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feat(dec): rework dynamic experimental controller
This commit is contained in:
rav4kumar
@@ -1,17 +1,46 @@
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from openpilot.common.realtime import DT_MDL
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class WMACConstants:
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# Lead detection parameters
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LEAD_WINDOW_SIZE = 6 # Stable detection window
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LEAD_PROB = 0.45 # Balanced threshold for lead detection
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TRAJECTORY_SIZE = 33
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PARAM_READ_FRAMES = max(1, int(round(1.0 / DT_MDL)))
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# Slow down detection parameters
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SLOW_DOWN_WINDOW_SIZE = 5 # Responsive but stable
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SLOW_DOWN_PROB = 0.3 # Balanced threshold for slow down scenarios
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EMERGENCY_HOLD_FRAMES = max(1, int(round(0.75 / DT_MDL)))
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MIN_MODE_DURATION = {'acc': max(1, int(round(0.6 / DT_MDL))), 'blended': max(1, int(round(0.5 / DT_MDL)))}
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ENTER_BLENDED_FRAMES = max(1, int(round(0.4 / DT_MDL)))
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EXIT_BLENDED_FRAMES = max(1, int(round(0.35 / DT_MDL)))
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STANDSTILL_FRAMES = max(1, int(round(0.2 / DT_MDL)))
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# Optimized slow down distance curve - smooth and progressive
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LEAD_PROB = 0.45
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LEAD_EXIT_PROB = 0.25
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LEAD_RISE_RATE = 1.0
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LEAD_FALL_RATE = 0.35
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RADAR_LEAD_ACC_PROB = 0.5
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RADAR_LEAD_ACC_EXIT_PROB = 0.4
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RADAR_LEAD_ACC_RISE_RATE = 1.0
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RADAR_LEAD_ACC_FALL_RATE = 0.25
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RADAR_LEAD_ACC_MAX_DREL = 80.0
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RADAR_LEAD_ACC_MAX_TTC = 6.0
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RADAR_LEAD_ACC_MIN_CLOSING_SPEED = -0.5
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SLOW_DOWN_PROB = 0.5
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SLOW_DOWN_EXIT_PROB = 0.4
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SLOW_DOWN_RISE_RATE = 0.65
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SLOW_DOWN_FALL_RATE = 0.15
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SLOW_DOWN_BP = [0., 10., 20., 30., 40., 50., 55., 60.]
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SLOW_DOWN_DIST = [32., 46., 64., 86., 108., 130., 145., 165.]
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URGENT_SLOW_DOWN_PROB = 0.85
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# Slowness detection parameters
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SLOWNESS_WINDOW_SIZE = 10 # Stable slowness detection
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SLOWNESS_PROB = 0.55 # Clear threshold for slowness
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SLOWNESS_CRUISE_OFFSET = 1.025 # Conservative cruise speed offset
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MODEL_DECEL_START = -0.5
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MODEL_DECEL_RANGE = 2.0
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ENDPOINT_URGENCY_GAIN = 1.3
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CRITICAL_ENDPOINT_FACTOR = 0.3
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CRITICAL_URGENCY_GAIN = 1.5
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SPEED_URGENCY_MIN = 25.0
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SPEED_URGENCY_RANGE = 80.0
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SLOWNESS_PROB = 0.55
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SLOWNESS_EXIT_PROB = 0.45
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SLOWNESS_RISE_RATE = 0.35
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SLOWNESS_FALL_RATE = 0.5
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SLOWNESS_CRUISE_OFFSET = 1.025
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@@ -6,129 +6,116 @@ See the LICENSE.md file in the root directory for more details.
