分析手动和自动驾驶汽车混合驾驶中的安全风险:多种视角
Yaqin He1, Jun Xia1, Jiayin Dai1
1School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan, Hubei, China.
PloS one
|May 15, 2025
概括
这项研究确定了自动驾驶汽车 (AV) 和人类驾驶员在混合交通中的关键安全风险. 调查结果突出了影响事故严重程度和紧急制动的诸如周日,道路类型和不利条件等因素.
科学领域:
- 交通安全 交通安全 交通安全
- 自主系统 自主系统
- 人与计算机的交互
背景情况:
- 与自动驾驶汽车 (AV) 混合的交通环境带来了独特的安全挑战.
- 了解风险因素对于制定有效的安全策略至关重要.
研究的目的:
- 在涉及人类驾驶和自动驾驶车辆的混合交通中识别和分析安全风险因素.
- 调查影响事故严重程度和紧急制动事件的因素.
- 检查各种交通参与者的风险感知.
主要方法:
- XGBoost算法和沙普利增量解释 (SHAP) 用于分析来自加利福尼亚州自动驾驶汽车的撞车数据.
- 协会规则挖掘来自中国的无人驾驶出租车数据,以研究应急制动.
- 使用问卷数据进行风险感知的攻击性方法的平均程度.
主要成果:
- 混合交通中的风险因素包括周日,特定路段,多条车道,中央中道,缺乏控制和不利的环境条件.
- 分析揭示了事故严重程度和紧急制动事件的关键预测因素.
- 交通参与者对风险的看法各不相同,受攻击性等因素的影响.
结论:
- 混合交通安全受到环境,道路和运营因素的结合的影响.
- 针对特定风险因素的有针对性的干预措施可以提高交通安全.
- 建议进一步研究人类-AV相互作用和风险感知.
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