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

2025-02-11

Electronic Proceedings in Theoretical Computer Science

AI Summary

This work addresses the challenge of interpretable modeling and compliance verification of traffic regulations—particularly UK Highway Code intersection rules—in autonomous–human driver cooperative scenarios. We propose the first Logical English–Prolog–NetLogo tri-modal collaborative architecture. Logical English enables human-readable formalization of natural-language rules; Prolog ensures sound, verifiable logical reasoning; and NetLogo supports multi-agent dynamic simulation. These components form a closed-loop system via bidirectional, predicate-level translation and interaction. The framework successfully formalizes a subset of Highway Code intersection rules, enabling automated violation detection, exception classification, and visual validation. Crucially, it distinguishes legally actionable violations from permissible exceptions under dynamic traffic conditions, thereby reconciling legal rigor, human–machine interpretability, and engineering deployability.

Technology Category

• Knowledge Representation and Reasoning: Automated Reasoning and Theorem Proving
• Natural Language Processing: Safety and Robustness
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

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.

Problem

• Representing legal traffic rules for autonomous vehicles
• Developing a modular system for multi-agent interaction
• Ensuring compliance and validating violations in urban scenarios

Innovation

• Logical English interface
• Prolog rule representation
• NetLogo multi-agent simulation