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"""
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# Version = 2025-6-30
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from cereal import messaging
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from opendbc.car import structs
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from numpy import interp
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from openpilot.common.params import Params
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from openpilot.common.realtime import DT_MDL
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from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
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from typing import Literal
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# d-e2e, from modeldata.h
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TRAJECTORY_SIZE = 33
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SET_MODE_TIMEOUT = 15
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from cereal import messaging
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from numpy import interp
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from opendbc.car import structs
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from openpilot.common.params import Params
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from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
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# Define the valid mode types
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ModeType = Literal['acc', 'blended']
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class SmoothKalmanFilter:
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"""Enhanced Kalman filter with smoothing for stable decision making."""
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def clip01(value: float) -> float:
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return max(0.0, min(1.0, float(value)))
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def __init__(self, initial_value=0, measurement_noise=0.1, process_noise=0.01,
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alpha=1.0, smoothing_factor=0.85):
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self.x = initial_value
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self.P = 1.0
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self.R = measurement_noise
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self.Q = process_noise
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self.alpha = alpha
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self.smoothing_factor = smoothing_factor
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self.initialized = False
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self.history = []
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self.max_history = 10
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self.confidence = 0.0
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def add_data(self, measurement):
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if len(self.history) >= self.max_history:
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self.history.pop(0)
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self.history.append(measurement)
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class SmoothedSignal:
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def __init__(self, rise_rate: float, fall_rate: float, initial_value: float = 0.0):
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self.rise_rate = clip01(rise_rate)
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self.fall_rate = clip01(fall_rate)
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self.value = clip01(initial_value)
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if not self.initialized:
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self.x = measurement
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self.initialized = True
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self.confidence = 0.1
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return
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def update(self, measurement: float) -> float:
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measurement = clip01(measurement)
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rate = self.rise_rate if measurement > self.value else self.fall_rate
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self.value += (measurement - self.value) * rate
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return self.value
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self.P = self.alpha * self.P + self.Q
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def reset(self, value: float = 0.0) -> None:
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self.value = clip01(value)
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K = self.P / (self.P + self.R)
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effective_K = K * (1.0 - self.smoothing_factor) + self.smoothing_factor * 0.1
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innovation = measurement - self.x
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self.x = self.x + effective_K * innovation
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self.P = (1 - effective_K) * self.P
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class HysteresisSignal:
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def __init__(self, enter_threshold: float, exit_threshold: float, rise_rate: float, fall_rate: float):
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self.enter_threshold = clip01(enter_threshold)
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self.exit_threshold = clip01(exit_threshold)
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self.filter = SmoothedSignal(rise_rate, fall_rate)
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self.active = False
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if abs(innovation) < 0.1:
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self.confidence = min(1.0, self.confidence + 0.05)
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else:
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self.confidence = max(0.1, self.confidence - 0.02)
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def update(self, measurement: float) -> bool:
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value = self.filter.update(measurement)
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threshold = self.exit_threshold if self.active else self.enter_threshold
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self.active = value > threshold
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return self.active
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def get_value(self):
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return self.x if self.initialized else None
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def reset(self) -> None:
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self.filter.reset()
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self.active = False
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def get_confidence(self):
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return self.confidence
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def reset_data(self):
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self.initialized = False
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self.history = []
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self.confidence = 0.0
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@property
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def value(self) -> float:
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return self.filter.value
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class ModeTransitionManager:
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"""Manages smooth transitions between driving modes with hysteresis."""
