Euro NCAP 2026 无响应驾驶员干预：ESF 紧急停车功能详解

发布时间： 2026-06-14
标签： Euro NCAP 2026, 无响应驾驶员, ESF, 紧急停车, DMS-ADAS 协同
来源： Euro NCAP 官方协议, Smart Eye

---

核心场景：驾驶员突然失去意识

当驾驶员因突发疾病、严重疲劳或损伤而完全失去响应时，DMS 必须触发 紧急停车功能（ESF：Emergency Stop Function），将车辆安全停靠。

---

Euro NCAP 2026 无响应检测要求

1. 检测触发条件

触发条件	描述	检测时限
闭眼持续	双眼闭合 >10 秒	持续监控
无转向输入	方向盘无动作 >15 秒	结合眼动追踪
无脚踏输入	油门/刹车无动作 >15 秒	结合眼动追踪
头部下垂	头部姿态异常（低头/后仰）	持续监控

2. 检测流程

持续监控驾驶员状态
       ↓
  检测到异常信号
  (闭眼/无转向/无踏板)
       ↓
  ┌────┴────┐
  │ 警告阶段 │ (5秒)
  │ 声音+振动 │
  └────┬────┘
       ↓
   无响应？
       ↓
  ┌────┴────┐
  │升级警告 │ (10秒)
  │闪烁+鸣笛 │
  └────┬────┘
       ↓
   无响应？
       ↓
  ┌────┴────┐
  │紧急停车 │ (ESF)
  │减速+靠边 │
  └────┬────┘
       ↓
  ┌────┴────┐
  │呼叫救援 │ (eCall)
  └─────────┘

---

ESF 紧急停车功能要求

1. 功能定义

功能	描述
减速控制	逐渐减速至停车（-2m/s² 至 -4m/s²）
车道保持	保持当前车道或安全变道
靠边停车	如有路肩，缓慢靠边
危险警告灯	自动开启双闪
电子驻车	停车后自动驻车
紧急呼叫	通过 eCall 联系救援

2. 性能要求

指标	要求
减速范围	-2m/s² 至 -4m/s²
停车距离	<100m（从检测到停止）
车道保持	减速过程中不偏离车道
响应时间	检测后 <5秒 开始减速

---

DMS-ADAS 协同架构

graph TB
    subgraph DMS
    A[眼动追踪] --> D[状态融合]
    B[头部姿态] --> D
    C[转向输入] --> D
    end
    
    D --> E{无响应判定}
    
    E -->|是| F[警告系统]
    F --> G{警告响应}
    
    G -->|无响应| H[ESF 激活]
    
    subgraph ADAS
    H --> I[减速控制]
    H --> J[车道保持]
    H --> K[靠边停车]
    end
    
    K --> L[危险警告灯]
    K --> M[eCall]

---

代码实现

1. 无响应检测器

import time
import numpy as np
from enum import Enum
from dataclasses import dataclass
from typing import Optional, Dict

class DriverState(Enum):
    """驾驶员状态枚举"""
    NORMAL = "normal"
    WARNING = "warning"
    CRITICAL = "critical"
    UNRESPONSIVE = "unresponsive"

@dataclass
class DriverMonitoringData:
    """驾驶员监控数据"""
    timestamp: float
    
    # 眼动数据
    eyes_closed: bool = False
    eyes_closed_duration: float = 0.0
    
    # 头部姿态
    head_pitch: float = 0.0
    head_yaw: float = 0.0
    head_roll: float = 0.0
    head_drooping: bool = False
    
    # 驾驶输入
    steering_input: bool = False
    pedal_input: bool = False
    last_steering_time: float = 0.0
    last_pedal_time: float = 0.0
    
    # 车辆状态
    vehicle_speed: float = 0.0
    lane_position: float = 0.0

class UnresponsiveDriverDetector:
    """
    无响应驾驶员检测器
    
    符合 Euro NCAP 2026 标准
    """
    
    def __init__(self):
        # 检测阈值（秒）
        self.eyes_closed_threshold = 10.0
        self.no_input_threshold = 15.0
        self.warning_duration = 5.0
        self.escalation_duration = 10.0
        
        # 状态
        self.current_state = DriverState.NORMAL
        self.state_start_time: Optional[float] = None
        self.warning_count = 0
        
    def update(self, data: DriverMonitoringData) -> Dict:
        """
        更新驾驶员状态
        
        Args:
            data: 驾驶员监控数据
        
        Returns:
            状态更新结果
        """
        current_time = data.timestamp
        result = {
            'state': self.current_state.value,
            'action': None,
            'confidence': 0.0
        }
        
