255)))
if self._after_points.size:
draw_polygon(rect, self._after_points, rl.Color(*AFTER_COLOR, 200))
self._readout_rect = None
if self._strength > 0.0:
self._draw_readout(rect)
def handle_tap(self, pos) -> bool:
"""Tapping the readout opens the laneful settings page. Returns True if the tap was consumed."""
r = self._readout_rect
if r is None or not (r.x - 20 <= pos.x <= r.x + r.width + 20 and r.y - 20 <= pos.y <= r.y + r.height + 20):
return False
if self._settings_page is None:
from openpilot.selfdrive.ui.sunnypilot.mici.layouts.laneful import LanefulLayoutMici
self._settings_page = LanefulLayoutMici()
gui_app.push_widget(self._settings_page)
return True
def _draw_readout(self, rect: rl.Rectangle) -> None:
"""Top-center pill: pull toward lane center in cm (capped at 50), arrow = side,
bar grows from center toward the pull (full at the cap), brighter with more lane line trust."""
pull, trust = self._pull_display.x, self._trust_display.x
w, h = 190, 76
x, y = rect.x + (rect.width - w) / 2, rect.y + 10
cx, cy = x + w / 2, y + 30
self._readout_rect = rl.Rectangle(x, y, w, h)
rl.draw_rectangle_rounded(self._readout_rect, 0.5, 12, rl.Color(0, 0, 0, 170))
text = f"{abs(pull) * 100:.0f}"
text_w = measure_text_cached(self._font, text, 44, 0).x
rl.draw_text_ex(self._font, text, rl.Vector2(cx - text_w / 2, cy - 24), 44, 0, rl.WHITE)
active = rl.Color(*CENTER_COLOR, int(np.clip(abs(pull) / 0.1, 0.0, 1.0) * 255))
idle = rl.Color(255, 255, 255, 40)
lx, rx = x + 18, x + w - 18
rl.draw_triangle(rl.Vector2(lx, cy), rl.Vector2(lx + 16, cy + 12), rl.Vector2(lx + 16, cy - 12), active if pull < 0 else idle)
rl.draw_triangle(rl.Vector2(rx - 16, cy - 12), rl.Vector2(rx - 16, cy + 12), rl.Vector2(rx, cy), active if pull > 0 else idle)
bar = rl.Rectangle(x + 24, y + h - 16, w - 48, 6)
rl.draw_rectangle_rounded(bar, 1.0, 6, rl.Color(255, 255, 255, 40))
rl.draw_rectangle(int(cx - 1), int(bar.y - 2), 2, int(bar.height + 4), rl.Color(255, 255, 255, 120))
fill = bar.width / 2 * float(np.clip(abs(pull) / MAX_ERROR, 0.0, 1.0))
if fill > 1:
fill_x = cx if pull > 0 else cx - fill
rl.draw_rectangle_rounded(rl.Rectangle(fill_x, bar.y, fill, bar.height), 1.0, 6,
rl.Color(*CENTER_COLOR, int(np.clip(0.3 + 0.7 * trust, 0.0, 1.0) * 255)))
@@ -6,7 +6,6 @@ See the LICENSE.md file in the root directory for more details.
"""
import pyray as rl
from openpilot.selfdrive.ui.ui_state import UIStatus
from openpilot.selfdrive.ui.sunnypilot.mici.onroad.laneful import LanefulRenderer
from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath
LANE_LINE_COLORS_SP = {
@@ -18,4 +17,3 @@ LANE_LINE_COLORS_SP = {
class ModelRendererSP:
def __init__(self):
self.rainbow_path = RainbowPath()
self.laneful = LanefulRenderer()
@@ -221,9 +221,10 @@ class UIStateSP:
self.params.remove("LateralJerkTorqueController")
self.params.remove("AlphaLongitudinalEnabled")
# No longitudinal control: no experimental mode
# No longitudinal control: no experimental mode or DEC
if not has_long:
self.params.remove("ExperimentalMode")
self.params.remove("DynamicExperimentalControl")
# ICBM: clear if not available or if full longitudinal control is active
if self.CP_SP is not None:
-79
View File
@@ -1,79 +0,0 @@
"""
Copyright (c) 2021-, 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.
Laneful: nudge the model's curvature toward the lane center seen by the lane lines.
The model stays in charge; this only adds a pure-pursuit correction weighted by lane line confidence,
and fades to zero (plain laneless) when the lines are weak.