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def __init__(self):
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self.current_mode: ModeType = 'acc'
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self.mode_confidence = {'acc': 1.0, 'blended': 0.0}
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self.transition_timeout = 0
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self.min_mode_duration = 10
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self.mode_duration = 0
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self.emergency_override = False
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self._pending_mode: ModeType = 'acc'
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self._pending_count = 0
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self._blended_hold_frames = 0
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def request_mode(self, mode: ModeType, confidence: float = 1.0, emergency: bool = False):
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# Emergency override for critical situations (stops, collisions)
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if emergency:
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self.emergency_override = True
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self.current_mode = mode
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self.transition_timeout = SET_MODE_TIMEOUT
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self.mode_duration = 0
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def request_mode(self, mode: ModeType, immediate: bool = False, hold_frames: int = 0, cancel_hold: bool = False) -> None:
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if immediate:
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self._blended_hold_frames = max(self._blended_hold_frames, hold_frames)
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self._pending_mode = mode
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self._pending_count = 0
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self._switch_mode(mode)
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return
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self.mode_confidence[mode] = min(1.0, self.mode_confidence[mode] + 0.1 * confidence)
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for m in self.mode_confidence:
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if m != mode:
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self.mode_confidence[m] = max(0.0, self.mode_confidence[m] - 0.05)
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if cancel_hold and mode == 'acc':
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self._blended_hold_frames = 0
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# Require minimum duration in current mode (unless emergency)
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if self.mode_duration < self.min_mode_duration and not self.emergency_override:
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if self._blended_hold_frames > 0:
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mode = 'blended'
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if mode == self.current_mode:
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self._pending_mode = mode
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self._pending_count = 0
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return
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# Hysteresis: higher threshold for mode changes
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confidence_threshold = 0.6 if mode != self.current_mode else 0.3 # Lower threshold for faster response
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if mode != self._pending_mode:
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self._pending_mode = mode
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self._pending_count = 1
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else:
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self._pending_count += 1
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if self.mode_confidence[mode] > confidence_threshold:
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if mode != self.current_mode and self.transition_timeout == 0:
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self.transition_timeout = SET_MODE_TIMEOUT
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self.current_mode = mode
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self.mode_duration = 0
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if self.mode_duration < WMACConstants.MIN_MODE_DURATION[self.current_mode]:
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return
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def update(self):
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if self.transition_timeout > 0:
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self.transition_timeout -= 1
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required_count = WMACConstants.ENTER_BLENDED_FRAMES if mode == 'blended' else WMACConstants.EXIT_BLENDED_FRAMES
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if self._pending_count >= required_count:
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self._switch_mode(mode)
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def update(self) -> None:
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if self._blended_hold_frames > 0:
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self._blended_hold_frames -= 1
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self.mode_duration += 1
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# Reset emergency override after some time
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if self.emergency_override and self.mode_duration > 20:
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self.emergency_override = False
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# Gradual confidence decay
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for mode in self.mode_confidence:
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self.mode_confidence[mode] *= 0.98
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def get_mode(self) -> ModeType:
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return self.current_mode
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def _switch_mode(self, mode: ModeType) -> None:
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if mode == self.current_mode:
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return
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self.current_mode = mode
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self.mode_duration = 0
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self._pending_mode = mode
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self._pending_count = 0
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class DynamicExperimentalController:
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def __init__(self, CP: structs.CarParams, mpc, params=None):
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@@ -142,35 +129,33 @@ class DynamicExperimentalController:
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self._mode_manager = ModeTransitionManager()
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# Smooth filters for stable decision making with faster response for critical scenarios
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self._lead_filter = SmoothKalmanFilter(
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measurement_noise=0.15,
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process_noise=0.05,
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alpha=1.02,
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smoothing_factor=0.8
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self._lead_tracker = HysteresisSignal(
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enter_threshold=WMACConstants.LEAD_PROB,
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exit_threshold=WMACConstants.LEAD_EXIT_PROB,
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rise_rate=WMACConstants.LEAD_RISE_RATE,
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fall_rate=WMACConstants.LEAD_FALL_RATE,
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)
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self._radar_acc_lead_tracker = HysteresisSignal(
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enter_threshold=WMACConstants.RADAR_LEAD_ACC_PROB,
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exit_threshold=WMACConstants.RADAR_LEAD_ACC_EXIT_PROB,
