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232 lines
9.8 KiB
232 lines
9.8 KiB
import numpy as np
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from common.realtime import DT_CTRL, DT_DMON
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from selfdrive.controls.lib.drive_helpers import create_event, EventTypes as ET
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from common.filter_simple import FirstOrderFilter
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from common.stat_live import RunningStatFilter
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_AWARENESS_TIME = 100. # 1.6 minutes limit without user touching steering wheels make the car enter a terminal status
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_AWARENESS_PRE_TIME_TILL_TERMINAL = 25. # a first alert is issued 25s before expiration
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_AWARENESS_PROMPT_TIME_TILL_TERMINAL = 15. # a second alert is issued 15s before start decelerating the car
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_DISTRACTED_TIME = 11.
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_DISTRACTED_PRE_TIME_TILL_TERMINAL = 8.
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_DISTRACTED_PROMPT_TIME_TILL_TERMINAL = 6.
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_FACE_THRESHOLD = 0.4
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_EYE_THRESHOLD = 0.6
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_BLINK_THRESHOLD = 0.5 # 0.225
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_BLINK_THRESHOLD_SLACK = 0.65
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_BLINK_THRESHOLD_STRICT = 0.5
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_PITCH_WEIGHT = 1.35 # 1.5 # pitch matters a lot more
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_METRIC_THRESHOLD = 0.4
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_METRIC_THRESHOLD_SLACK = 0.55
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_METRIC_THRESHOLD_STRICT = 0.4
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_PITCH_POS_ALLOWANCE = 0.12 # rad, to not be too sensitive on positive pitch
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_PITCH_NATURAL_OFFSET = 0.02 # people don't seem to look straight when they drive relaxed, rather a bit up
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_YAW_NATURAL_OFFSET = 0.08 # people don't seem to look straight when they drive relaxed, rather a bit to the right (center of car)
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_DISTRACTED_FILTER_TS = 0.25 # 0.6Hz
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_POSE_CALIB_MIN_SPEED = 13 # 30 mph
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_POSE_OFFSET_MIN_COUNT = 600 # valid data counts before calibration completes, 1 seg is 600 counts
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_POSE_OFFSET_MAX_COUNT = 3600 # stop deweighting new data after 6 min, aka "short term memory"
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_RECOVERY_FACTOR_MAX = 5. # relative to minus step change
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_RECOVERY_FACTOR_MIN = 1.25 # relative to minus step change
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MAX_TERMINAL_ALERTS = 3 # not allowed to engage after 3 terminal alerts
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MAX_TERMINAL_DURATION = 3000 # 30s
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# model output refers to center of cropped image, so need to apply the x displacement offset
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RESIZED_FOCAL = 320.0
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H, W, FULL_W = 320, 160, 426
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class DistractedType():
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NOT_DISTRACTED = 0
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BAD_POSE = 1
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BAD_BLINK = 2
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def face_orientation_from_net(angles_desc, pos_desc, rpy_calib):
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# the output of these angles are in device frame
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# so from driver's perspective, pitch is up and yaw is right
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pitch_net = angles_desc[0]
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yaw_net = angles_desc[1]
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roll_net = angles_desc[2]
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face_pixel_position = ((pos_desc[0] + .5)*W - W + FULL_W, (pos_desc[1]+.5)*H)
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yaw_focal_angle = np.arctan2(face_pixel_position[0] - FULL_W//2, RESIZED_FOCAL)
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pitch_focal_angle = np.arctan2(face_pixel_position[1] - H//2, RESIZED_FOCAL)
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roll = roll_net
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pitch = pitch_net + pitch_focal_angle
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yaw = -yaw_net + yaw_focal_angle
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# no calib for roll
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pitch -= rpy_calib[1]
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yaw -= rpy_calib[2]
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return np.array([roll, pitch, yaw])
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class DriverPose():
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def __init__(self):
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self.yaw = 0.
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self.pitch = 0.
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self.roll = 0.