"""
import numpy as np
from openpilot.common.filter_simple import FirstOrderFilter
from openpilot.common.realtime import DT_MDL
from openpilot.sunnypilot.modeld_v2.constants import ModelConstants, Plan
LANE_WIDTH_DEFAULT = 3.7 # m
LANE_WIDTH_CLIP = (2.8, 4.5) # m
LOOKAHEAD_TIME = 1.5 # s
MIN_LOOKAHEAD = 10.0 # m
MAX_ERROR = 0.5 # m, cap on how far laneful can pull
MIN_SPEED = 9.0 # m/s
class Laneful:
def __init__(self):
self.lane_width = FirstOrderFilter(LANE_WIDTH_DEFAULT, 10.0, DT_MDL)
def update(self, model_output: dict[str, np.ndarray], v_ego: float, strength: float, desire_active: bool) -> float:
"""Returns a curvature offset to add to the model's raw desired curvature."""
if strength <= 0.0 or desire_active or v_ego < MIN_SPEED or 'lane_lines' not in model_output:
return 0.0
lookahead = max(v_ego * LOOKAHEAD_TIME, MIN_LOOKAHEAD)
lines = model_output['lane_lines'][0, :, :, 0]
left_y = np.interp(lookahead, ModelConstants.X_IDXS, lines[1])
right_y = np.interp(lookahead, ModelConstants.X_IDXS, lines[2])
# line confidence, discounted when the model is unsure where the line is
probs = model_output['lane_lines_prob'][0, 1::2]
stds = model_output['lane_lines_stds'][0, :, 0, 0]
l_prob = float(probs[1] * np.interp(stds[1], [0.15, 0.3], [1.0, 0.0]))
r_prob = float(probs[2] * np.interp(stds[2], [0.15, 0.3], [1.0, 0.0]))
if l_prob * r_prob > 0.5:
self.lane_width.update(float(np.clip(right_y - left_y, *LANE_WIDTH_CLIP)))
half_width = self.lane_width.x / 2
# one weak line -> hug the strong one at half a lane width
center_y = (l_prob * (left_y + half_width) + r_prob * (right_y - half_width)) / (l_prob + r_prob + 1e-4)
lane_trust = l_prob + r_prob - l_prob * r_prob
plan = model_output['plan'][0, :, Plan.POSITION]
plan_y = np.interp(lookahead, plan[:, 0], plan[:, 1])
error = np.clip(center_y - plan_y, -MAX_ERROR, MAX_ERROR)
return float(strength * lane_trust * 2.0 * error / lookahead ** 2)
if __name__ == "__main__":
def fake_output(left_y, right_y, prob=0.9, std=0.1, plan_y=0.0):
x = np.array(ModelConstants.X_IDXS)
lines = np.zeros((1, 4, len(x), 2), dtype=np.float32)
lines[0, 1, :, 0], lines[0, 2, :, 0] = left_y, right_y
plan = np.zeros((1, len(x), 15), dtype=np.float32)
plan[0, :, 0], plan[0, :, 1] = x, plan_y
return {'lane_lines': lines, 'plan': plan,
'lane_lines_prob': np.full((1, 8), prob, dtype=np.float32),
'lane_lines_stds': np.full((1, 4, len(x), 2), std, dtype=np.float32)}
lf = Laneful()
assert abs(lf.update(fake_output(-1.85, 1.85), 25.0, 1.0, False)) < 1e-6, "centered -> no nudge"
assert lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, False) > 0, "lane center to the +y side -> nudge toward +y"
assert lf.update(fake_output(-2.7, 1.0), 25.0, 1.0, False) < 0, "lane center to the -y side -> nudge toward -y"
assert lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, True) == 0.0, "off during lane change/turn"
assert lf.update(fake_output(-1.0, 2.7, std=0.5), 25.0, 1.0, False) == 0.0, "blurry lines -> laneless"
assert lf.update(fake_output(-1.0, 2.7), 25.0, 0.0, False) == 0.0, "strength 0 -> off"
assert lf.update(fake_output(-1.0, 2.7), 25.0, 0.5, False) < lf.update(fake_output(-1.0, 2.7), 25.0, 1.0, False)
print("laneful self-check ok")
+2 -10
View File
@@ -37,7 +37,6 @@ from openpilot.selfdrive.modeld.modeld import ChestnutGpuState
from openpilot.sunnypilot.modeld_v2.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState, get_curvature_from_output
from openpilot.sunnypilot.modeld_v2.parse_model_outputs import Parser
from openpilot.sunnypilot.modeld_v2.laneful import Laneful
from openpilot.sunnypilot.modeld_v2.constants import ModelConstants, Plan
from openpilot.sunnypilot.modeld_v2.meta_helper import load_meta_constants
from openpilot.sunnypilot.modeld_v2.camera_offset_helper import CameraOffsetHelper
@@ -225,8 +224,7 @@ class ModelState(ModelStateBase):
return outputs
def get_action_from_model(self, model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
lat_action_t: float, long_action_t: float, v_ego: float,
laneful_curvature: float = 0.0) -> log.ModelDataV2.Action:
lat_action_t: float, long_action_t: float, v_ego: float) -> log.ModelDataV2.Action:
if 'action' not in model_output:
plan = model_output['plan'][0]
desired_accel = get_accel_from_plan(plan[:, Plan.VELOCITY][:, 0], plan[:, Plan.ACCELERATION][:, 0], self.constants.T_IDXS,
@@ -238,7 +236,6 @@ class ModelState(ModelStateBase):
else:
desired_accel = model_output['action'][0, 1]
desired_curvature = model_output['action'][0, 0] / (max(1.0, v_ego))**2
desired_curvature += laneful_curvature
stop = v_ego < 0.3 and desired_accel < 0.1
desired_accel = smooth_value(desired_accel, prev_action.desiredAcceleration, self.LONG_SMOOTH_SECONDS)
@@ -353,8 +350,6 @@ def main(demo=False):
DH = DesireHelper()
meta_constants = load_meta_constants()
RELC = RoadEdgeLaneChangeController()
laneful = Laneful()
laneful_strength = 0.0
while True:
