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交通中的道德复杂性:推进自动驾驶系统的ADC模型

Moral Complexity in Traffic: Advancing the ADC Model for Automated Driving Systems.

作者信息

Cecchini Dario, Dubljević Veljko

机构信息

Department of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC, USA.

出版信息

Sci Eng Ethics. 2025 Jan 24;31(1):5. doi: 10.1007/s11948-025-00528-1.

Abstract

The incorporation of ethical settings in Automated Driving Systems (ADSs) has been extensively discussed in recent years with the goal of enhancing potential stakeholders' trust in the new technology. However, a comprehensive ethical framework for ADS decision-making, capable of merging multiple ethical considerations and investigating their consistency is currently missing. This paper addresses this gap by providing a taxonomy of ADS decision-making based on the Agent-Deed-Consequences (ADC) model of moral judgment. Specifically, we identify three main components of traffic moral judgment: driving style, traffic rules compliance, and risk distribution. Then, we suggest distinguishable ethical settings for each traffic component.

摘要

近年来,为增强潜在利益相关者对自动驾驶系统(ADSs)这项新技术的信任,自动驾驶系统中道德场景的纳入问题已得到广泛讨论。然而,目前缺少一个全面的自动驾驶系统决策道德框架,该框架能够融合多种道德考量并研究它们的一致性。本文通过提供一种基于道德判断的行为者-行为-后果(ADC)模型的自动驾驶系统决策分类法来填补这一空白。具体而言,我们确定了交通道德判断的三个主要组成部分:驾驶风格、交通规则遵守情况和风险分配。然后,我们针对每个交通组成部分提出了可区分的道德场景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84fb/11761772/6b8d7180d405/11948_2025_528_Fig1_HTML.jpg

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