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| class DaimlerSafetyFusion:
"""
Daimler Truck 270° 传感器融合安全系统
传感器组合：
- 6× 短距雷达（两侧+前角）
- 1× 多功能摄像头（前视）
- 1× 红外DMS摄像头（车内）
"""
SENSORS = {
"long_range_radar": {
"range_m": 250,
"field_of_view_deg": 18,
"count": 1,
"purpose": "前方车辆检测",
},
"short_range_radar": {
"range_m": 100,
"field_of_view_deg": 150,
"count": 6,
"purpose": "侧方/交叉交通检测",
"coverage": "270度环绕",
},
"multifunction_camera": {
"range_m": 200,
"field_of_view_deg": 52,
"count": 1,
"purpose": "车道标线/交通标志/物体分类",
},
"infrared_dms_camera": {
"range_m": 1.5,
"field_of_view_deg": 60,
"count": 1,
"purpose": "驾驶员状态监测",
"privacy": "no_storage",
},
}
def assess_risk(
self,
driver_state: str,
cross_traffic: dict,
side_traffic: dict,
speed_kmh: float,
) -> dict:
"""
多系统融合风险评估
关键创新：DMS状态影响安全系统响应阈值
- 正常：标准警告序列
- 疲劳：提前触发警告
- 分心：降低自动制动触发阈值
- 微睡眠：立即启动紧急制动准备
"""
risk_level = 0
response_plan = []
driver_risk = {
"normal": 0,
"fatigued": 0.2,
"distracted": 0.3,
"microsleep": 0.5,
}
risk_adjustment = driver_risk.get(driver_state, 0)
if cross_traffic.get("approaching", False):
collision_time = cross_traffic.get("ttc_sec", 999)
threshold = 3.0 - risk_adjustment * 3.0
if collision_time < threshold:
risk_level = max(risk_level, 3)
response_plan.append("cross_traffic_warning")
if collision_time < threshold * 0.5:
risk_level = max(risk_level, 4)
response_plan.append("partial_brake")
if collision_time < threshold * 0.3:
risk_level = max(risk_level, 5)
response_plan.append("full_automatic_brake")
if side_traffic.get("oncoming", False) and speed_kmh < 40:
risk_level = max(risk_level, 2)
response_plan.append("turn_warning")
if risk_adjustment > 0.2 and speed_kmh < 20:
response_plan.append("auto_brake_turn")
if driver_state == "microsleep":
response_plan.insert(0, "emergency_brake_preparation")
response_plan.append("acoustic_shock_warning")
return {
"risk_level": risk_level,
"response": response_plan,
"driver_risk_adjustment": risk_adjustment,
"speed": speed_kmh,
}
if __name__ == "__main__":
system = DaimlerSafetyFusion()
r1 = system.assess_risk("normal", {"approaching": True, "ttc_sec": 2.0}, {}, 80)
print(f"正常+交叉交通: 风险{r1['risk_level']}, 响应={r1['response']}")
r2 = system.assess_risk("distracted", {"approaching": True, "ttc_sec": 2.0}, {}, 80)
print(f"分心+交叉交通: 风险{r2['risk_level']}, 响应={r2['response']}")
r3 = system.assess_risk("microsleep", {"approaching": True, "ttc_sec": 4.0}, {}, 60)
print(f"微睡眠+交叉交通: 风险{r3['risk_level']}, 响应={r3['response']}")
|