# Keep receiving frames until we are at least 1 frame ahead of previous extra frame
@@ -398,7 +393,6 @@ def main(demo=False):
model.lat_delay = get_lat_delay(params, sm["lateralDelay"].lateralDelay)
model.PLANPLUS_CONTROL = params.get("PlanplusControl", return_default=True)
camera_offset_helper.set_offset(params.get("CameraOffset", return_default=True))
laneful_strength = params.get("LanefulStrength", return_default=True)
lat_delay = model.lat_delay + model.LAT_SMOOTH_SECONDS
if sm.updated["extrinsicsCalibration"] and sm.seen['narrowRoadCameraState'] and sm.seen['deviceState']:
device_from_calib_euler = np.array(sm["extrinsicsCalibration"].rpyCalib, dtype=np.float32)
@@ -470,9 +464,7 @@ def main(demo=False):
posenet_send = messaging.new_message('cameraOdometry')
mdv2sp_send = messaging.new_message('modelDataV2SP')
laneful_curvature = laneful.update(model_output, v_ego, laneful_strength,
desire != log.Desire.none or DH.lane_change_state != log.LaneChangeState.off)
action = model.get_action_from_model(model_output, prev_action, lat_action_t, long_action_t, v_ego, laneful_curvature)
action = model.get_action_from_model(model_output, prev_action, lat_action_t, long_action_t, v_ego)
prev_action = action
fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
@@ -81,6 +81,7 @@ def _cleanup_unsupported_params(CP: structs.CarParams, CP_SP: structs.CarParamsS
if not CP.openpilotLongitudinalControl and CP_SP.pcmCruiseSpeed:
cloudlog.warning("openpilot Longitudinal Control and ICBM not available, cleaning up params")
params.remove("DynamicExperimentalControl")
params.remove("CustomAccIncrementsEnabled")
params.remove("SmartCruiseControlVision")
params.remove("SmartCruiseControlMap")
@@ -57,7 +57,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
def test_default_behavior_when_disabled(self):
"""Test that default increments are used when custom ACC is disabled"""
self.set_custom_increments(enabled=False, short_inc=5, long_inc=10)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False)
self.enable(V_CRUISE_INITIAL * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
@@ -69,7 +69,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
def test_custom_short_press_increments(self, increment):
"""Test custom short press increments (1-10)"""
self.set_custom_increments(enabled=True, short_inc=increment, long_inc=5)
self.enable(50 * CV.KPH_TO_MS, False)
self.enable(50 * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_short(ButtonType.accelCruise)
@@ -86,7 +86,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
def test_custom_long_press_increments(self, increment):
"""Test custom long press increments (1, 5, 10)"""
self.set_custom_increments(enabled=True, short_inc=1, long_inc=increment)
self.enable(50 * CV.KPH_TO_MS, False)
self.enable(50 * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_long(ButtonType.accelCruise)
@@ -103,7 +103,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
def test_accel_decel_symmetry(self, button_type):
"""Test that acceleration and deceleration work symmetrically"""
self.set_custom_increments(enabled=True, short_inc=3, long_inc=5)
self.enable(50 * CV.KPH_TO_MS, False)
self.enable(50 * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_short(button_type)
@@ -123,7 +123,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
for initial, increment, expected in test_cases:
self.set_custom_increments(enabled=True, short_inc=increment, long_inc=increment)
self.reset_cruise_speed_state()
self.enable(initial * CV.KPH_TO_MS, False)
self.enable(initial * CV.KPH_TO_MS, False, False)
self.press_button_short(ButtonType.accelCruise)
assert self.v_cruise_helper.v_cruise_kph == expected
@@ -132,7 +132,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
"""Test that invalid values fallback to safe defaults"""
# Test invalid short increment
self.set_custom_increments(enabled=True, short_inc=-1, long_inc=5)
self.enable(50 * CV.KPH_TO_MS, False)
self.enable(50 * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_short(ButtonType.accelCruise)
@@ -141,7 +141,7 @@ class TestCustomAccIncrements(TestVCruiseHelper):
# Test invalid long increment
self.reset_cruise_speed_state()
self.set_custom_increments(enabled=True, short_inc=1, long_inc=99)
self.enable(50 * CV.KPH_TO_MS, False)
self.enable(50 * CV.KPH_TO_MS, False, False)
initial_speed = self.v_cruise_helper.v_cruise_kph
self.press_button_long(ButtonType.accelCruise)
@@ -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
@@ -0,0 +1,17 @@
class WMACConstants:
# Lead detection parameters
LEAD_WINDOW_SIZE = 6 # Stable detection window
LEAD_PROB = 0.45 # Balanced threshold for lead detection
# Slow down detection parameters
SLOW_DOWN_WINDOW_SIZE = 5 # Responsive but stable
SLOW_DOWN_PROB = 0.3 # Balanced threshold for slow down scenarios
# Optimized slow down distance curve - smooth and progressive
SLOW_DOWN_BP = [0., 10., 20., 30., 40., 50., 55., 60.]
