摘要
随着智能交通系统的发展，自动驾驶汽车逐渐成为研究热点，其在提升交通安全性和效率方面展现出巨大潜力，但面临复杂的道德决策问题。本研究旨在构建适用于自动驾驶汽车的道德决策算法，以解决在紧急情况下如何抉择这一关键问题。通过分析传统伦理理论如功利主义、义务论等，结合人工智能领域强化学习、深度学习等技术，提出一种融合多源信息（包括交通规则、环境感知数据、行人行为预测）的混合式道德决策框架。该框架能够在不同场景下动态调整决策权重，确保既遵循法律规范又体现人文关怀。实验采用虚拟仿真平台与实车测试相结合的方式，在多种典型事故场景中验证算法的有效性。结果表明，所提算法能够根据具体情境快速生成合理决策方案，相比现有方法具有更高的适应性和灵活性。创新点在于首次将伦理学原理与先进AI技术深度融合，为自动驾驶汽车提供了更具操作性的道德决策依据，不仅有助于推动相关法律法规的完善，也为未来智能交通系统的安全可靠运行奠定了理论基础。
关键词：自动驾驶汽车道德决策；伦理算法；强化学习
Abstract
With the development of intelligent transportation systems, autonomous vehicles have become a research hotspot, demonstrating significant potential in enhancing traffic safety and efficiency but facing complex ethical decision-making challenges. This study aims to develop an ethical decision-making algorithm tailored for autonomous vehicles to address critical choices in emergency situations. By analyzing traditional ethical theories such as utilitarianism and deontology, and integrating advanced artificial intelligence technologies like reinforcement learning and deep learning, we propose a hybrid ethical decision-making fr amework that incorporates multi-source information including traffic regulations, environmental perception data, and pedestrian behavior prediction. This fr amework dynamically adjusts decision weights across different scenarios, ensuring compliance with legal norms while embodying humanitarian considerations. The experimental validation combines virtual simulation platforms with real-vehicle testing in various typical accident scenarios, demonstrating the algorithm's effectiveness. Results indicate that the proposed algorithm can rapidly generate reasonable decision-making schemes based on specific contexts, exhibiting higher adaptability and flexibility compared to existing methods. The innovation lies in the first-time integration of ethical principles with cutting-edge AI technologies, providing more operational ethical decision-making guidelines for autonomous vehicles. This not only facilitates the improvement of relevant laws and regulations but also lays a theoretical foundation for the safe and reliable operation of future intelligent transportation systems.
Keywords：Autonomous Vehicle Moral Decision; Ethical Algorithm; Reinforcement Learning
目 录
摘要 I
Abstract II
一、绪论 1
(一) 自动驾驶汽车发展背景 1
(二) 道德决策算法的意义 1
(三) 国内外研究现状综述 1
(四) 本文研究方法与思路 2
二、道德决策算法的理论基础 2
(一) 伦理学基本概念解析 2
(二) 决策算法的哲学依据 3
(三) 主要伦理框架分析 4
(四) 算法设计的基本原则 4
三、道德决策算法的设计与实现 5
(一) 算法模型构建方法 5
(二) 关键技术难点分析 5
(三) 典型场景应用案例 6
(四) 算法性能评估体系 7
四、道德决策算法的社会影响 7
(一) 法律法规适应性 7
(二) 社会伦理挑战 8
(三) 公众接受度调查 8
(四) 未来发展方向展望 9
结 论 11
参考文献 12
随着智能交通系统的发展，自动驾驶汽车逐渐成为研究热点，其在提升交通安全性和效率方面展现出巨大潜力，但面临复杂的道德决策问题。本研究旨在构建适用于自动驾驶汽车的道德决策算法，以解决在紧急情况下如何抉择这一关键问题。通过分析传统伦理理论如功利主义、义务论等，结合人工智能领域强化学习、深度学习等技术，提出一种融合多源信息（包括交通规则、环境感知数据、行人行为预测）的混合式道德决策框架。该框架能够在不同场景下动态调整决策权重，确保既遵循法律规范又体现人文关怀。实验采用虚拟仿真平台与实车测试相结合的方式，在多种典型事故场景中验证算法的有效性。结果表明，所提算法能够根据具体情境快速生成合理决策方案，相比现有方法具有更高的适应性和灵活性。创新点在于首次将伦理学原理与先进AI技术深度融合，为自动驾驶汽车提供了更具操作性的道德决策依据，不仅有助于推动相关法律法规的完善，也为未来智能交通系统的安全可靠运行奠定了理论基础。
关键词：自动驾驶汽车道德决策；伦理算法；强化学习
Abstract
With the development of intelligent transportation systems, autonomous vehicles have become a research hotspot, demonstrating significant potential in enhancing traffic safety and efficiency but facing complex ethical decision-making challenges. This study aims to develop an ethical decision-making algorithm tailored for autonomous vehicles to address critical choices in emergency situations. By analyzing traditional ethical theories such as utilitarianism and deontology, and integrating advanced artificial intelligence technologies like reinforcement learning and deep learning, we propose a hybrid ethical decision-making fr amework that incorporates multi-source information including traffic regulations, environmental perception data, and pedestrian behavior prediction. This fr amework dynamically adjusts decision weights across different scenarios, ensuring compliance with legal norms while embodying humanitarian considerations. The experimental validation combines virtual simulation platforms with real-vehicle testing in various typical accident scenarios, demonstrating the algorithm's effectiveness. Results indicate that the proposed algorithm can rapidly generate reasonable decision-making schemes based on specific contexts, exhibiting higher adaptability and flexibility compared to existing methods. The innovation lies in the first-time integration of ethical principles with cutting-edge AI technologies, providing more operational ethical decision-making guidelines for autonomous vehicles. This not only facilitates the improvement of relevant laws and regulations but also lays a theoretical foundation for the safe and reliable operation of future intelligent transportation systems.
Keywords：Autonomous Vehicle Moral Decision; Ethical Algorithm; Reinforcement Learning
目 录
摘要 I
Abstract II
一、绪论 1
(一) 自动驾驶汽车发展背景 1
(二) 道德决策算法的意义 1
(三) 国内外研究现状综述 1
(四) 本文研究方法与思路 2
二、道德决策算法的理论基础 2
(一) 伦理学基本概念解析 2
(二) 决策算法的哲学依据 3
(三) 主要伦理框架分析 4
(四) 算法设计的基本原则 4
三、道德决策算法的设计与实现 5
(一) 算法模型构建方法 5
(二) 关键技术难点分析 5
(三) 典型场景应用案例 6
(四) 算法性能评估体系 7
四、道德决策算法的社会影响 7
(一) 法律法规适应性 7
(二) 社会伦理挑战 8
(三) 公众接受度调查 8
(四) 未来发展方向展望 9
结 论 11
参考文献 12
