arXiv:2502.09216cs.AIcs.CL2025-02被引 5

用逻辑英语+逻辑编程构建自动驾驶交通规则推理系统

Mind the Gaps: Logical English, Prolog, and Multi-agent Systems for Autonomous Vehicles

  • 用逻辑英语与Prolog构建可读的交通规则模型
  • 在NetLogo中模拟车辆交互并自动检测违规行为
  • 适合研究自动驾驶合规性与法律责任的学者

本文提出一个模块化系统,用于表示和推理自动驾驶车辆在英国道路规则中的法律要素,聚焦于交叉口相关条款。鉴于人类驾驶员与自动驾驶车辆将在城市道路中交互,系统需为双方提供统一、高阶、可访问的计算模型,避免将责任转移给人类驾驶员带来额外负担。系统由三部分构成:基于逻辑英语的自然语言接口,用于编码规则;以Prolog表示的内部规则表示;以及基于NetLogo的多智能体仿真环境。逻辑英语与Prolog间双向转换,通过谓词与NetLogo交互。该设计使各组件分担不同职责,并支持模块替换。利用NetLogo可可视化规则影响,并通过动态场景验证系统有效性。指定智能体监控车辆行为以识别违规,违规信息交由验证器判断是否可罚,区分例外情况。

原文摘要 · Abstract (English)

In this paper, we present a modular system for representing and reasoning with legal aspects of traffic rules for autonomous vehicles. We focus on a subset of the United Kingdom's Highway Code (HC) related to junctions. As human drivers and automated vehicles (AVs) will interact on the roads, especially in urban environments, we claim that an accessible, unitary, high-level computational model should exist and be applicable to both users. Autonomous vehicles introduce a shift in liability that should not bring disadvantages or increased burden on human drivers. We develop a system "in silico" of the model. The proposed system is built of three main components: a natural language interface, using Logical English, which encodes the rules; an internal representation of the rules in Prolog; and an multi-agent-based simulation environment, built in NetLogo. The three components interact: Logical English is translated into and out of Prolog (along with some support code); Prolog and NetLogo interface via predicates. Such a modular approach enables the different components to carry different "burdens" in the overall system; it also allows swapping of modules. Given NetLogo, we can visualize the effect of the modeled rules as well as validate the system with a simple dynamic running scenario. Designated agents monitor the behaviour of the vehicles for compliance and record potential violations where they occur. The information on potential violations is then utilized by Validators, to determine whether the violation is punishable, differentiating between exceptions and cases.

自动驾驶逻辑推理多智能体交通规则

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