SLOW_DOWN_DIST = [32., 46., 64., 86., 108., 130., 145., 165.]
# Slowness detection parameters
SLOWNESS_WINDOW_SIZE = 10 # Stable slowness detection
SLOWNESS_PROB = 0.55 # Clear threshold for slowness
SLOWNESS_CRUISE_OFFSET = 1.025 # Conservative cruise speed offset
@@ -0,0 +1,388 @@
"""
Copyright (c) 2021-, rav4kumar, 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.
"""
# Version = 2025-6-30
from openpilot.cereal import messaging
from opendbc.car import structs
from numpy import interp
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
from typing import Literal
# d-e2e, from modeldata.h
TRAJECTORY_SIZE = 33
SET_MODE_TIMEOUT = 15
# Define the valid mode types
ModeType = Literal['acc', 'blended']
class SmoothKalmanFilter:
"""Enhanced Kalman filter with smoothing for stable decision making."""
def __init__(self, initial_value=0, measurement_noise=0.1, process_noise=0.01,
alpha=1.0, smoothing_factor=0.85):
self.x = initial_value
self.P = 1.0
self.R = measurement_noise
self.Q = process_noise
self.alpha = alpha
self.smoothing_factor = smoothing_factor
self.initialized = False
self.history = []
self.max_history = 10
self.confidence = 0.0
def add_data(self, measurement):
if len(self.history) >= self.max_history:
self.history.pop(0)
self.history.append(measurement)
if not self.initialized:
self.x = measurement
self.initialized = True
self.confidence = 0.1
return
self.P = self.alpha * self.P + self.Q
K = self.P / (self.P + self.R)
effective_K = K * (1.0 - self.smoothing_factor) + self.smoothing_factor * 0.1
innovation = measurement - self.x
self.x = self.x + effective_K * innovation
self.P = (1 - effective_K) * self.P
if abs(innovation) < 0.1:
self.confidence = min(1.0, self.confidence + 0.05)
else:
self.confidence = max(0.1, self.confidence - 0.02)
def get_value(self):
return self.x if self.initialized else None
def get_confidence(self):
return self.confidence
def reset_data(self):
self.initialized = False
self.history = []
self.confidence = 0.0
class ModeTransitionManager:
"""Manages smooth transitions between driving modes with hysteresis."""
def __init__(self):
self.current_mode: ModeType = 'acc'
self.mode_confidence = {'acc': 1.0, 'blended': 0.0}
self.transition_timeout = 0
self.min_mode_duration = 10
self.mode_duration = 0
self.emergency_override = False
def request_mode(self, mode: ModeType, confidence: float = 1.0, emergency: bool = False):
# Emergency override for critical situations (stops, collisions)
if emergency:
self.emergency_override = True
self.current_mode = mode
self.transition_timeout = SET_MODE_TIMEOUT
self.mode_duration = 0
return
self.mode_confidence[mode] = min(1.0, self.mode_confidence[mode] + 0.1 * confidence)
for m in self.mode_confidence:
if m != mode:
self.mode_confidence[m] = max(0.0, self.mode_confidence[m] - 0.05)
# Require minimum duration in current mode (unless emergency)
if self.mode_duration < self.min_mode_duration and not self.emergency_override:
return
# Hysteresis: higher threshold for mode changes
confidence_threshold = 0.6 if mode != self.current_mode else 0.3 # Lower threshold for faster response
if self.mode_confidence[mode] > confidence_threshold:
if mode != self.current_mode and self.transition_timeout == 0:
self.transition_timeout = SET_MODE_TIMEOUT
self.current_mode = mode
self.mode_duration = 0
def update(self):
if self.transition_timeout > 0:
self.transition_timeout -= 1
self.mode_duration += 1
# Reset emergency override after some time
if self.emergency_override and self.mode_duration > 20:
self.emergency_override = False
# Gradual confidence decay
for mode in self.mode_confidence:
self.mode_confidence[mode] *= 0.98
def get_mode(self) -> ModeType:
return self.current_mode
class DynamicExperimentalController:
def __init__(self, CP: structs.CarParams, mpc, params=None):
self._CP = CP
self._mpc = mpc
self._params = params or Params()
self._enabled: bool = self._params.get_bool("DynamicExperimentalControl")
self._active: bool = False
self._frame: int = 0
self._urgency = 0.0
self._mode_manager = ModeTransitionManager()
# Smooth filters for stable decision making with faster response for critical scenarios
self._lead_filter = SmoothKalmanFilter(
measurement_noise=0.15,
process_noise=0.05,
alpha=1.02,
smoothing_factor=0.8
)
self._slow_down_filter = SmoothKalmanFilter(
measurement_noise=0.1,
process_noise=0.1,
alpha=1.05,
smoothing_factor=0.7
)
self._slowness_filter = SmoothKalmanFilter(
measurement_noise=0.1,