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self.pitch_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
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self.yaw_offseter = RunningStatFilter(max_trackable=_POSE_OFFSET_MAX_COUNT)
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self.cfactor = 1.
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class DriverBlink():
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def __init__(self):
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self.left_blink = 0.
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self.right_blink = 0.
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self.cfactor = 1.
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class DriverStatus():
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def __init__(self):
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self.pose = DriverPose()
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self.pose_calibrated = self.pose.pitch_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT and \
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self.pose.yaw_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT
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self.blink = DriverBlink()
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self.awareness = 1.
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self.awareness_active = 1.
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self.awareness_passive = 1.
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self.driver_distracted = False
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self.driver_distraction_filter = FirstOrderFilter(0., _DISTRACTED_FILTER_TS, DT_DMON)
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self.face_detected = False
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self.terminal_alert_cnt = 0
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self.terminal_time = 0
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self.step_change = 0.
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self.active_monitoring_mode = True
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self.threshold_prompt = _DISTRACTED_PROMPT_TIME_TILL_TERMINAL / _DISTRACTED_TIME
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self.is_rhd_region = False
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self.is_rhd_region_checked = False
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self._set_timers(active_monitoring=True)
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def _set_timers(self, active_monitoring):
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if self.active_monitoring_mode and self.awareness <= self.threshold_prompt:
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if active_monitoring:
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self.step_change = DT_CTRL / _DISTRACTED_TIME
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else:
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self.step_change = 0.
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return # no exploit after orange alert
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elif self.awareness <= 0.:
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return
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if active_monitoring:
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# when falling back from passive mode to active mode, reset awareness to avoid false alert
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if not self.active_monitoring_mode:
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self.awareness_passive = self.awareness
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self.awareness = self.awareness_active
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self.threshold_pre = _DISTRACTED_PRE_TIME_TILL_TERMINAL / _DISTRACTED_TIME
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self.threshold_prompt = _DISTRACTED_PROMPT_TIME_TILL_TERMINAL / _DISTRACTED_TIME
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self.step_change = DT_CTRL / _DISTRACTED_TIME
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self.active_monitoring_mode = True
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else:
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if self.active_monitoring_mode:
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self.awareness_active = self.awareness
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self.awareness = self.awareness_passive
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self.threshold_pre = _AWARENESS_PRE_TIME_TILL_TERMINAL / _AWARENESS_TIME
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self.threshold_prompt = _AWARENESS_PROMPT_TIME_TILL_TERMINAL / _AWARENESS_TIME
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self.step_change = DT_CTRL / _AWARENESS_TIME
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self.active_monitoring_mode = False
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def _is_driver_distracted(self, pose, blink):
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if not self.pose_calibrated:
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pitch_error = pose.pitch - _PITCH_NATURAL_OFFSET
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yaw_error = pose.yaw - _YAW_NATURAL_OFFSET
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else:
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pitch_error = pose.pitch - self.pose.pitch_offseter.filtered_stat.mean()
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yaw_error = pose.yaw - self.pose.yaw_offseter.filtered_stat.mean()
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# positive pitch allowance
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if pitch_error > 0.:
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pitch_error = max(pitch_error - _PITCH_POS_ALLOWANCE, 0.)