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rise_rate=WMACConstants.RADAR_LEAD_ACC_RISE_RATE,
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fall_rate=WMACConstants.RADAR_LEAD_ACC_FALL_RATE,
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)
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self._slow_down_tracker = HysteresisSignal(
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enter_threshold=WMACConstants.SLOW_DOWN_PROB,
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exit_threshold=WMACConstants.SLOW_DOWN_EXIT_PROB,
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rise_rate=WMACConstants.SLOW_DOWN_RISE_RATE,
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fall_rate=WMACConstants.SLOW_DOWN_FALL_RATE,
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)
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self._slowness_tracker = HysteresisSignal(
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enter_threshold=WMACConstants.SLOWNESS_PROB,
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exit_threshold=WMACConstants.SLOWNESS_EXIT_PROB,
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rise_rate=WMACConstants.SLOWNESS_RISE_RATE,
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fall_rate=WMACConstants.SLOWNESS_FALL_RATE,
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)
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self._slow_down_filter = SmoothKalmanFilter(
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measurement_noise=0.1,
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process_noise=0.1,
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alpha=1.05,
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smoothing_factor=0.7
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)
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self._slowness_filter = SmoothKalmanFilter(
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measurement_noise=0.1,
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process_noise=0.06,
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alpha=1.015,
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smoothing_factor=0.92
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)
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self._mpc_fcw_filter = SmoothKalmanFilter(
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measurement_noise=0.2,
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process_noise=0.1,
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alpha=1.1,
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smoothing_factor=0.5
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)
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self._has_lead_filtered = False
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self._has_radar_acc_lead = False
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self._has_slow_down = False
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self._has_slowness = False
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self._has_mpc_fcw = False
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@@ -179,13 +164,14 @@ class DynamicExperimentalController:
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self._has_standstill = False
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self._mpc_fcw_crash_cnt = 0
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self._standstill_count = 0
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# debug
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self._endpoint_x = float('inf')
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self._expected_distance = 0.0
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self._trajectory_valid = False
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self._raw_urgency = 0.0
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def _read_params(self) -> None:
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if self._frame % int(1. / DT_MDL) == 0:
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if self._frame % WMACConstants.PARAM_READ_FRAMES == 0:
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self._enabled = self._params.get_bool("DynamicExperimentalControl")
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def mode(self) -> str:
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@@ -198,7 +184,6 @@ class DynamicExperimentalController:
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return self._active
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def set_mpc_fcw_crash_cnt(self) -> None:
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"""Set MPC FCW crash count"""
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self._mpc_fcw_crash_cnt = self._mpc.crash_cnt
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def _update_calculations(self, sm: messaging.SubMaster) -> None:
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@@ -210,179 +195,109 @@ class DynamicExperimentalController:
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self._v_cruise_kph = car_state.vCruise
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self._has_standstill = car_state.standstill
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# standstill detection
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if self._has_standstill:
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self._standstill_count = min(20, self._standstill_count + 1)
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self._standstill_count = min(WMACConstants.STANDSTILL_FRAMES * 3, self._standstill_count + 1)
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else:
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self._standstill_count = max(0, self._standstill_count - 1)
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# Lead detection
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self._lead_filter.add_data(float(lead_one.status))
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lead_value = self._lead_filter.get_value() or 0.0
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self._has_lead_filtered = lead_value > WMACConstants.LEAD_PROB
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# MPC FCW detection
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fcw_filtered_value = self._mpc_fcw_filter.get_value() or 0.0
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self._mpc_fcw_filter.add_data(float(self._mpc_fcw_crash_cnt > 0))
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self._has_mpc_fcw = fcw_filtered_value > 0.5
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# Slow down detection
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self._has_lead_filtered = self._lead_tracker.update(float(lead_one.status))
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self._has_radar_acc_lead = self._radar_acc_lead_tracker.update(self._radar_acc_lead_score(lead_one))
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self._has_mpc_fcw = self._mpc_fcw_crash_cnt > 0
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self._calculate_slow_down(md)
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# Slowness detection
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if not (self._standstill_count > 5) and not self._has_slow_down:
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if self._standstill_count > WMACConstants.STANDSTILL_FRAMES or self._has_slow_down:
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self._slowness_tracker.reset()
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self._has_slowness = False
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else:
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current_slowness = float(self._v_ego_kph <= (self._v_cruise_kph * WMACConstants.SLOWNESS_CRUISE_OFFSET))
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self._slowness_filter.add_data(current_slowness)
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slowness_value = self._slowness_filter.get_value() or 0.0
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self._has_slowness = self._slowness_tracker.update(current_slowness)
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# Hysteresis for slowness
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threshold = WMACConstants.SLOWNESS_PROB * (0.8 if self._has_slowness else 1.1)
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self._has_slowness = slowness_value > threshold
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def _calculate_slow_down(self, md):
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"""Calculate urgency based on trajectory endpoint vs expected distance."""