process_noise=0.06,
alpha=1.015,
smoothing_factor=0.92
)
self._mpc_fcw_filter = SmoothKalmanFilter(
measurement_noise=0.2,
process_noise=0.1,
alpha=1.1,
smoothing_factor=0.5
)
self._has_lead_filtered = False
self._has_slow_down = False
self._has_slowness = False
self._has_mpc_fcw = False
self._v_ego_kph = 0.0
self._v_cruise_kph = 0.0
self._has_standstill = False
self._mpc_fcw_crash_cnt = 0
self._standstill_count = 0
# debug
self._endpoint_x = float('inf')
self._expected_distance = 0.0
self._trajectory_valid = False
def _read_params(self) -> None:
if self._frame % int(1. / DT_MDL) == 0:
self._enabled = self._params.get_bool("DynamicExperimentalControl")
def mode(self) -> str:
return self._mode_manager.get_mode()
def enabled(self) -> bool:
return self._enabled
def active(self) -> bool:
return self._active
def set_mpc_fcw_crash_cnt(self) -> None:
"""Set MPC FCW crash count"""
self._mpc_fcw_crash_cnt = self._mpc.crash_cnt
def _update_calculations(self, sm: messaging.SubMaster) -> None:
car_state = sm['carState']
lead_one = sm['radarState'].leadOne
md = sm['modelV2']
self._v_ego_kph = car_state.vEgo * 3.6
self._v_cruise_kph = car_state.vCruise
self._has_standstill = car_state.standstill
# standstill detection
if self._has_standstill:
self._standstill_count = min(20, self._standstill_count + 1)
else:
self._standstill_count = max(0, self._standstill_count - 1)
# Lead detection
self._lead_filter.add_data(float(lead_one.present))
lead_value = self._lead_filter.get_value() or 0.0
self._has_lead_filtered = lead_value > WMACConstants.LEAD_PROB
# MPC FCW detection
fcw_filtered_value = self._mpc_fcw_filter.get_value() or 0.0
self._mpc_fcw_filter.add_data(float(self._mpc_fcw_crash_cnt > 0))
self._has_mpc_fcw = fcw_filtered_value > 0.5
# Slow down detection
self._calculate_slow_down(md)
# Slowness detection
if not (self._standstill_count > 5) and not self._has_slow_down:
current_slowness = float(self._v_ego_kph <= (self._v_cruise_kph * WMACConstants.SLOWNESS_CRUISE_OFFSET))
self._slowness_filter.add_data(current_slowness)
slowness_value = self._slowness_filter.get_value() or 0.0
# Hysteresis for slowness
threshold = WMACConstants.SLOWNESS_PROB * (0.8 if self._has_slowness else 1.1)
self._has_slowness = slowness_value > threshold
def _calculate_slow_down(self, md):
"""Calculate urgency based on trajectory endpoint vs expected distance."""
# Reset to safe defaults
urgency = 0.0
self._endpoint_x = float('inf')
self._trajectory_valid = False
#Require exact trajectory size
position_valid = len(md.position.x) == TRAJECTORY_SIZE
orientation_valid = len(md.orientation.x) == TRAJECTORY_SIZE
if not (position_valid and orientation_valid):
# Invalid trajectory - this itself might indicate a stop scenario
# Apply moderate urgency for incomplete trajectories at speed
if self._v_ego_kph > 20.0:
urgency = 0.3
self._slow_down_filter.add_data(urgency)
urgency_filtered = self._slow_down_filter.get_value() or 0.0
self._has_slow_down = urgency_filtered > WMACConstants.SLOW_DOWN_PROB
self._urgency = urgency_filtered
return
# We have a valid full trajectory
self._trajectory_valid = True
# Use the exact endpoint (33rd point, index 32)
endpoint_x = md.position.x[TRAJECTORY_SIZE - 1]
self._endpoint_x = endpoint_x
# Get expected distance based on current speed using tuned constants
expected_distance = interp(self._v_ego_kph,
WMACConstants.SLOW_DOWN_BP,
WMACConstants.SLOW_DOWN_DIST)
self._expected_distance = expected_distance
# Calculate urgency based on trajectory shortage
if endpoint_x < expected_distance:
shortage = expected_distance - endpoint_x
shortage_ratio = shortage / expected_distance
# Base urgency on shortage ratio
urgency = min(1.0, shortage_ratio * 2.0)
# Increase urgency for very short trajectories (imminent stops)
critical_distance = expected_distance * 0.3
if endpoint_x < critical_distance:
urgency = min(1.0, urgency * 2.0)
# Speed-based urgency adjustment
if self._v_ego_kph > 25.0:
speed_factor = 1.0 + (self._v_ego_kph - 25.0) / 80.0
urgency = min(1.0, urgency * speed_factor)
# Apply filtering but with less smoothing for stops
self._slow_down_filter.add_data(urgency)
urgency_filtered = self._slow_down_filter.get_value() or 0.0
# Update state with lower threshold for better stop detection
self._has_slow_down = urgency_filtered > (WMACConstants.SLOW_DOWN_PROB * 0.8)
self._urgency = urgency_filtered
def _radarless_mode(self) -> None:
"""Radarless mode decision logic with emergency handling."""
