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| """
座舱雷达+摄像头传感器融合系统
参考: Tesla/Murata/Magna 量产方案
融合策略: 决策级融合 (Late Fusion)
- 摄像头: 驾驶员行为/表情/视线
- 雷达: 生命体征/存在检测/微动作
- 融合: 贝叶斯加权 + 冲突解决
"""
import numpy as np
from dataclasses import dataclass
from typing import Optional, Dict, List
from collections import deque
@dataclass
class RadarOutput:
"""雷达感知输出"""
presence_detected: bool
num_occupants: int
avg_heart_rate: float
avg_breathing_rate: float
movement_intensity: float
position_estimate: tuple
child_detected: bool
@dataclass
class CameraOutput:
"""摄像头感知输出"""
face_detected: bool
eye_openness: float
gaze_direction: tuple
head_pose: tuple
expression: str
behavior: str
confidence: float
@dataclass
class FusedOutput:
"""融合输出"""
occupant_present: bool
occupant_category: str
drowsiness_level: int
distraction_level: int
heart_rate: float
breathing_rate: float
position: tuple
alerts: List[str]
class RadarCameraFusion:
"""
雷达+摄像头决策级融合
融合规则:
1. 存在检测: 雷达为主(穿透遮挡), 摄像头为辅
2. 疲劳检测: 摄像头为主(面部), 雷达为辅(心率变异性)
3. CPD: 雷达为主(穿透), 摄像头辅助验证
4. 行为: 摄像头为主, 雷达运动强度辅助
"""
def __init__(self):
self.radar_weight_presence = 0.7
self.camera_weight_presence = 0.3
self.radar_weight_drowsiness = 0.3
self.camera_weight_drowsiness = 0.7
def fuse(self, radar: RadarOutput, camera: CameraOutput) -> FusedOutput:
"""执行融合"""
occupant_present = self._fuse_presence(radar, camera)
category = self._classify_occupant(radar, camera)
drowsiness = self._fuse_drowsiness(radar, camera)
distraction = self._assess_distraction(camera)
hr = radar.avg_heart_rate if radar.avg_heart_rate > 0 else 0
br = radar.avg_breathing_rate if radar.avg_breathing_rate > 0 else 0
alerts = self._generate_alerts(
drowsiness, distraction, category, radar
)
return FusedOutput(
occupant_present=occupant_present,
occupant_category=category,
drowsiness_level=drowsiness,
distraction_level=distraction,
heart_rate=hr,
breathing_rate=br,
position=radar.position_estimate,
alerts=alerts
)
def _fuse_presence(self, radar, camera):
"""存在检测融合"""
if radar.presence_detected:
return True
if camera.face_detected:
return True
return False
def _classify_occupant(self, radar, camera):
"""乘员分类"""
if not radar.presence_detected and not camera.face_detected:
return 'empty'
if radar.child_detected:
return 'child'
if radar.movement_intensity < 0.1 and not camera.face_detected:
return 'unknown_occupant'
return 'adult'
def _fuse_drowsiness(self, radar, camera):
"""疲劳融合 (0-3)"""
cam_score = 0
if camera.eye_openness < 0.3:
cam_score += 2
elif camera.eye_openness < 0.5:
cam_score += 1
if camera.expression == 'tired':
cam_score += 1
cam_score = min(cam_score, 3)
radar_score = 0
if 50 < radar.avg_heart_rate < 60:
radar_score += 1
if radar.avg_breathing_rate < 12:
radar_score += 1
radar_score = min(radar_score, 3)
fused = (
self.camera_weight_drowsiness * cam_score +
self.radar_weight_drowsiness * radar_score
)
return int(round(fused))
def _assess_distraction(self, camera):
"""分心评估"""
if not camera.face_detected:
return 0
if camera.behavior in ('phone', 'eating'):
return 3
if abs(camera.gaze_direction[0]) > 30:
return 2
if camera.behavior == 'distracted':
return 2
return 0
def _generate_alerts(self, drowsiness, distraction, category, radar):
"""生成警报"""
alerts = []
if drowsiness >= 2:
alerts.append(f'疲劳警告(L{drowsiness})')
if distraction >= 2:
alerts.append(f'分心警告(L{distraction})')
if category == 'child':
alerts.append('儿童检测警报')
if radar.avg_heart_rate > 120:
alerts.append('心率异常')
return alerts
if __name__ == "__main__":
fusion = RadarCameraFusion()
radar1 = RadarOutput(
presence_detected=True, num_occupants=1,
avg_heart_rate=72, avg_breathing_rate=16,
movement_intensity=0.3,
position_estimate=(0.5, 0.3, 1.2),
child_detected=False
)
cam1 = CameraOutput(
face_detected=True, eye_openness=0.8,
gaze_direction=(5, -5, 0),
head_pose=(0, 0, 0),
expression='neutral', behavior='driving',
confidence=0.95
)
result1 = fusion.fuse(radar1, cam1)
print("场景1: 正常驾驶")
print(f" 乘员: {result1.occupant_category}")
print(f" 疲劳: L{result1.drowsiness_level}")
print(f" 分心: L{result1.distraction_level}")
print(f" 心率: {result1.heart_rate} bpm")
print(f" 警报: {result1.alerts}")
radar2 = RadarOutput(
presence_detected=True, num_occupants=1,
avg_heart_rate=55, avg_breathing_rate=11,
movement_intensity=0.05,
position_estimate=(0.5, 0.3, 1.2),
child_detected=False
)
cam2 = CameraOutput(
face_detected=True, eye_openness=0.15,
gaze_direction=(0, 10, 0),
head_pose=(5, 0, 0),
expression='tired', behavior='driving',
confidence=0.88
)
result2 = fusion.fuse(radar2, cam2)
print("\n场景2: 疲劳驾驶")
print(f" 乘员: {result2.occupant_category}")
print(f" 疲劳: L{result2.drowsiness_level}")
print(f" 心率: {result2.heart_rate} bpm (低)")
print(f" 警报: {result2.alerts}")
radar3 = RadarOutput(
presence_detected=True, num_occupants=2,
avg_heart_rate=90, avg_breathing_rate=22,
movement_intensity=0.4,
position_estimate=(1.2, 0.5, 0.8),
child_detected=True
)
cam3 = CameraOutput(
face_detected=False, eye_openness=0,
gaze_direction=(0, 0, 0),
head_pose=(0, 0, 0),
expression='neutral', behavior='driving',
confidence=0.3
)
result3 = fusion.fuse(radar3, cam3)
print("\n场景3: 后排儿童 (CPD)")
print(f" 乘员: {result3.occupant_category}")
print(f" 位置: {result3.position}")
print(f" 警报: {result3.alerts}")
|