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# Reset to safe defaults
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urgency = 0.0
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def _calculate_slow_down(self, md) -> None:
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self._endpoint_x = float('inf')
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self._expected_distance = 0.0
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self._trajectory_valid = False
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#Require exact trajectory size
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position_valid = len(md.position.x) == TRAJECTORY_SIZE
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orientation_valid = len(md.orientation.x) == TRAJECTORY_SIZE
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urgency = self._model_action_urgency(md)
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position_valid = len(md.position.x) == WMACConstants.TRAJECTORY_SIZE
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if not (position_valid and orientation_valid):
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# Invalid trajectory - this itself might indicate a stop scenario
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# Apply moderate urgency for incomplete trajectories at speed
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if self._v_ego_kph > 20.0:
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urgency = 0.3
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if position_valid:
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self._trajectory_valid = True
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self._endpoint_x = md.position.x[WMACConstants.TRAJECTORY_SIZE - 1]
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self._expected_distance = interp(self._v_ego_kph, WMACConstants.SLOW_DOWN_BP, WMACConstants.SLOW_DOWN_DIST)
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urgency = max(urgency, self._endpoint_urgency(self._endpoint_x, self._expected_distance))
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self._slow_down_filter.add_data(urgency)
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urgency_filtered = self._slow_down_filter.get_value() or 0.0
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self._has_slow_down = urgency_filtered > WMACConstants.SLOW_DOWN_PROB
|
||||
self._urgency = urgency_filtered
|
||||
return
|
||||
self._raw_urgency = clip01(urgency)
|
||||
self._has_slow_down = self._slow_down_tracker.update(self._raw_urgency)
|
||||
self._urgency = self._slow_down_tracker.value
|
||||
|
||||
# We have a valid full trajectory
|
||||
self._trajectory_valid = True
|
||||
def _radar_acc_lead_score(self, lead_one) -> float:
|
||||
if not lead_one.status:
|
||||
return 0.0
|
||||
|
||||
# Use the exact endpoint (33rd point, index 32)
|
||||
endpoint_x = md.position.x[TRAJECTORY_SIZE - 1]
|
||||
self._endpoint_x = endpoint_x
|
||||
d_rel = float(getattr(lead_one, 'dRel', float('inf')))
|
||||
v_rel = float(getattr(lead_one, 'vRel', 0.0))
|
||||
if d_rel <= WMACConstants.RADAR_LEAD_ACC_MAX_DREL:
|
||||
return 1.0
|
||||
if v_rel <= WMACConstants.RADAR_LEAD_ACC_MIN_CLOSING_SPEED and d_rel / max(-v_rel, 0.1) <= WMACConstants.RADAR_LEAD_ACC_MAX_TTC:
|
||||
return 1.0
|
||||
return 0.0
|
||||
|
||||
# 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
|
||||
def _model_action_urgency(self, md) -> float:
|
||||
action = getattr(md, 'action', None)
|
||||
if action is None:
|
||||
return 0.0
|
||||
|
||||
# Calculate urgency based on trajectory shortage
|
||||
if endpoint_x < expected_distance:
|
||||
shortage = expected_distance - endpoint_x
|
||||
shortage_ratio = shortage / expected_distance
|
||||
urgency = 1.0 if getattr(action, 'shouldStop', False) else 0.0