        # 检测无响应信号
        unresponsive_signals = self._detect_unresponsive_signals(data, current_time)
        
        if self.current_state == DriverState.NORMAL:
            if unresponsive_signals['detected']:
                self._transition_to(DriverState.WARNING, current_time)
                result['action'] = 'INITIAL_WARNING'
        
        elif self.current_state == DriverState.WARNING:
            if not unresponsive_signals['detected']:
                self._transition_to(DriverState.NORMAL, current_time)
                result['action'] = 'CANCEL_WARNING'
            elif self._time_in_state(current_time) >= self.warning_duration:
                self._transition_to(DriverState.CRITICAL, current_time)
                result['action'] = 'ESCALATION_WARNING'
        
        elif self.current_state == DriverState.CRITICAL:
            if not unresponsive_signals['detected']:
                self._transition_to(DriverState.NORMAL, current_time)
                result['action'] = 'CANCEL_WARNING'
            elif self._time_in_state(current_time) >= self.escalation_duration:
                self._transition_to(DriverState.UNRESPONSIVE, current_time)
                result['action'] = 'ACTIVATE_ESF'
        
        elif self.current_state == DriverState.UNRESPONSIVE:
            # 保持 ESF 激活直到驾驶员响应或车辆停止
            if data.vehicle_speed < 0.5:
                result['action'] = 'VEHICLE_STOPPED'
        
        result['confidence'] = unresponsive_signals['confidence']
        
        return result
    
    def _detect_unresponsive_signals(self, data: DriverMonitoringData,
                                     current_time: float) -> Dict:
        """
        检测无响应信号
        
        Returns:
            {
                'detected': bool,
                'signals': list,
                'confidence': float
            }
        """
        signals = []
        
        # 1. 闭眼检测
        if data.eyes_closed_duration >= self.eyes_closed_threshold:
            signals.append('EYES_CLOSED_EXTENDED')
        
        # 2. 头部下垂检测
        if data.head_drooping:
            signals.append('HEAD_DROOPING')
        
        # 3. 无转向输入
        time_since_steering = current_time - data.last_steering_time
        if time_since_steering >= self.no_input_threshold:
            signals.append('NO_STEERING_INPUT')
        
        # 4. 无踏板输入
        time_since_pedal = current_time - data.last_pedal_time
        if time_since_pedal >= self.no_input_threshold:
            signals.append('NO_PEDAL_INPUT')
        
        # 综合判断
        detected = len(signals) >= 1
        
        # 置信度计算
        confidence = min(1.0, len(signals) / 3.0)
        
        return {
            'detected': detected,
            'signals': signals,
            'confidence': confidence
        }
    
    def _transition_to(self, new_state: DriverState, current_time: float):
        """状态转换"""
        self.current_state = new_state
        self.state_start_time = current_time
    
    def _time_in_state(self, current_time: float) -> float:
        """在当前状态的时间"""
        if self.state_start_time is None:
            return 0.0
        return current_time - self.state_start_time

2. ESF 控制器

import numpy as np
from enum import Enum
from typing import Dict, Optional

class ESFState(Enum):
    """ESF 状态"""
    INACTIVE = "inactive"
    DECELERATING = "decelerating"
    STOPPING = "stopping"
    STOPPED = "stopped"

class EmergencyStopFunction:
    """
    紧急停车功能（ESF）
    
    Euro NCAP 2026 合规
    """
    
    def __init__(self):
        self.state = ESFState.INACTIVE
        self.deceleration_target = -3.0  # m/s²
        
        # 车辆控制参数
        self.max_decel = -4.0  # m/s²
        self.min_decel = -2.0  # m/s²
        self.target_stop_distance = 100.0  # m
        
        # 车道保持参数
        self.lane_keep_gain = 0.1
        self.max_steering_rate = 10.0  # deg/s
        
    def activate(self, vehicle_speed: float, lane_position: float) -> Dict:
        """
        激活 ESF
        
        Args:
            vehicle_speed: 当前车速 (m/s)
            lane_position: 车道位置 (-1 到 1)
        
        Returns:
            控制指令
        """
        self.state = ESFState.DECELERATING
        
        return {
            'deceleration': self._calculate_deceleration(vehicle_speed),
            'steering_angle': self._calculate_steering(lane_position),
            'hazard_lights': True,
            'horn': True,
            'ecall': True
        }
    
    def update(self, vehicle_speed: float, lane_position: float) -> Dict:
        """
        更新 ESF 控制
        
        Returns:
            控制指令
        """
        if self.state == ESFState.INACTIVE:
            return {'active': False}
        
        # 减速控制
        decel = self._calculate_deceleration(vehicle_speed)
        
        # 车道保持
        steering = self._calculate_steering(lane_position)
        
        # 检查是否停止
        if vehicle_speed < 0.5:
            self.state = ESFState.STOPPED
            return {
                'deceleration': 0.0,
                'steering_angle': 0.0,
                'hazard_lights': True,
                'parking_brake': True,
                'ecall': True,
                'stopped': True
            }
        
        return {
            'deceleration': decel,
            'steering_angle': steering,
            'hazard_lights': True,
            'horn': False
        }
    
    def _calculate_deceleration(self, vehicle_speed: float) -> float:
        """
        计算减速度指令
        