# EMERGENCY: MPC FCW - immediate blended mode
if self._has_mpc_fcw:
self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
return
# Standstill: use blended
if self._standstill_count > 3:
self._mode_manager.request_mode('blended', confidence=0.9)
return
# Slow down scenarios: emergency for high urgency, normal for lower urgency
if self._has_slow_down:
if self._urgency > 0.7:
# Emergency: immediate blended mode for high urgency stops
self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
else:
# Normal: blended with urgency-based confidence
confidence = min(1.0, self._urgency * 1.5)
self._mode_manager.request_mode('blended', confidence=confidence)
return
# Driving slow: use ACC (but not if actively slowing down)
if self._has_slowness and not self._has_slow_down:
self._mode_manager.request_mode('acc', confidence=0.8)
return
# Default: ACC
self._mode_manager.request_mode('acc', confidence=0.7)
def _radar_mode(self) -> None:
"""Radar mode with emergency handling."""
# EMERGENCY: MPC FCW - immediate blended mode
if self._has_mpc_fcw:
self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
return
# If lead detected and not in standstill: always use ACC
if self._has_lead_filtered and not (self._standstill_count > 3):
self._mode_manager.request_mode('acc', confidence=1.0)
return
# Slow down scenarios: emergency for high urgency, normal for lower urgency
if self._has_slow_down:
if self._urgency > 0.7:
# Emergency: immediate blended mode for high urgency stops
self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
else:
# Normal: blended with urgency-based confidence
confidence = min(1.0, self._urgency * 1.3)
self._mode_manager.request_mode('blended', confidence=confidence)
return
# Standstill: use blended
if self._standstill_count > 3:
self._mode_manager.request_mode('blended', confidence=0.9)
return
# Driving slow: use ACC (but not if actively slowing down)
if self._has_slowness and not self._has_slow_down:
self._mode_manager.request_mode('acc', confidence=0.8)
return
# Default: ACC
self._mode_manager.request_mode('acc', confidence=0.7)
def update(self, sm: messaging.SubMaster) -> None:
self._read_params()
self.set_mpc_fcw_crash_cnt()
self._update_calculations(sm)
if self._CP.radarUnavailable:
self._radarless_mode()
else:
self._radar_mode()
self._mode_manager.update()
self._active = sm['selfdriveState'].experimentalMode and self._enabled
self._frame += 1
@@ -0,0 +1,112 @@
"""
Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
This file is part of sunnypilot and is licensed under the MIT License.
See the LICENSE.md file in the root directory for more details.
