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Controls - Longitudinal Tuning - Lead Detection Threshold

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Increase or decrease the lead detection threshold to either detect leads sooner, or increase model confidence.
This commit is contained in:
FrogAi 2024-05-10 12:56:42 -07:00
parent 48169cfba3
commit 51776c2e14
1 changed files with 5 additions and 5 deletions
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10
selfdrive/controls/radard.py
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@ -168,9 +168,9 @@ def get_RadarState_from_vision(lead_msg: capnp._DynamicStructReader, v_ego: floa
def get_lead(v_ego: float, ready: bool, tracks: dict[int, Track], lead_msg: capnp._DynamicStructReader, def get_lead(v_ego: float, ready: bool, tracks: dict[int, Track], lead_msg: capnp._DynamicStructReader,
model_v_ego: float, low_speed_override: bool = True) -> dict[str, Any]: model_v_ego: float, lead_detection_threshold: float, low_speed_override: bool = True) -> dict[str, Any]:
# Determine leads, this is where the essential logic happens # Determine leads, this is where the essential logic happens
if len(tracks) > 0 and ready and lead_msg.prob > .5: if len(tracks) > 0 and ready and lead_msg.prob > lead_detection_threshold:
track = match_vision_to_track(v_ego, lead_msg, tracks) track = match_vision_to_track(v_ego, lead_msg, tracks)
else: else:
track = None track = None
@ -178,7 +178,7 @@ def get_lead(v_ego: float, ready: bool, tracks: dict[int, Track], lead_msg: capn
lead_dict = {'status': False} lead_dict = {'status': False}
if track is not None: if track is not None:
lead_dict = track.get_RadarState(lead_msg.prob) lead_dict = track.get_RadarState(lead_msg.prob)
elif (track is None) and ready and (lead_msg.prob > .5): elif (track is None) and ready and (lead_msg.prob > lead_detection_threshold):
lead_dict = get_RadarState_from_vision(lead_msg, v_ego, model_v_ego) lead_dict = get_RadarState_from_vision(lead_msg, v_ego, model_v_ego)
if low_speed_override: if low_speed_override:
@ -261,8 +261,8 @@ class RadarD:
model_v_ego = self.v_ego model_v_ego = self.v_ego
leads_v3 = sm['modelV2'].leadsV3 leads_v3 = sm['modelV2'].leadsV3
if len(leads_v3) > 1: if len(leads_v3) > 1:
self.radar_state.leadOne = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[0], model_v_ego, low_speed_override=True) self.radar_state.leadOne = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[0], model_v_ego, self.frogpilot_toggles.lead_detection_threshold, low_speed_override=True)
self.radar_state.leadTwo = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[1], model_v_ego, low_speed_override=False) self.radar_state.leadTwo = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[1], model_v_ego, self.frogpilot_toggles.lead_detection_threshold, low_speed_override=False)
# Update FrogPilot parameters # Update FrogPilot parameters
if FrogPilotVariables.toggles_updated: if FrogPilotVariables.toggles_updated: