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| """
Euro NCAP 2026酒驾损伤检测
醉酒驾驶眼动特征识别
"""
import numpy as np
class EuroNCAPAlcoholImpairmentDetection:
"""Euro NCAP酒驾损伤检测
核心特征：
- 醉酒眼动特征：眼球震颤（Nystagmus）
- 头部姿态异常：晃动/不稳定
- 反应迟缓：视线切换延迟
Euro NCAP要求：
- 实时眼动+头部追踪连续监测
- 醉酒识别得分纳入DSM评分
- 技术人员佩戴眼动追踪眼镜测试
"""
def __init__(self):
self.alcohol_impairment_features = {
'眼球震颤': {
'医学名称': 'Nystagmus',
'醉酒表现': '眼球不规则震颤',
'检测方法': '眼动轨迹FFT分析',
'频率范围': '1-4 Hz震颤'
},
'视线切换延迟': {
'正常反应': '<500ms',
'醉酒反应': '>800ms',
'检测方法': '视线切换时间测量',
'阈值': '>800ms判损伤'
},
'头部姿态异常': {
'醉酒表现': '头部晃动不稳定',
'检测方法': '头部姿态稳定性分析',
'指标': '姿态变化频率'
},
'瞳孔异常': {
'醉酒表现': '瞳孔对光反应迟缓',
'检测方法': '瞳孔直径变化检测',
'阈值': '对光反应延迟>200ms'
}
}
self.euro_ncap_scoring = {
'疲劳检测': '原有评分',
'分心检测': '原有评分',
'酒驾损伤检测': '新增评分',
'药物损伤检测': '新增评分',
'测试方法': '眼动追踪眼镜测试',
'评分标准': '实时眼动+头部追踪'
}
def detect_nystagmus(self, eye_movement_sequence: np.ndarray) -> dict:
"""
检测眼球震颤
Args:
eye_movement_sequence: 眼动序列
Returns:
nystagmus_result: 震颤检测结果
"""
fft_result = np.fft.fft(eye_movement_sequence)
freqs = np.fft.fftfreq(len(eye_movement_sequence))
tremor_power = np.sum(np.abs(fft_result)**2 *
((freqs >= 1) & (freqs <= 4)))
is_nystagmus = tremor_power > 0.5
return {
'tremor_power': tremor_power,
'is_nystagmus': is_nystagmus,
'freq_range': '1-4 Hz'
}
def measure_response_delay(self,
stimulus_time: float,
response_time: float) -> dict:
"""
测量视线切换延迟
Args:
stimulus_time: 刺激时间
response_time: 响应时间
Returns:
delay_result: 延迟检测结果
"""
delay = response_time - stimulus_time
is_impairment = delay > 800
return {
'response_delay_ms': delay,
'is_impairment': is_impairment,
'threshold_ms': 800
}
def detect_alcohol_impairment(self,
eye_movement: np.ndarray,
response_delay: float) -> dict:
"""
酒驾损伤检测
Args:
eye_movement: 眼动序列
response_delay: 响应延迟
Returns:
impairment_result: 损伤检测结果
"""
nystagmus = self.detect_nystagmus(eye_movement)
delay_result = self.measure_response_delay(0, response_delay)
is_alcohol_impairment = (
nystagmus['is_nystagmus'] or
delay_result['is_impairment']
)
return {
'nystagmus_detected': nystagmus['is_nystagmus'],
'response_delay_ms': delay_result['response_delay_ms'],
'is_alcohol_impairment': is_alcohol_impairment,
'euro_ncap_scoring': 'DSM酒驾损伤得分'
}
if __name__ == "__main__":
detector = EuroNCAPAlcoholImpairmentDetection()
print("Euro NCAP 2026酒驾损伤检测：")
print("=" * 70)
print("\n酒驾损伤特征:")
for feature, specs in detector.alcohol_impairment_features.items():
print(f"\n{feature}:")
for key, value in specs.items():
print(f" {key}: {value}")
print("\nEuro NCAP DSM评分构成:")
for key, value in detector.euro_ncap_scoring.items():
print(f" {key}: {value}")
print("\n酒驾损伤检测测试:")
print("-" * 70)
normal_eye = np.random.normal(0, 0.05, 100)
print("\n正常状态测试:")
result_normal = detector.detect_alcohol_impairment(normal_eye, 400)
print(f" 眼球震颤检测: {result_normal['nystagmus_detected']}")
print(f" 响应延迟: {result_normal['response_delay_ms']}ms")
print(f" 醉酒损伤判定: {result_normal['is_alcohol_impairment']}")
drunk_eye = np.sin(np.linspace(0, 10, 100) * 2) + np.random.normal(0, 0.02, 100)
print("\n醉酒状态测试:")
result_drunk = detector.detect_alcohol_impairment(drunk_eye, 900)
print(f" 眼球震颤检测: {result_drunk['nystagmus_detected']}")
print(f" 响应延迟: {result_drunk['response_delay_ms']}ms")
print(f" 醉酒损伤判定: {result_drunk['is_alcohol_impairment']}")
print(f" Euro NCAP评分: {result_drunk['euro_ncap_scoring']}")
print("\nIMS集成建议:")
print(" - 眼球震颤检测新增于疲劳检测")
print(" - 响应延迟测量新增于分心检测")
print(" - Euro NCAP DSM酒驾损伤得分纳入")
print(" - 多模态融合（眼动+头部+瞳孔）")
|