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| """
Euro NCAP 2026 分心检测评分
10分评分标准实现
评分逻辑：
- D-01 长分心（3-4秒）：3分
- D-02 手机使用（耳旁）：2分
- D-03 手机使用（打字）：2分
- D-04 短分心（10秒累积）：1分
- D-05 短分心（30秒累积）：1分
- D-06 VATS：1分
满分条件：
- 所有6个场景均通过
- 总分 = 3+2+2+1+1+1 = 10分
"""
from typing import Dict, Tuple
from dataclasses import dataclass
@dataclass
class DistractionTestResult:
"""分心检测测试结果"""
scenario_id: str
scenario_name: str
max_score: int
achieved_score: int
passed: bool
detection_latency_sec: float
warning_latency_sec: float
criteria_met: str
class DistractionScoringEngine:
"""
分心检测评分引擎
Euro NCAP 2026分心检测评分标准：
D-01 长分心（3-4秒）：
- 检测条件：注视偏离道路3-4秒
- 通过标准：≤3秒触发一级警告
- 分值：3分
D-02 手机使用（耳旁）：
- 检测条件：手持手机至耳边
- 通过标准：≤3秒触发一级警告
- 分值：2分
D-03 手机使用（打字）：
- 检测条件：低头打字操作
- 通过标准：≤3秒触发一级警告
- 分值：2分
D-04 短分心（10秒累积）：
- 检测条件：多次短分心累积10秒
- 通过标准：累积判定触发警告
- 分值：1分
D-05 短分心（30秒累积）：
- 检测条件：多次短分心累积30秒
- 通过标准：累积判定触发二级警告
- 分值：1分
D-06 VATS视觉注意力时间：
- 检测条件：注视道路时间占比
- 通过标准：VATS≥70%
- 分值：1分
"""
def __init__(self):
self.long_distraction_sec = 3.0
self.short_distraction_10_sec = 10.0
self.short_distraction_30_sec = 30.0
self.vats_threshold = 0.70
self.warning_latency_threshold_sec = 3.0
def score_d01_long_distraction(self,
detection_latency_sec: float,
warning_latency_sec: float) -> DistractionTestResult:
"""
D-01 长分心（3-4秒）评分
通过条件：
- 检测到注视偏离道路3-4秒
- ≤3秒触发一级警告
- 警告内容：视觉+听觉
Args:
detection_latency_sec: 检测时延
warning_latency_sec: 警告时延
Returns:
DistractionTestResult: 测试结果
"""
passed = warning_latency_sec <= self.warning_latency_threshold_sec
achieved_score = 3 if passed else 0
return DistractionTestResult(
scenario_id='D-01',
scenario_name='长分心（3-4秒）',
max_score=3,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=detection_latency_sec,
warning_latency_sec=warning_latency_sec,
criteria_met=f"警告时延{warning_latency_sec:.1f}s {'≤' if passed else '>'}3s"
)
def score_d02_phone_ear(self,
detection_latency_sec: float,
warning_latency_sec: float) -> DistractionTestResult:
"""
D-02 手机使用（耳旁）评分
通过条件：≤3秒触发一级警告
分值：2分
"""
passed = warning_latency_sec <= self.warning_latency_threshold_sec
achieved_score = 2 if passed else 0
return DistractionTestResult(
scenario_id='D-02',
scenario_name='手机使用（耳旁）',
max_score=2,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=detection_latency_sec,
warning_latency_sec=warning_latency_sec,
criteria_met=f"警告时延{warning_latency_sec:.1f}s {'≤' if passed else '>'}3s"
)
def score_d03_phone_texting(self,
detection_latency_sec: float,
warning_latency_sec: float) -> DistractionTestResult:
"""
D-03 手机使用（打字）评分
通过条件：≤3秒触发一级警告
分值：2分
"""
passed = warning_latency_sec <= self.warning_latency_threshold_sec
achieved_score = 2 if passed else 0
return DistractionTestResult(
scenario_id='D-03',
scenario_name='手机使用（打字）',
max_score=2,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=detection_latency_sec,
warning_latency_sec=warning_latency_sec,
criteria_met=f"警告时延{warning_latency_sec:.1f}s {'≤' if passed else '>'}3s"
)
def score_d04_short_distraction_10s(self,
cumulative_distraction_sec: float,
warning_triggered: bool) -> DistractionTestResult:
"""
D-04 短分心（10秒累积）评分
通过条件：多次短分心累积10秒触发警告
分值：1分
"""
passed = warning_triggered and cumulative_distraction_sec >= self.short_distraction_10_sec
achieved_score = 1 if passed else 0
return DistractionTestResult(
scenario_id='D-04',