        目标：在 target_stop_distance 内停车
        """
        if vehicle_speed < 0.5:
            return 0.0
        
        # 计算所需减速度
        # v² = 2as → a = v²/(2s)
        required_decel = -vehicle_speed**2 / (2 * self.target_stop_distance)
        
        # 限制在允许范围内
        decel = np.clip(required_decel, self.max_decel, self.min_decel)
        
        return decel
    
    def _calculate_steering(self, lane_position: float) -> float:
        """
        计算转向角度
        
        目标：保持车道中心
        """
        # PID 控制（简化版）
        steering = -self.lane_keep_gain * lane_position
        
        # 限制转向速率
        steering = np.clip(steering, -self.max_steering_rate, self.max_steering_rate)
        
        return steering
    
    def deactivate(self):
        """取消 ESF"""
        self.state = ESFState.INACTIVE


# 完整系统集成
class DMS_ADAS_Integration:
    """
    DMS-ADAS 集成系统
    """
    
    def __init__(self):
        self.unresponsive_detector = UnresponsiveDriverDetector()
        self.esf = EmergencyStopFunction()
        
    def process(self, monitoring_data: DriverMonitoringData) -> Dict:
        """
        处理监控数据并返回控制指令
        
        Returns:
            {
                'driver_state': str,
                'warning_level': int,
                'esf_active': bool,
                'control_commands': dict
            }
        """
        result = {
            'driver_state': 'normal',
            'warning_level': 0,
            'esf_active': False,
            'control_commands': None
        }
        
        # 更新无响应检测
        detection_result = self.unresponsive_detector.update(monitoring_data)
        result['driver_state'] = detection_result['state']
        
        # 根据动作类型处理
        action = detection_result['action']
        
        if action == 'INITIAL_WARNING':
            result['warning_level'] = 1
            result['control_commands'] = {
                'audio_alert': True,
                'visual_alert': True,
                'haptic_alert': False
            }
        
        elif action == 'ESCALATION_WARNING':
            result['warning_level'] = 2
            result['control_commands'] = {
                'audio_alert': True,
                'visual_alert': True,
                'haptic_alert': True,
                'horn': True
            }
        
        elif action == 'ACTIVATE_ESF':
            result['esf_active'] = True
            result['control_commands'] = self.esf.activate(
                monitoring_data.vehicle_speed,
                monitoring_data.lane_position
            )
        
        elif self.unresponsive_detector.current_state == DriverState.UNRESPONSIVE:
            # ESF 已激活，持续更新
            result['esf_active'] = True
            result['control_commands'] = self.esf.update(
                monitoring_data.vehicle_speed,
                monitoring_data.lane_position
            )
        
        return result


# 使用示例
if __name__ == "__main__":
    system = DMS_ADAS_Integration()
    
    # 模拟驾驶员失去意识场景
    for i in range(30):
        data = DriverMonitoringData(
            timestamp=i,
            eyes_closed=True,
            eyes_closed_duration=i,
            head_drooping=True if i > 5 else False,
            last_steering_time=0,
            last_pedal_time=0,
            vehicle_speed=30.0 - i * 1.0,  # 逐渐减速
            lane_position=0.1
        )
        
        result = system.process(data)
        
        print(f"[{i}s] State: {result['driver_state']}, "
              f"Warning: {result['warning_level']}, "
              f"ESF: {result['esf_active']}")

---

对 IMS 开发的启示

1. 功能优先级

优先级	功能	技术方案
P0	无响应检测	眼动 + 转向 + 踏板融合
P0	警告系统	声音 + 振动 + 闪烁
P1	ESF 控制	减速 + 车道保持
P1	eCall 集成	紧急呼叫

2. DMS-ADAS 接口

接口	方向	数据
DMS → ADAS	输出	驾驶员状态、警告级别、ESF 激活信号
ADAS → DMS	输入	车速、车道位置、转向输入、踏板输入

3. 测试场景

场景	触发条件	预期结果
UR-01	闭眼 10 秒	初始警告
UR-02	闭眼 15 秒	升级警告
UR-03	闭眼 25 秒	ESF 激活
UR-04	ESF 激活后	车辆减速停车

---

参考资料

1. Euro NCAP 2026 Protocols: https://www.euroncap.com/en/for-engineers/protocols/2026-protocols/
2. Smart Eye Euro NCAP 2026: https://smarteye.se/blog/euro-ncap-2026-whats-changing/

---

总结

Euro NCAP 2026 无响应驾驶员干预要求：

1. 多信号融合检测： 闭眼 + 无转向 + 无踏板
2. 分级警告： 初始警告 → 升级警告 → ESF 激活
3. ESF 功能： 减速 + 车道保持 + 靠边停车
4. 紧急呼叫： 自动 eCall

对 IMS 开发，DMS-ADAS 接口设计与多信号融合是关键技术难点。