100 lines
5.3 KiB
Python
100 lines
5.3 KiB
Python
#!/usr/bin/env python3
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import numpy as np
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from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import COMFORT_BRAKE, STOP_DISTANCE, desired_follow_distance, get_jerk_factor, get_T_FOLLOW
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from openpilot.frogpilot.common.frogpilot_variables import CITY_SPEED_LIMIT, MAX_T_FOLLOW
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TRAFFIC_MODE_BP = [0., CITY_SPEED_LIMIT]
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class FrogPilotFollowing:
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def __init__(self, FrogPilotPlanner):
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self.frogpilot_planner = FrogPilotPlanner
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self.following_lead = False
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self.slower_lead = False
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self.acceleration_jerk = 0
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self.danger_jerk = 0
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self.desired_follow_distance = 0
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self.speed_jerk = 0
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self.t_follow = 0
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def update(self, v_ego, sm, frogpilot_toggles):
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if sm["controlsState"].enabled and sm["frogpilotCarState"].trafficModeEnabled:
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if sm["carState"].aEgo >= 0:
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self.base_acceleration_jerk = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_acceleration))
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self.base_speed_jerk = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_speed))
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else:
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self.base_acceleration_jerk = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_deceleration))
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self.base_speed_jerk = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_speed_decrease))
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self.base_danger_jerk = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_danger))
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self.t_follow = float(np.interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_follow))
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elif sm["controlsState"].enabled:
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if sm["carState"].aEgo >= 0:
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self.base_acceleration_jerk, self.base_danger_jerk, self.base_speed_jerk = get_jerk_factor(
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frogpilot_toggles.aggressive_jerk_acceleration, frogpilot_toggles.aggressive_jerk_danger, frogpilot_toggles.aggressive_jerk_speed,
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frogpilot_toggles.standard_jerk_acceleration, frogpilot_toggles.standard_jerk_danger, frogpilot_toggles.standard_jerk_speed,
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frogpilot_toggles.relaxed_jerk_acceleration, frogpilot_toggles.relaxed_jerk_danger, frogpilot_toggles.relaxed_jerk_speed,
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frogpilot_toggles.custom_personalities, sm["controlsState"].personality
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)
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else:
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self.base_acceleration_jerk, self.base_danger_jerk, self.base_speed_jerk = get_jerk_factor(
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frogpilot_toggles.aggressive_jerk_deceleration, frogpilot_toggles.aggressive_jerk_danger, frogpilot_toggles.aggressive_jerk_speed_decrease,
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frogpilot_toggles.standard_jerk_deceleration, frogpilot_toggles.standard_jerk_danger, frogpilot_toggles.standard_jerk_speed_decrease,
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frogpilot_toggles.relaxed_jerk_deceleration, frogpilot_toggles.relaxed_jerk_danger, frogpilot_toggles.relaxed_jerk_speed_decrease,
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frogpilot_toggles.custom_personalities, sm["controlsState"].personality
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)
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self.t_follow = get_T_FOLLOW(
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frogpilot_toggles.aggressive_follow,
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frogpilot_toggles.standard_follow,
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frogpilot_toggles.relaxed_follow,
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frogpilot_toggles.custom_personalities, sm["controlsState"].personality
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)
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else:
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self.base_acceleration_jerk = 0
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self.base_danger_jerk = 0
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self.base_speed_jerk = 0
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self.t_follow = 0
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self.acceleration_jerk = self.base_acceleration_jerk
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self.danger_jerk = self.base_danger_jerk
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self.speed_jerk = self.base_speed_jerk
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self.following_lead = self.frogpilot_planner.tracking_lead and self.frogpilot_planner.lead_one.dRel < (self.t_follow * 2) * v_ego
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if self.frogpilot_planner.frogpilot_weather.weather_id != 0:
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self.t_follow = min(self.t_follow + self.frogpilot_planner.frogpilot_weather.increase_following_distance, MAX_T_FOLLOW)
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if sm["controlsState"].enabled and self.frogpilot_planner.tracking_lead:
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if not sm["frogpilotCarState"].trafficModeEnabled:
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self.update_follow_values(self.frogpilot_planner.lead_one.dRel, v_ego, self.frogpilot_planner.lead_one.vLead, frogpilot_toggles)
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self.desired_follow_distance = int(desired_follow_distance(v_ego, self.frogpilot_planner.lead_one.vLead, self.t_follow))
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else:
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self.desired_follow_distance = 0
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def update_follow_values(self, lead_distance, v_ego, v_lead, frogpilot_toggles):
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# Offset by FrogAi for FrogPilot for a more natural approach to a faster lead
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if frogpilot_toggles.human_following and v_lead > v_ego:
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distance_factor = max(lead_distance - (v_ego * self.t_follow), 1)
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accelerating_offset = float(np.clip(STOP_DISTANCE - v_ego, 1, distance_factor))
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self.acceleration_jerk /= accelerating_offset
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self.speed_jerk /= accelerating_offset
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self.t_follow /= accelerating_offset
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# Offset by FrogAi for FrogPilot for a more natural approach to a slower lead
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if (frogpilot_toggles.conditional_slower_lead or frogpilot_toggles.human_following) and v_lead < v_ego:
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distance_factor = max(lead_distance - (v_lead * self.t_follow), 1)
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braking_offset = float(np.clip(min(v_ego - v_lead, v_lead) - COMFORT_BRAKE, 1, distance_factor))
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if frogpilot_toggles.human_following:
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if not self.following_lead and v_lead > CITY_SPEED_LIMIT:
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far_lead_offset = max(lead_distance - (v_ego * self.t_follow) - STOP_DISTANCE, 0)
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else:
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far_lead_offset = 0
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self.t_follow /= braking_offset + far_lead_offset
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self.slower_lead = braking_offset > 1
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