从对人类驾驶汽车驾驶员与自动驾驶汽车互动的心理生理学工作负载分析得出的见解
Hoseon Kim1, Jieun Ko2, Cheol Oh2
1Department of Smart City Engineering, Hanyang University, ERICA Campus, 55 Hanynagdaehak-ro, Sangnok-gu, Ansan-city, Gyeonggi-do 15588, the Republic of Korea.
Accident; analysis and prevention
|September 25, 2025
概括
在混合交通中,自动驾驶汽车 (AV) 的决策应该考虑人类驾驶员的压力. 整合心理生理学数据,如驾驶员焦虑,提高了与手动驾驶汽车 (MV) 交互期间的安全性和舒适性.
科学领域:
- 交通工程是交通工程.
- 人类因素工程 人类因素工程
- 自主系统 自主系统
背景情况:
- 评估在混合交通中自动驾驶汽车 (AV) 的行为对于城市安全至关重要.
- 了解人类驾驶员对自动驾驶汽车的反应对于无集成至关重要.
研究的目的:
- 通过包括手动驾驶车辆 (MV) 驾驶员的心理生理工作负载来开发评估AV行为的方法.
- 在混合交通场景中为AV决策建立以人为中心的行为门.
主要方法:
- 使用多代理驾驶模拟 (MADS) 平台来同步AV和MV交互.
- 使用电脑电图 (EEG) 信号测量了MV驾驶员的压力,以获得焦虑和紧张指数 (ANI).
- 分析了ANI和侵占后时间 (PET) 之间的关系,以此来衡量机潜力.
主要成果:
- 在驾驶员焦虑 (ANI) 和入侵后时间 (PET) 之间发现了显著的反向关系.
- 随着PET的增加,驾驶员的焦虑程度下降,超过2.7秒的回报率下降 (边际改善点-MIP).
- 建议基于PET值的AV决策协议,以平衡交通流量和人类舒适性.
结论:
- 视听行为必须整合人类的心理反应,而不仅仅是技术性能.
- 该研究为自动驾驶汽车建立了以人为中心的门,提高了混合交通中的可靠性和安全性.
- 调查结果为在城市交叉路口更安全的AV-MV交互提供了基础.
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