scenario_name='短分心（10秒累积）',
max_score=1,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=cumulative_distraction_sec,
warning_latency_sec=0,
criteria_met=f"累积分心{cumulative_distraction_sec:.1f}s {'≥' if passed else '<'}10s"
)
def score_d05_short_distraction_30s(self,
cumulative_distraction_sec: float,
warning_triggered: bool) -> DistractionTestResult:
"""
D-05 短分心（30秒累积）评分
通过条件：多次短分心累积30秒触发二级警告
分值：1分
"""
passed = warning_triggered and cumulative_distraction_sec >= self.short_distraction_30_sec
achieved_score = 1 if passed else 0
return DistractionTestResult(
scenario_id='D-05',
scenario_name='短分心（30秒累积）',
max_score=1,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=cumulative_distraction_sec,
warning_latency_sec=0,
criteria_met=f"累积分心{cumulative_distraction_sec:.1f}s {'≥' if passed else '<'}30s"
)
def score_d06_vats(self,
gaze_road_ratio: float) -> DistractionTestResult:
"""
D-06 VATS视觉注意力时间评分
通过条件：注视道路时间占比≥70%
分值：1分
"""
passed = gaze_road_ratio >= self.vats_threshold
achieved_score = 1 if passed else 0
return DistractionTestResult(
scenario_id='D-06',
scenario_name='VATS视觉注意力时间',
max_score=1,
achieved_score=achieved_score,
passed=passed,
detection_latency_sec=0,
warning_latency_sec=0,
criteria_met=f"VATS {gaze_road_ratio:.1%} {'≥' if passed else '<'}70%"
)
def compute_total_distraction_score(self,
results: list) -> Dict:
"""
计算分心检测总分
Args:
results: 所有场景测试结果列表
Returns:
total_score: 总分结果
"""
total_achieved = sum(r.achieved_score for r in results)
total_max = sum(r.max_score for r in results)
return {
'total_achieved': total_achieved,
'total_max': total_max,
'percentage': total_achieved / total_max * 100 if total_max > 0 else 0,
'scenario_results': results,
'full_score_possible': total_achieved == total_max
}
if __name__ == "__main__":
engine = DistractionScoringEngine()
print("=== Euro NCAP 2026 分心检测评分测试 ===")
results = []
r1 = engine.score_d01_long_distraction(2.5, 2.8)
results.append(r1)
print(f"\n{r1.scenario_id} {r1.scenario_name}：")
print(f" 得分：{r1.achieved_score}/{r1.max_score}")
print(f" 判定：{r1.criteria_met}")
r2 = engine.score_d02_phone_ear(2.0, 2.5)
results.append(r2)
print(f"\n{r2.scenario_id} {r2.scenario_name}：")
print(f" 得分：{r2.achieved_score}/{r2.max_score}")
print(f" 判定：{r2.criteria_met}")
r3 = engine.score_d03_phone_texting(2.8, 3.2)
results.append(r3)
print(f"\n{r3.scenario_id} {r3.scenario_name}：")
print(f" 得分：{r3.achieved_score}/{r3.max_score}")
print(f" 判定：{r3.criteria_met}")
r4 = engine.score_d04_short_distraction_10s(12.0, True)
results.append(r4)
print(f"\n{r4.scenario_id} {r4.scenario_name}：")
print(f" 得分：{r4.achieved_score}/{r4.max_score}")
print(f" 判定：{r4.criteria_met}")
r5 = engine.score_d05_short_distraction_30s(25.0, False)
results.append(r5)
print(f"\n{r5.scenario_id} {r5.scenario_name}：")
print(f" 得分：{r5.achieved_score}/{r5.max_score}")
print(f" 判定：{r5.criteria_met}")
r6 = engine.score_d06_vats(0.75)
results.append(r6)
print(f"\n{r6.scenario_id} {r6.scenario_name}：")
print(f" 得分：{r6.achieved_score}/{r6.max_score}")
print(f" 判定：{r6.criteria_met}")
total = engine.compute_total_distraction_score(results)
print(f"\n=== 分心检测总分 ===")
print(f" 得分：{total['total_achieved']}/{total['total_max']}")
print(f" 百分比：{total['percentage']:.1f}%")
print(f" 满分可能：{total['full_score_possible']}")
|