自动驾驶汽车在现实世界的碰撞场景中会如何表现?
Rui Zhou1, Guoqing Zhang1, Helai Huang1
1School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China.
Accident; analysis and prevention
|April 24, 2024
概括
自动驾驶汽车 (AV) 可以避免超过60%的现实世界碰撞,并减轻其他人的伤害. 无人驾驶汽车的性能优于人类驾驶员,特别是当人类驾驶员表现出异常行为时,提高了整体的交通安全.
科学领域:
- 运输工程 运输工程
- 道路交通安全 道路交通安全
- 人工智能的人工智能
背景情况:
- 自动驾驶汽车 (AV) 承诺提高交通安全.
- 严格的安全测试,特别是在高风险场景中,对于AV部署至关重要.
- 现实世界的崩数据为评估AV能力提供了宝贵的见解.
研究的目的:
- 开发和验证一种新的方法来评估使用真实世界的碰撞数据的AV安全.
- 在模拟撞车场景中评估自动驾驶系统 (ADS) 的安全性能.
- 在复杂的交通情况中确定影响AV安全的关键因素.
主要方法:
- 从CIMSS-TA数据库中重建了453起真实世界机事件.
- 从每个涉及的乘用车的角度创建596个测试场景.
- 使用百度阿波罗ADS进行反事实模拟,并评估安全性能.
- 应用逻辑模型来识别重要的场景元素.
主要成果:
- 无人驾驶汽车可以避免60.91%的模拟碰撞,并在不可避免的场景中减轻伤害.
- 在大多数场景中,自动驾驶汽车与人类驾驶员相比保持了更平稳的速度.
- 不可避免的碰撞往往是由于人类驾驶员的异常行为造成的,而不是因为违反了AV规则.
结论:
- 与人类驾驶员相比,自动驾驶汽车表现出优越的避免和减轻碰撞的能力.
- 自动驾驶汽车可以在人类驾驶员扎的场景中成功导航,大大提高了交通安全.
- 确定了七个特定的场景,其中AV无法避免机,突出了需要进一步研究的领域.
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