基于公众的道德偏好,为自动驾驶汽车制定道德决策框架
Yi Yang1, Qingfan Wang1, Hong Wang1
1School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China.
Accident; analysis and prevention
|September 17, 2025
概括
本研究介绍了基于公共道德偏好的自动驾驶汽车 (AV) 的伦理算法. 新的框架显著降低了伤害严重程度,并使AV决策与社会价值观保持一致,促进公众接受.
科学领域:
- 人工智能道德和自主系统
- 人与计算机的交互
- 运输安全运输安全
背景情况:
- 自动驾驶汽车 (AV) 的伦理决策对于公众接受和技术采用至关重要.
- 当前的AV算法缺乏将公众论纳入不可避免的道德困境.
- 公众对AV的信任取决于他们认为的道德理性.
研究的目的:
- 提出基于公共道德偏好的自动驾驶汽车道德决策算法框架.
- 将社会道德共识建模为AVs的机器可执行语言.
- 加强AVS与人类价值观的伦理一致,并提高安全性.
主要方法:
- 确定了五个核心道德偏好:减少整体伤害,减少个人伤害,确保平等照顾,保护合规者,避免积极伤害.
- 进行了一项大规模的在线调查,以量化道路使用者的伤害严重程度和模型道德偏好.
- 开发并验证了一种使用4860种不同的交通场景的伦理决策算法.
主要成果:
- 拟议的算法将AV决策与公众的道德偏好密切结合起来.
- 与基线相比,平均个体伤害严重程度 (52%),伤害严重程度标准偏差 (15%) 和合规者 (20%) 和非占用者 (24%) 的伤害严重程度显著降低.
- 该框架显示了高度的可扩展性和与社会伦理考虑保持一致.
结论:
- 将公共道德观点整合到AV伦理算法中是可行的和有效的.
- 开发的框架提供了一个可扩展的解决方案,以改善AV道德决策和公众接受.
- 这项研究为具有文化适应性的 AV 伦理框架提供了基础,促进了技术推广.
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