mirror of
https://github.com/firestar5683/StarPilot.git
synced 2026-07-26 19:52:06 +08:00
firestar5683
117 lines
4.5 KiB
Python
117 lines
4.5 KiB
Python
#!/usr/bin/env python3
|
|
import numpy as np
|
|
|
|
from openpilot.common.constants import CV
|
|
from openpilot.common.filter_simple import FirstOrderFilter
|
|
from openpilot.common.realtime import DT_MDL
|
|
from openpilot.starpilot.common.experimental_state import CEStatus
|
|
|
|
|
|
MODEL_STOP_TIME = 7.0
|
|
MODEL_STOP_ENTER = 0.63
|
|
MODEL_STOP_EXIT = 0.28
|
|
MODEL_STOP_FILTER_TIME = 0.35
|
|
SLOW_LEAD_FILTER_TIME = 0.35
|
|
TURN_VETO_MAX_SPEED = 15.0 * CV.MPH_TO_MS
|
|
TURN_VETO_MIN_STEERING_ANGLE = 45.0
|
|
MAX_STOP_DETECTION_SPEED = 75.0 * CV.MPH_TO_MS
|
|
|
|
|
|
class UnifiedLongitudinalIntent:
|
|
"""Small scene detector for continuous longitudinal planning.
|
|
|
|
This class never selects a planner mode. It reports model stop intent and a
|
|
UI reason while the longitudinal planner continuously considers cruise,
|
|
model, curves, and both leads.
|
|
"""
|
|
|
|
def __init__(self, starpilot_planner):
|
|
self.starpilot_planner = starpilot_planner
|
|
self.params_memory = starpilot_planner.params_memory
|
|
self.stop_filter = FirstOrderFilter(0.0, MODEL_STOP_FILTER_TIME, DT_MDL)
|
|
self.lead_filter = FirstOrderFilter(0.0, SLOW_LEAD_FILTER_TIME, DT_MDL)
|
|
self.stop_detected = False
|
|
self.status_value = CEStatus["OFF"]
|
|
self._last_status = None
|
|
|
|
@staticmethod
|
|
def _committed_turn(v_ego, car_state, driving_in_curve):
|
|
if car_state.standstill or v_ego > TURN_VETO_MAX_SPEED:
|
|
return False
|
|
if not (car_state.leftBlinker or car_state.rightBlinker):
|
|
return False
|
|
return abs(float(car_state.steeringAngleDeg)) >= TURN_VETO_MIN_STEERING_ANGLE or driving_in_curve
|
|
|
|
def _model_stop_candidate(self, v_ego, sm):
|
|
model = sm["modelV2"]
|
|
if bool(getattr(model.action, "shouldStop", False)):
|
|
return True
|
|
if not len(model.position.x):
|
|
return False
|
|
|
|
model_length = max(float(model.position.x[-1]), 0.0)
|
|
end_speed = float(model.velocity.x[-1]) if len(model.velocity.x) else v_ego
|
|
stop_distance = max(v_ego * MODEL_STOP_TIME - 2.5, 0.0)
|
|
return model_length < stop_distance and end_speed < max(2.0, 0.2 * v_ego)
|
|
|
|
@staticmethod
|
|
def _slow_lead_candidate(v_ego, sm):
|
|
candidates = []
|
|
for lead in (sm["radarState"].leadOne, sm["radarState"].leadTwo):
|
|
if not bool(getattr(lead, "status", False)):
|
|
continue
|
|
d_rel = float(getattr(lead, "dRel", np.inf))
|
|
v_lead = float(getattr(lead, "vLead", v_ego))
|
|
model_prob = float(getattr(lead, "modelProb", 1.0 if getattr(lead, "radar", False) else 0.0))
|
|
credible = bool(getattr(lead, "radar", False)) or model_prob >= 0.85
|
|
if credible and d_rel < max(40.0, 3.0 * v_ego) and v_lead < v_ego - 0.75:
|
|
candidates.append(lead)
|
|
return bool(candidates)
|
|
|
|
def update(self, v_ego, sm, starpilot_toggles):
|
|
car_state = sm["carState"]
|
|
force_stop = bool(getattr(self.starpilot_planner.starpilot_vcruise, "forcing_stop", False))
|
|
stop_sign = bool(getattr(self.starpilot_planner.starpilot_vcruise, "stop_sign_confirmed", False))
|
|
traffic_mode = bool(sm["starpilotCarState"].trafficModeEnabled)
|
|
turn_veto = self._committed_turn(v_ego, car_state, self.starpilot_planner.driving_in_curve)
|
|
|
|
model_stop = self._model_stop_candidate(v_ego, sm)
|
|
model_stop &= not traffic_mode and not turn_veto and v_ego <= MAX_STOP_DETECTION_SPEED
|
|
self.stop_filter.update(model_stop)
|
|
|
|
if force_stop or stop_sign:
|
|
self.stop_detected = True
|
|
self.stop_filter.x = 1.0
|
|
elif self.stop_detected:
|
|
self.stop_detected = self.stop_filter.x > MODEL_STOP_EXIT
|
|
else:
|
|
self.stop_detected = self.stop_filter.x >= MODEL_STOP_ENTER
|
|
|
|
slow_lead = self._slow_lead_candidate(v_ego, sm)
|
|
self.lead_filter.update(slow_lead)
|
|
slow_lead = self.lead_filter.x >= MODEL_STOP_ENTER
|
|
|
|
signal = bool(car_state.leftBlinker or car_state.rightBlinker) and v_ego < 15.0
|
|
curve = bool(self.starpilot_planner.road_curvature_detected or self.starpilot_planner.driving_in_curve)
|
|
slc_request = bool(self.starpilot_planner.starpilot_vcruise.slc.experimental_mode)
|
|
|
|
if self.stop_detected:
|
|
status = CEStatus["STOP_LIGHT"]
|
|
elif slow_lead:
|
|
status = CEStatus["LEAD"]
|
|
elif signal:
|
|
status = CEStatus["SIGNAL"]
|
|
elif curve:
|
|
status = CEStatus["CURVATURE"]
|
|
elif slc_request:
|
|
status = CEStatus["SPEED_LIMIT"]
|
|
elif bool(getattr(starpilot_toggles, "longitudinal_model_preference", False)):
|
|
status = CEStatus["USER_OVERRIDDEN"]
|
|
else:
|
|
status = CEStatus["OFF"]
|
|
|
|
self.status_value = status
|
|
if status != self._last_status:
|
|
self.params_memory.put_int("CEStatus", status)
|
|
self._last_status = status
|