DMS与ADAS协同：无响应驾驶员紧急停车系统设计

来源： Euro NCAP 2026 Protocol + Smart Eye
发布时间： 2026年4月
核心价值： 无响应驾驶员干预是Euro NCAP 2026新增要求

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核心洞察

无响应驾驶员检测流程：

检测流程
         │
         ├── 1. DMS检测驾驶员无响应
         │   ├── 视线长时间闭眼
         │   ├── 头部下垂
         │   └── 无操作响应
         │
         ├── 2. 分级警告
         │   ├── 一级警告（5秒）
         │   └── 二级警告（10秒）
         │
         ├── 3. ADAS介入
         │   ├── 增加FCW灵敏度
         │   ├── 车道保持激活
         │   └── 减速
         │
         └── 4. 紧急停车
              ├── 靠边停车
              ├── 开启双闪
              └── 呼叫救援

Euro NCAP 2026要求：

• 无响应检测必须在15秒内触发干预
• 必须有紧急停车能力
• 可以获得5分评分

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一、无响应检测

1.1 检测指标

指标	阈值	时间窗口
双眼闭合	PERCLOS > 80%	5秒
头部下垂	俯仰角 > 30°	3秒
无操作	方向盘/踏板无输入	10秒
无响应警告	不对警告做出反应	5秒

1.2 检测系统实现

"""
无响应驾驶员检测系统
"""

import numpy as np
from enum import Enum
from dataclasses import dataclass
from typing import Optional, List
from collections import deque
import time

class DriverState(Enum):
    """驾驶员状态"""
    NORMAL = "normal"
    ATTENTION_LOST = "attention_lost"
    UNRESPONSIVE = "unresponsive"
    EMERGENCY = "emergency"

class InterventionLevel(Enum):
    """干预等级"""
    NONE = 0
    WARNING_1 = 1  # 一级警告
    WARNING_2 = 2  # 二级警告
    ADAS_TAKEOVER = 3  # ADAS接管
    EMERGENCY_STOP = 4  # 紧急停车

@dataclass
class DriverMetrics:
    """驾驶员指标"""
    eye_openness: float       # 眼睑开度 (0-1)
    head_pitch: float         # 头部俯仰角 (度)
    head_yaw: float           # 头部偏航角 (度)
    steering_activity: float  # 方向盘活动 (0-1)
    pedal_activity: float     # 踏板活动 (0-1)
    response_to_warning: bool # 是否响应警告

class UnresponsiveDriverDetector:
    """
    无响应驾驶员检测器
    
    Euro NCAP 2026要求：
    - 15秒内检测并触发干预
    - 分级警告机制
    - 紧急停车能力
    """
    
    def __init__(self):
        # 检测阈值
        self.thresholds = {
            'eye_closure': 0.2,     # 眼睑开度阈值
            'head_pitch_down': 30,  # 头部下垂角度
            'no_activity': 0.1,     # 无活动阈值
        }
        
        # 时间阈值（秒）
        self.time_thresholds = {
            'eye_closure_duration': 5,
            'head_down_duration': 3,
            'no_activity_duration': 10,
            'no_response_duration': 5,
        }
        
        # 状态跟踪
        self.current_state = DriverState.NORMAL
        self.state_start_time: Optional[float] = None
        self.warning_start_time: Optional[float] = None
        
        # 历史缓冲
        self.metrics_history = deque(maxlen=300)  # 10秒@30fps
        
        # 检测器
        self.eye_closure_detector = EyeClosureDetector()
        self.head_pose_monitor = HeadPoseMonitor()
        self.activity_monitor = ActivityMonitor()
    
    def update(self, metrics: DriverMetrics) -> tuple:
        """
        更新检测状态
        
        Args:
            metrics: 当前驾驶员指标
            
        Returns:
            (state, intervention_level, info)
        """
        current_time = time.time()
        self.metrics_history.append(metrics)
        
        # 检测各项异常
        eye_closed = self._detect_eye_closure(metrics)
        head_down = self._detect_head_down(metrics)
        no_activity = self._detect_no_activity(metrics)
        
        # 判断状态
        if eye_closed or head_down or no_activity:
            if self.state_start_time is None:
                self.state_start_time = current_time
                self.current_state = DriverState.ATTENTION_LOST
            
            duration = current_time - self.state_start_time
            
            # 判断无响应
            if duration > self.time_thresholds['eye_closure_duration']:
                self.current_state = DriverState.UNRESPONSIVE
        
        else:
            # 恢复正常
            self.state_start_time = None
            self.current_state = DriverState.NORMAL
        