|
||||
desired_accel = getattr(action, 'desiredAcceleration', 0.0)
|
||||
if desired_accel < WMACConstants.MODEL_DECEL_START:
|
||||
urgency = max(urgency, min(1.0, (WMACConstants.MODEL_DECEL_START - desired_accel) / WMACConstants.MODEL_DECEL_RANGE))
|
||||
return urgency
|
||||
|
||||
# Base urgency on shortage ratio
|
||||
urgency = min(1.0, shortage_ratio * 2.0)
|
||||
def _endpoint_urgency(self, endpoint_x: float, expected_distance: float) -> float:
|
||||
if endpoint_x >= expected_distance:
|
||||
return 0.0
|
||||
|
||||
# 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)
|
||||
shortage_ratio = (expected_distance - endpoint_x) / expected_distance
|
||||
urgency = min(1.0, shortage_ratio * WMACConstants.ENDPOINT_URGENCY_GAIN)
|
||||
|
||||
# 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)
|
||||
if endpoint_x < expected_distance * WMACConstants.CRITICAL_ENDPOINT_FACTOR:
|
||||
urgency = min(1.0, urgency * WMACConstants.CRITICAL_URGENCY_GAIN)
|
||||
|
||||
# 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
|
||||
if self._v_ego_kph > WMACConstants.SPEED_URGENCY_MIN:
|
||||
speed_factor = 1.0 + (self._v_ego_kph - WMACConstants.SPEED_URGENCY_MIN) / WMACConstants.SPEED_URGENCY_RANGE
|
||||
urgency = min(1.0, urgency * speed_factor)
|
||||
|
||||
# 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
|
||||
return urgency
|
||||
|
||||
def _radarless_mode(self) -> None:
|
||||
"""Radarless mode decision logic with emergency handling."""
|
||||
def _desired_mode(self) -> tuple[ModeType, bool]:
|
||||
if not self._CP.radarUnavailable and self._has_radar_acc_lead:
|
||||
return 'acc', False
|
||||
|
||||
# EMERGENCY: MPC FCW - immediate blended mode
|
||||
if self._has_mpc_fcw:
|
||||
self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
|
||||
return
|
||||
return 'blended', True
|
||||
|
||||
# Standstill: use blended
|
||||
if self._standstill_count > 3:
|
||||
self._mode_manager.request_mode('blended', confidence=0.9)
|
||||
return
|
||||
standstill = self._standstill_count > WMACConstants.STANDSTILL_FRAMES
|
||||
urgent_slow_down = self._has_slow_down and self._raw_urgency > WMACConstants.URGENT_SLOW_DOWN_PROB
|
||||
|
||||
# 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
|
||||
if self._CP.radarUnavailable:
|
||||
if standstill or self._has_slow_down:
|
||||
return 'blended', urgent_slow_down
|
||||
return 'acc', False
|
||||
|
||||
# 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
|
||||
if standstill or self._has_slow_down:
|
||||
return 'blended', urgent_slow_down
|
||||
|
||||
# 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)
|
||||
return 'acc', False
|
||||
|
||||
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()
|
||||
|
||||
mode, immediate = self._desired_mode()
|
||||
self._mode_manager.request_mode(mode, immediate=immediate, hold_frames=WMACConstants.EMERGENCY_HOLD_FRAMES,
|
||||
cancel_hold=self._has_radar_acc_lead)
|
||||
self._mode_manager.update()
|
||||
|
||||
self._active = sm['selfdriveState'].experimentalMode and self._enabled
|
||||
self._frame += 1
|
||||
|
||||
@@ -1,94 +0,0 @@
|
||||
import pytest
|
||||
|
||||
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
|
||||
|
||||
class MockLeadOne:
|
||||
def __init__(self, status=0.0):
|
||||
self.status = status
|
||||
|
||||
class MockRadarState:
|
||||
def __init__(self, status=0.0):
|
||||
self.leadOne = MockLeadOne(status=status)
|
||||
|
||||
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
|
||||
|
||||
@pytest.fixture
|
||||
def default_sm():
|
||||
sm = {
|
||||
'carState': MockCarState(vEgo=10.0, vCruise=20.0),
|
||||
'radarState': MockRadarState(status=1.0),
|
||||
'modelV2': MockModelData(valid=True),
|
||||
'selfdriveState': MockSelfDriveState(experimentalMode=True),