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pitch_error *= _PITCH_WEIGHT
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pose_metric = np.sqrt(yaw_error**2 + pitch_error**2)
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if pose_metric > _METRIC_THRESHOLD*pose.cfactor:
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return DistractedType.BAD_POSE
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elif (blink.left_blink + blink.right_blink)*0.5 > _BLINK_THRESHOLD*blink.cfactor:
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return DistractedType.BAD_BLINK
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else:
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return DistractedType.NOT_DISTRACTED
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def set_policy(self, model_data):
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ep = min(model_data.meta.engagedProb, 0.8) / 0.8
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self.pose.cfactor = np.interp(ep, [0, 0.5, 1], [_METRIC_THRESHOLD_STRICT, _METRIC_THRESHOLD, _METRIC_THRESHOLD_SLACK])/_METRIC_THRESHOLD
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self.blink.cfactor = np.interp(ep, [0, 0.5, 1], [_BLINK_THRESHOLD_STRICT, _BLINK_THRESHOLD, _BLINK_THRESHOLD_SLACK])/_BLINK_THRESHOLD
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def get_pose(self, driver_monitoring, cal_rpy, car_speed, op_engaged):
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# 10 Hz
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if len(driver_monitoring.faceOrientation) == 0 or len(driver_monitoring.facePosition) == 0:
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return
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self.pose.roll, self.pose.pitch, self.pose.yaw = face_orientation_from_net(driver_monitoring.faceOrientation, driver_monitoring.facePosition, cal_rpy)
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self.blink.left_blink = driver_monitoring.leftBlinkProb * (driver_monitoring.leftEyeProb>_EYE_THRESHOLD)
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self.blink.right_blink = driver_monitoring.rightBlinkProb * (driver_monitoring.rightEyeProb>_EYE_THRESHOLD)
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self.face_detected = driver_monitoring.faceProb > _FACE_THRESHOLD and \
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abs(driver_monitoring.facePosition[0]) <= 0.4 and abs(driver_monitoring.facePosition[1]) <= 0.45 and \
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not self.is_rhd_region
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self.driver_distracted = self._is_driver_distracted(self.pose, self.blink)>0
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# first order filters
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self.driver_distraction_filter.update(self.driver_distracted)
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# update offseter
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# only update when driver is actively driving the car above a certain speed
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if self.face_detected and car_speed>_POSE_CALIB_MIN_SPEED and (not op_engaged or not self.driver_distracted):
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self.pose.pitch_offseter.push_and_update(self.pose.pitch)
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self.pose.yaw_offseter.push_and_update(self.pose.yaw)
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self.pose_calibrated = self.pose.pitch_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT and \
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self.pose.yaw_offseter.filtered_stat.n > _POSE_OFFSET_MIN_COUNT
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self._set_timers(self.face_detected)
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def update(self, events, driver_engaged, ctrl_active, standstill):
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if (driver_engaged and self.awareness > 0) or not ctrl_active:
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# reset only when on disengagement if red reached
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self.awareness = 1.
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self.awareness_active = 1.
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self.awareness_passive = 1.
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return events
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driver_attentive = self.driver_distraction_filter.x < 0.37
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awareness_prev = self.awareness
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if (driver_attentive and self.face_detected and self.awareness > 0):
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# only restore awareness when paying attention and alert is not red
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self.awareness = min(self.awareness + ((_RECOVERY_FACTOR_MAX-_RECOVERY_FACTOR_MIN)*(1.-self.awareness)+_RECOVERY_FACTOR_MIN)*self.step_change, 1.)
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if self.awareness == 1.:
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self.awareness_passive = min(self.awareness_passive + self.step_change, 1.)
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# don't display alert banner when awareness is recovering and has cleared orange
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if self.awareness > self.threshold_prompt:
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return events
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# should always be counting if distracted unless at standstill and reaching orange
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if (not self.face_detected or (self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected)) and \
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not (standstill and self.awareness - self.step_change <= self.threshold_prompt):
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self.awareness = max(self.awareness - self.step_change, -0.1)
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alert = None
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if self.awareness <= 0.:
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# terminal red alert: disengagement required
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alert = 'driverDistracted' if self.active_monitoring_mode else 'driverUnresponsive'
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self.terminal_time += 1
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if awareness_prev > 0.:
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self.terminal_alert_cnt += 1
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elif self.awareness <= self.threshold_prompt:
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# prompt orange alert
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alert = 'promptDriverDistracted' if self.active_monitoring_mode else 'promptDriverUnresponsive'
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elif self.awareness <= self.threshold_pre:
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# pre green alert
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alert = 'preDriverDistracted' if self.active_monitoring_mode else 'preDriverUnresponsive'
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if alert is not None:
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events.append(create_event(alert, [ET.WARNING]))
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return events
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