        # 确定干预等级
        intervention = self._determine_intervention(metrics)
        
        info = {
            'state': self.current_state.value,
            'duration': current_time - self.state_start_time if self.state_start_time else 0,
            'eye_closed': eye_closed,
            'head_down': head_down,
            'no_activity': no_activity,
        }
        
        return self.current_state, intervention, info
    
    def _detect_eye_closure(self, metrics: DriverMetrics) -> bool:
        """检测眼睛闭合"""
        return metrics.eye_openness < self.thresholds['eye_closure']
    
    def _detect_head_down(self, metrics: DriverMetrics) -> bool:
        """检测头部下垂"""
        return metrics.head_pitch > self.thresholds['head_pitch_down']
    
    def _detect_no_activity(self, metrics: DriverMetrics) -> bool:
        """检测无活动"""
        return (metrics.steering_activity < self.thresholds['no_activity'] and
                metrics.pedal_activity < self.thresholds['no_activity'])
    
    def _determine_intervention(self, metrics: DriverMetrics) -> InterventionLevel:
        """确定干预等级"""
        if self.current_state == DriverState.NORMAL:
            return InterventionLevel.NONE
        
        duration = time.time() - self.state_start_time if self.state_start_time else 0
        
        # 分级干预
        if duration < 5:
            return InterventionLevel.WARNING_1
        elif duration < 10:
            return InterventionLevel.WARNING_2
        elif duration < 15:
            return InterventionLevel.ADAS_TAKEOVER
        else:
            return InterventionLevel.EMERGENCY_STOP


class EyeClosureDetector:
    """眼睛闭合检测器"""
    
    def __init__(self):
        self.perclos_window = deque(maxlen=150)  # 5秒@30fps
    
    def update(self, eye_openness: float) -> dict:
        """更新检测"""
        self.perclos_window.append(eye_openness < 0.2)
        
        perclos = sum(self.perclos_window) / len(self.perclos_window) * 100
        
        return {
            'perclos': perclos,
            'closed': perclos > 80
        }


class HeadPoseMonitor:
    """头部姿态监控器"""
    
    def __init__(self):
        self.pitch_history = deque(maxlen=90)  # 3秒@30fps
    
    def update(self, pitch: float) -> dict:
        """更新监控"""
        self.pitch_history.append(pitch)
        
        avg_pitch = sum(self.pitch_history) / len(self.pitch_history)
        
        return {
            'avg_pitch': avg_pitch,
            'head_down': avg_pitch > 30
        }


class ActivityMonitor:
    """活动监控器"""
    
    def __init__(self):
        self.steering_history = deque(maxlen=300)
        self.pedal_history = deque(maxlen=300)
    
    def update(self, steering: float, pedal: float) -> dict:
        """更新监控"""
        self.steering_history.append(steering)
        self.pedal_history.append(pedal)
        
        steering_activity = np.std(list(self.steering_history))
        pedal_activity = np.std(list(self.pedal_history))
        
        return {
            'steering_activity': steering_activity,
            'pedal_activity': pedal_activity,
            'no_activity': steering_activity < 0.1 and pedal_activity < 0.1
        }


# 实际测试
if __name__ == "__main__":
    detector = UnresponsiveDriverDetector()
    
    print("=== 无响应驾驶员检测测试 ===")
    
    # 模拟正常驾驶
    print("\n[正常驾驶 5秒]")
    for i in range(150):
        metrics = DriverMetrics(
            eye_openness=0.8,
            head_pitch=5,
            head_yaw=0,
            steering_activity=0.5,
            pedal_activity=0.3,
            response_to_warning=False
        )
        state, intervention, info = detector.update(metrics)
        if i % 50 == 0:
            print(f"  {i//30}s: 状态={state.value}, 干预={intervention.value}")
    
    # 模拟无响应
    print("\n[无响应驾驶员 20秒]")
    for i in range(600):
        # 模拟眼睛闭合
        metrics = DriverMetrics(
            eye_openness=0.1 if i > 30 else 0.8,
            head_pitch=35 if i > 50 else 5,
            head_yaw=0,
            steering_activity=0.02,
            pedal_activity=0.01,
            response_to_warning=False
        )
        state, intervention, info = detector.update(metrics)
        
        if intervention.value >= 1 and i % 30 == 0:
            print(f"  {i//30}s: 状态={state.value}, 干预={intervention.name}, 时长={info['duration']:.1f}s")