|
||||
}
|
||||
return sm
|
||||
|
||||
@pytest.fixture
|
||||
def mock_cp():
|
||||
class CP:
|
||||
radarUnavailable = False
|
||||
return CP()
|
||||
|
||||
@pytest.fixture
|
||||
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
|
||||
|
||||
def test_initial_mode_is_acc(mock_cp, mock_mpc):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
def test_standstill_triggers_blended(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(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(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) # Ensure urgency triggers slowdown
|
||||
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"
|
||||
@@ -0,0 +1,235 @@
|
||||
import pytest
|
||||
|
||||
from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController, HysteresisSignal
|
||||
|
||||
|
||||
class MockLeadOne:
|
||||
def __init__(self, status=0.0, dRel=30.0, vRel=0.0):
|
||||
self.status = status
|
||||
self.dRel = dRel
|
||||
self.vRel = vRel
|
||||
|
||||
|
||||
class MockRadarState:
|
||||
def __init__(self, status=0.0, dRel=30.0, vRel=0.0):
|
||||
self.leadOne = MockLeadOne(status=status, dRel=dRel, vRel=vRel)
|
||||
|
||||
|
||||
class MockCarState:
|
||||
def __init__(self, vEgo=0.0, vCruise=0.0, standstill=False):
|
||||
self.vEgo = vEgo
|
||||
self.vCruise = vCruise
|
||||
self.standstill = standstill
|
||||
|
||||
|
||||
class MockAction:
|
||||
def __init__(self, desiredAcceleration=0.0, shouldStop=False):
|
||||
self.desiredAcceleration = desiredAcceleration
|
||||
self.shouldStop = shouldStop
|
||||
|
||||
|
||||
class MockModelData:
|
||||
def __init__(self, valid=True, endpoint_x=200.0, orientation_valid=None, desired_acceleration=0.0, should_stop=False):
|
||||
position_size = 33 if valid else 10
|
||||
orientation_size = position_size if orientation_valid is None else (33 if orientation_valid else 10)
|
||||
position_x = [0.0] * position_size
|
||||
if position_x:
|
||||
position_x[-1] = endpoint_x
|
||||
self.position = type("Pos", (), {"x": position_x})()
|
||||
self.orientation = type("Ori", (), {"x": [0.0] * orientation_size})()
|
||||
self.acceleration = type("Accel", (), {"x": [0.0] * position_size})()
|
||||
self.action = MockAction(desired_acceleration, should_stop)
|
||||
|
||||
|
||||
class MockSelfDriveState:
|
||||
def __init__(self, experimentalMode=False):
|
||||
self.experimentalMode = experimentalMode
|
||||
|
||||
|
||||
class MockParams:
|
||||
def get_bool(self, name):
|
||||
return True
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def default_sm():
|
||||
sm = {
|
||||
'carState': MockCarState(vEgo=10.0, vCruise=20.0),
|
||||
'radarState': MockRadarState(status=1.0),
|
||||
'modelV2': MockModelData(valid=True),
|
||||
'selfdriveState': MockSelfDriveState(experimentalMode=True),
|
||||
}
|
||||
return sm
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_cp():
|
||||
class CP:
|
||||
radarUnavailable = False
|
||||
return CP()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_mpc():
|
||||
class MPC:
|
||||
crash_cnt = 0
|
||||
return MPC()
|
||||
|
||||
|
||||
def test_initial_mode_is_acc(mock_cp, mock_mpc):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_standstill_triggers_blended(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['carState'].standstill = True
|
||||
for _ in range(20):
|
||||
controller.update(default_sm)
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_emergency_blended_on_fcw(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
mock_mpc.crash_cnt = 1
|
||||
controller.update(default_sm)
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_radarless_slowdown_triggers_blended(mock_cp, mock_mpc, default_sm):
|
||||
mock_cp.radarUnavailable = True
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_valid_position_with_missing_orientation_can_trigger_slowdown(mock_cp, mock_mpc, default_sm):