"""
from typing import cast
from openpilot.cereal import custom, messaging
from opendbc.car import structs
from openpilot.common.test import OpenpilotTestCase
from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanner, LongitudinalPlanSource
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
V_EGO = 20.0
E2E_ACCEL = -3.0 # low enough that e2e wins the min() whenever it is a candidate
class MockDec:
def __init__(self, active: bool, mode: str):
self._active = active
self._mode = mode
def update(self, sm):
pass
def active(self) -> bool:
return self._active
def mode(self) -> str:
return self._mode
def enabled(self) -> bool:
return True
class MockSubMaster(dict):
def __init__(self, services: dict):
super().__init__(services)
self.valid = dict.fromkeys(services, True)
self.logMonoTime = dict.fromkeys(services, 0)
self.updated = dict.fromkeys(services, True)
self.recv_frame = dict.fromkeys(services, 1)
def all_checks(self, service_list=None) -> bool:
return True
def build_sm(experimental_mode: bool) -> MockSubMaster:
services = {}
for service in ("radarState", "controlsState", "vehicleParameters", "carStateSP",
"liveMapDataSP", "gpsLocationExternal", "gpsLocation"):
services[service] = getattr(messaging.new_message(service), service)
car_state = messaging.new_message('carState')
car_state.carState.vEgo = V_EGO
car_state.carState.vCruise = 100.0
car_state.carState.vCruiseCluster = 100.0
services['carState'] = car_state.carState.as_reader()
selfdrive_state = messaging.new_message('selfdriveState')
selfdrive_state.selfdriveState.experimentalMode = experimental_mode
selfdrive_state.selfdriveState.enabled = True
services['selfdriveState'] = selfdrive_state.selfdriveState.as_reader()
car_control = messaging.new_message('carControl')
car_control.carControl.enabled = True
services['carControl'] = car_control.carControl.as_reader()
model = messaging.new_message('modelV2')
model.modelV2.orientationRate.z = [0.01] * 33 # nonzero: a straight path divides by zero in SCC vision
model.modelV2.velocity.x = [V_EGO] * 33
model.modelV2.position.x = [float(i) for i in range(33)]
model.modelV2.action.desiredAcceleration = E2E_ACCEL
services['modelV2'] = model.modelV2.as_reader()
return MockSubMaster(services)
def build_planner(dec_active: bool, dec_mode: str) -> LongitudinalPlanner:
CP = structs.CarParams()
CP.steerRatio = 15.0
CP.wheelbase = 2.7
CP.longitudinalActuatorDelay = 0.2
CP_SP = custom.CarParamsSP.new_message().as_reader()
planner = LongitudinalPlanner(CP, CP_SP, init_v=V_EGO)
planner.dec = cast(DynamicExperimentalController, MockDec(dec_active, dec_mode))
return planner
class TestDecPlannerGate(OpenpilotTestCase):
"""The e2e candidate must be gated on is_e2e(), not raw experimentalMode."""
def _source(self, experimental_mode: bool, dec_active: bool, dec_mode: str) -> LongitudinalPlanSource:
planner = build_planner(dec_active, dec_mode)
planner.update(build_sm(experimental_mode))
return planner.mpc.source
def test_no_e2e_when_experimental_mode_off(self):
assert self._source(False, False, 'acc') != LongitudinalPlanSource.e2e
def test_e2e_when_dec_inactive(self):
# DEC off: behavior must match upstream
assert self._source(True, False, 'acc') == LongitudinalPlanSource.e2e
def test_e2e_when_dec_blended(self):
assert self._source(True, True, 'blended') == LongitudinalPlanSource.e2e
def test_no_e2e_when_dec_holds_acc(self):
# the regression
assert self._source(True, True, 'acc') != LongitudinalPlanSource.e2e
@@ -0,0 +1,91 @@
from openpilot.common.test import OpenpilotTestCase
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
class MockLeadOne:
def __init__(self, present=0.0):
self.present = present
class MockRadarState:
def __init__(self, present=0.0):
self.leadOne = MockLeadOne(present=present)
class MockCarState:
def __init__(self, vEgo=0.0, vCruise=0.0, standstill=False):
self.vEgo = vEgo
self.vCruise = vCruise
self.standstill = standstill
class MockModelData:
def __init__(self, valid=True):
size = 33 if valid else 10 # incomplete if invalid
self.position = type("Pos", (), {"x": [0.0] * size})()
self.orientation = type("Ori", (), {"x": [0.0] * size})()
class MockSelfDriveState:
def __init__(self, experimentalMode=False):
self.experimentalMode = experimentalMode
class MockParams:
def get_bool(self, name):
return True
def default_sm():
sm = {
'carState': MockCarState(vEgo=10.0, vCruise=20.0),
'radarState': MockRadarState(present=1.0),
'modelV2': MockModelData(valid=True),
'selfdriveState': MockSelfDriveState(experimentalMode=True),
}
return sm
def mock_cp():
class CP:
radarUnavailable = False
return CP()
def mock_mpc():
class MPC:
crash_cnt = 0
return MPC()
# Fake Kalman Filter that always returns a given value
class FakeKalman:
def __init__(self, value=1.0):
self.value = value
def add_data(self, v): pass
def get_value(self): return self.value
def get_confidence(self): return 1.0
def reset_data(self): pass
class TestDynamicExperimentalController(OpenpilotTestCase):
def test_initial_mode_is_acc(self, mock_cp, mock_mpc):
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
assert controller.mode() == "acc"
def test_standstill_triggers_blended(self, mock_cp, mock_mpc, default_sm):
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
default_sm['carState'].standstill = True
for _ in range(10):
controller.update(default_sm)
assert controller.mode() == "blended"
def test_emergency_blended_on_fcw(self, mock_cp, mock_mpc, default_sm):
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
mock_mpc.crash_cnt = 1 # simulate FCW
for _ in range(2):
controller.update(default_sm)
assert controller.mode() == "blended"
def test_radarless_slowdown_triggers_blended(self, mock_cp, mock_mpc, default_sm):
mock_cp.radarUnavailable = True
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
# Force conditions to simulate slowdown
controller._slow_down_filter = FakeKalman(value=1.0) # ty: ignore[invalid-assignment]
controller._v_ego_kph = 35.0
default_sm['modelV2'] = MockModelData(valid=False) # Incomplete trajectory
for _ in range(3):
controller.update(default_sm)
assert controller.mode() == "blended"
@@ -9,6 +9,7 @@ from openpilot.cereal import messaging, custom
from opendbc.car import structs
from openpilot.common.constants import CV
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
from openpilot.sunnypilot.selfdrive.controls.lib.e2e_alerts_helper import E2EAlertsHelper
from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.smart_cruise_control import SmartCruiseControl
from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_assist import SpeedLimitAssist
@@ -16,6 +17,7 @@ from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_resolve
from openpilot.sunnypilot.selfdrive.selfdrived.events import EventsSP
from openpilot.sunnypilot.models.helpers import get_active_bundle
DecState = custom.LongitudinalPlanSP.DynamicExperimentalControl.DynamicExperimentalControlState
LongitudinalPlanSource = custom.LongitudinalPlanSP.LongitudinalPlanSource
@@ -23,6 +25,7 @@ class LongitudinalPlannerSP:
def __init__(self, CP: structs.CarParams, CP_SP: structs.CarParamsSP, mpc):
self.events_sp = EventsSP()
self.resolver = SpeedLimitResolver()
self.dec = DynamicExperimentalController(CP, mpc)
self.scc = SmartCruiseControl()
self.resolver = SpeedLimitResolver()
self.sla = SpeedLimitAssist(CP, CP_SP)
@@ -33,6 +36,13 @@ class LongitudinalPlannerSP:
self.output_v_target = 0.