---

二、ADAS协同干预

2.1 干预策略

干预等级	措施	时间
一级警告	视觉+听觉警告	5秒
二级警告	触觉+减速警告	10秒
ADAS接管	增加FCW/AEB灵敏度	15秒
紧急停车	靠边停车+双闪+呼叫	20秒

2.2 ADAS接口

"""
ADAS协同干预接口
"""

from dataclasses import dataclass
from typing import Dict, Optional

@dataclass
class ADASCommand:
    """ADAS命令"""
    fcw_sensitivity: float = 1.0     # FCW灵敏度倍数
    aeb_sensitivity: float = 1.0     # AEB灵敏度倍数
    lka_enabled: bool = False        # 车道保持使能
    target_speed: Optional[float] = None  # 目标速度
    pull_over: bool = False          # 靠边停车
    hazard_lights: bool = False      # 双闪灯
    emergency_call: bool = False     # 紧急呼叫

class ADASCoordinator:
    """
    ADAS协同控制器
    
    功能：
    1. 接收DMS无响应信号
    2. 执行分级干预
    3. 协调各ADAS功能
    """
    
    def __init__(self):
        self.current_command = ADASCommand()
        self.intervention_active = False
    
    def execute_intervention(self, 
                            level: InterventionLevel,
                            vehicle_speed: float) -> ADASCommand:
        """
        执行干预
        
        Args:
            level: 干预等级
            vehicle_speed: 当前车速
            
        Returns:
            ADAS命令
        """
        if level == InterventionLevel.NONE:
            return self._reset_command()
        
        elif level == InterventionLevel.WARNING_1:
            # 一级警告：仅HMI
            self.current_command = ADASCommand(
                fcw_sensitivity=1.2,
            )
        
        elif level == InterventionLevel.WARNING_2:
            # 二级警告：准备接管
            self.current_command = ADASCommand(
                fcw_sensitivity=1.5,
                aeb_sensitivity=1.3,
                lka_enabled=True,
            )
        
        elif level == InterventionLevel.ADAS_TAKEOVER:
            # ADAS接管：减速
            self.current_command = ADASCommand(
                fcw_sensitivity=2.0,
                aeb_sensitivity=1.5,
                lka_enabled=True,
                target_speed=max(vehicle_speed * 0.5, 30),  # 减速到50%或30km/h
            )
        
        elif level == InterventionLevel.EMERGENCY_STOP:
            # 紧急停车
            self.current_command = ADASCommand(
                fcw_sensitivity=2.0,
                aeb_sensitivity=2.0,
                lka_enabled=True,
                target_speed=0,
                pull_over=True,
                hazard_lights=True,
                emergency_call=True,
            )
        
        return self.current_command
    
    def _reset_command(self) -> ADASCommand:
        """重置命令"""
        self.current_command = ADASCommand()
        return self.current_command


# 实际测试
if __name__ == "__main__":
    coordinator = ADASCoordinator()
    
    print("=== ADAS协同测试 ===")
    
    for level in InterventionLevel:
        command = coordinator.execute_intervention(level, vehicle_speed=100)
        print(f"\n{level.name}:")
        print(f"  FCW灵敏度: {command.fcw_sensitivity}x")
        print(f"  AEB灵敏度: {command.aeb_sensitivity}x")
        print(f"  LKA使能: {command.lka_enabled}")
        print(f"  目标速度: {command.target_speed}")
        print(f"  靠边停车: {command.pull_over}")
        print(f"  双闪灯: {command.hazard_lights}")
        print(f"  紧急呼叫: {command.emergency_call}")

---

三、Euro NCAP合规

3.1 测试场景

场景	模拟条件	通过标准
场景1	驾驶员闭眼5秒	一级警告
场景2	驾驶员闭眼10秒	二级警告+减速
场景3	驾驶员无响应15秒	ADAS接管
场景4	驾驶员无响应20秒	紧急停车

3.2 评分标准

功能	分值	说明
无响应检测	2分	15秒内检测
警告机制	1分	分级警告
紧急停车	2分	靠边停车能力

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四、总结

4.1 核心要点

1. 多指标融合检测无响应
2. 分级干预降低风险
3. ADAS协同实现安全停车
4. Euro NCAP 2026合规

4.2 技术挑战

• 误报率控制
• 驾驶员恢复检测
• 复杂道路场景处理

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参考链接：

• Euro NCAP 2026 Assessment Protocol
• Smart Eye: Driver Monitoring 2.0
• NHTSA: Automatic Emergency Braking