应用AVWEWM在自动驾驶汽车发生事故时的伦理决策
Guoman Liu1,2, Yufeng Luo3, Jing Sheng4
1Key Innovation Center of Industry and Higher Education Integration of Jiangxi Province, East China Jiaotong University, Nanchang, 330013, China. jerry@nit.edu.cn.
Scientific reports
|February 17, 2024
概括
本研究介绍了自动驾驶汽车 (AV) 伦理困境的计算模型. 属性价值加权透法 (AVWEWM) 模型与公众论更符合,而不是透加权方法 (EWM).
科学领域:
- 计算伦理学 计算伦理学
- 人工智能决策 - - 人工智能决策
- 自动驾驶汽车的安全性
背景情况:
- 现有的关于道德困境决策的研究缺乏量化方法来衡量影响因素.
- 这种差距阻碍了用于解决伦理困境的计算模型的开发,特别是在自主系统中.
- 自动驾驶汽车 (AV) 在碰撞情况下面临复杂的伦理决策场景.
研究的目的:
- 开发和评估自动驾驶汽车 (AV) 伦理困境的计算决策模型.
- 量化评估各种因素在道德决策中的权重和作用.
- 为了比较值加权方法 (EWM) 和属性值加权EWM (AVWEWM) 在AV碰撞场景中的有效性.
主要方法:
- 在84个道德困境中应用了值加权方法 (EWM) 和属性值加权EWM (AVWEWM).
- 开发了基于EWM和AVWEWM的决策模型,用于AV事故情况.
- 使用40个不同的伦理困境来测试模型,以评估决策清晰度和公众论一致性.
主要成果:
- 对于40个经过测试的AV道德困境,EWM和AVWEWM模型都成功地提供了明确的决策.
- 与EWM模型相比,AVWEWM模型与公众论的一致性更大.
- 确定了不同因素在道德决策过程中的权重和影响.
结论:
- 计算模型,特别是AVWEWM,可以有效地解决自动驾驶汽车事故中的道德困境.
- AVWEWM为AV提供了一种更符合公众意见的伦理决策方法.
- 调查结果为交通管理和法律机构在制定未来的AV法规时提供了宝贵的见解.
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