|
||||
mock_cp.radarUnavailable = True
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0, orientation_valid=False)
|
||||
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._trajectory_valid
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_incomplete_position_does_not_trigger_slowdown(mock_cp, mock_mpc, default_sm):
|
||||
mock_cp.radarUnavailable = True
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=False, endpoint_x=0.0)
|
||||
|
||||
for _ in range(3):
|
||||
controller.update(default_sm)
|
||||
|
||||
assert not controller._trajectory_valid
|
||||
assert not controller._has_slow_down
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_slowdown_hysteresis_prevents_threshold_chatter():
|
||||
signal = HysteresisSignal(enter_threshold=0.5, exit_threshold=0.4, rise_rate=1.0, fall_rate=1.0)
|
||||
|
||||
assert signal.update(0.55)
|
||||
assert signal.update(0.45)
|
||||
assert not signal.update(0.35)
|
||||
|
||||
|
||||
def test_model_should_stop_triggers_blended_without_valid_trajectory(mock_cp, mock_mpc, default_sm):
|
||||
mock_cp.radarUnavailable = True
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=False, should_stop=True)
|
||||
|
||||
controller.update(default_sm)
|
||||
|
||||
assert not controller._trajectory_valid
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_radar_lead_keeps_acc_over_model_slowdown(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
|
||||
for _ in range(3):
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_slow_down
|
||||
assert controller._has_radar_acc_lead
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_far_radar_lead_allows_blended_until_acc_relevant(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0, dRel=120.0, vRel=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_lead_filtered
|
||||
assert not controller._has_radar_acc_lead
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
|
||||
def test_relevant_radar_lead_smoothly_returns_to_acc(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0, dRel=120.0, vRel=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
controller.update(default_sm)
|
||||
assert controller.mode() == "blended"
|
||||
|
||||
default_sm['radarState'] = MockRadarState(status=1.0, dRel=45.0, vRel=0.0)
|
||||
for _ in range(20):
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_radar_acc_lead
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_closing_far_radar_lead_returns_to_acc(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0, dRel=120.0, vRel=-25.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
|
||||
for _ in range(20):
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_radar_acc_lead
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_radar_lead_keeps_acc_over_fcw_and_standstill(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0)
|
||||
default_sm['carState'].standstill = True
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0, should_stop=True)
|
||||
mock_mpc.crash_cnt = 1
|
||||
|
||||
for _ in range(10):
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_lead_filtered
|
||||
assert controller._has_mpc_fcw
|
||||
assert controller.mode() == "acc"
|
||||
|
||||
|
||||
def test_lead_flicker_hold_prevents_one_frame_mode_flip(mock_cp, mock_mpc, default_sm):
|
||||
controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
|
||||
default_sm['radarState'] = MockRadarState(status=1.0)
|
||||
controller.update(default_sm)
|
||||
|
||||
default_sm['radarState'] = MockRadarState(status=0.0)
|
||||
default_sm['modelV2'] = MockModelData(valid=True, endpoint_x=0.0)
|
||||
controller.update(default_sm)
|
||||
|
||||
assert controller._has_lead_filtered
|
||||
assert controller.mode() == "acc"
|
||||
Reference in New Issue
Block a user