self.output_a_target = 0.
def is_e2e(self, sm: messaging.SubMaster) -> bool:
experimental_mode = sm['selfdriveState'].experimentalMode
if not self.dec.active():
return experimental_mode
return experimental_mode and self.dec.mode() == "blended"
def update_targets(self, sm: messaging.SubMaster, v_ego: float, a_ego: float, v_cruise: float) -> tuple[float, float]:
CS = sm['carState']
v_cruise_cluster_kph = min(CS.vCruiseCluster, V_CRUISE_MAX)
@@ -65,6 +75,7 @@ class LongitudinalPlannerSP:
def update(self, sm: messaging.SubMaster) -> None:
self.events_sp.clear()
self.dec.update(sm)
self.e2e_alerts_helper.update(sm, self.events_sp)
def publish_longitudinal_plan_sp(self, sm: messaging.SubMaster, pm: messaging.PubMaster) -> None:
@@ -78,6 +89,12 @@ class LongitudinalPlannerSP:
longitudinalPlanSP.aTarget = float(self.output_a_target)
longitudinalPlanSP.events = self.events_sp.to_msg()
# Dynamic Experimental Control
dec = longitudinalPlanSP.dec
dec.state = DecState.blended if self.dec.mode() == 'blended' else DecState.acc
dec.enabled = self.dec.enabled()
dec.active = self.dec.active()
# Smart Cruise Control
smartCruiseControl = longitudinalPlanSP.smartCruiseControl
# Vision Control
@@ -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
@@ -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
@@ -367,8 +367,8 @@ enablement:
enablement:
- type: any
conditions:
- {type: param, key: SmartCruiseControlVision, equals: true}
- {type: param, key: SmartCruiseControlMap, equals: true}
- {type: param, key: ExperimentalMode, equals: true}
- {type: param, key: DynamicExperimentalControl, equals: true}
```
**Mixed: capability AND param** (only on longitudinal cars when ShowAdvancedControls is on):
@@ -599,6 +599,26 @@
}
]
},
{
"key": "DynamicExperimentalControl",
"widget": "toggle",
"title": "Dynamic Experimental Control",
"description": "Let the model decide when to use sunnypilot ACC or sunnypilot End to End Longitudinal.",
"visibility": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
}
],
"enablement": [
{
"type": "capability",
"field": "has_longitudinal_control",
"equals": true
}
]
},
{
"key": "DisengageOnAccelerator",
"widget": "toggle",
@@ -16,6 +16,14 @@ sections:
title: Experimental Mode
enablement:
- $ref: '#/macros/longitudinal'
- key: DynamicExperimentalControl
widget: toggle
title: Dynamic Experimental Control
description: Let the model decide when to use sunnypilot ACC or sunnypilot End to End Longitudinal.
visibility:
- $ref: '#/macros/longitudinal'
enablement:
- $ref: '#/macros/longitudinal'
- key: DisengageOnAccelerator
widget: toggle
title: Disengage Cruise on Accelerator Pedal
@@ -201,6 +201,11 @@ class TestSpuriousOffroadGatesDropped(OpenpilotTestCase):
assert item is not None
assert "offroad_only" not in _flatten_rule_types(item.get("enablement"))
def test_dynamic_experimental_has_no_offroad_only(self, schema):
item = _find_item(schema, "DynamicExperimentalControl")
assert item is not None
assert "offroad_only" not in _flatten_rule_types(item.get("enablement"))
class TestNotEngagedReplacement(OpenpilotTestCase):
@parameterized.expand([