授权使用人类可信的认知编码来实现更安全,更社会敏感的自动驾驶汽车.
Hongliang Lu1,2, Meixin Zhu3, Chao Lu4
1Intelligent Transportation Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, Guangdong, China.
概括
自动驾驶汽车 (AV) 现在可以做出更道德的决定. 一个新的方案通过考虑个人道路使用者的影响及其集体影响,特别是对弱势用户而言,提高了安全性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 神经科学是一个神经科学.
- 伦理学 伦理学 伦理学
背景情况:
- 自动驾驶汽车 (AV) 越来越普遍,需要道德决策能力.
- 当前的自动驾驶车辆缺乏社会敏感性,未能考虑多个道路使用者的独特但相互关联的影响.
- 将伦理考虑纳入AV运营对于安全和社会可接受的部署至关重要.
研究的目的:
- 为AV道德决策提出一个新的方案,其中包括社会关注和人类可信的认知编码.
- 为了使自动驾驶汽车能够根据道路使用者类别进行差异化风险评估.
- 通过将个人影响编码为集体行为信念来实现整体的道德决策过程.
主要方法:
- 开发了一个结合社会关注和认知编码用于AV道德决策的方案.
- 根据风险和分类的用户评估了个人道路使用者的影响.
- 整体编码的独立影响进入行为信念,以支持道德决策.
- 通过使用CommonRoad的两千个基准场景来评估该计划.
主要成果:
- 拟议的方案导致了更安全,更道德的AV决策.
- 总体风险降低了26.3%,易受伤害的道路使用者减少了22.9%.
- 在事故场景中,自我保护提高了8.3%,整体道路使用者保护提高了17.6%,脆弱道路使用者保护提高了51.7%.
结论:
- 这种以人类为灵感的计划使得无人驾驶汽车变得更加社会敏感,解决了驾驶的伦理挑战.
- 该方法允许对道路使用者的差异化考虑和对集体影响的整体看法.
- 这项工作为自动驾驶汽车更负责任,更符合人性的道德决策铺平了道路.
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