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32 A.I. & L. 1 (2024)

handle is hein.journals/artinl32 and id is 1 raw text is: Artificial Intelligence and Law (2024) 32:1-56 https:I/doi.org/l 0.1007/si10506-022-09340-9 ORIGINAL RESEARCH Traffic rules compliance checking of automated vehicle maneuvers Hanif Bhuiyan1 2- Guido Governatori3 - Andy Bond2 . Andry Rakotonirainy2 Accepted: 9 November 2022 / Published online: 21 January 2023 ŠThe Author(s), under exclusive licence to Springer Nature B.V. 2023 Abstract Automated Vehicles (AVs) are designed and programmed to follow traffic rules. However, there is no separate and comprehensive regulatory framework dedicated to AVs. The current Queensland traffic rules were designed for humans. These rules often contain open texture expressions, exceptions, and potential conflicts (conflict arises when exceptions cannot be handled in rules), which makes it hard for AVs to follow. This paper presents an automatic compliance checking framework to assess AVs behaviour against current traffic rules by addressing these issues. Specifically, it proposes a framework to determine which traffic rules and open texture expressions need some additional interpretation. Essentially this enables AVs to have a suitable and executable formalization of the traffic rules. Defeasible Deontic Logic (DDL) is used to formalize traffic rules and reasoning with AV information (behaviour and environment). The representation of rules in DDL helps effectively in handling and resolving exceptions, potential conflicts, and open textures in rules. 40 experiments were conducted on eight realistic traffic scenarios to evaluate the framework. The evaluation was undertaken both quantitatively and qualitatively. The evaluation result shows that the proposed framework is a promising system for checking Auto- mated Vehicle interpretation and compliance with current traffic rules. Keywords Automated vehicle - Defeasible deontic logic - Logical reasoning Ontology knowledge base - Overtaking maneuver - Traffic rule formalization 1 Introduction Automated Vehicles (AVs) are designed and programmed to follow traffic rules; it is therefore suggested that AVs would be the solution to traffic rule violations (Kho- rasani et al. 2013; Leenes and Lucivero 2015). AVs have the potential to reduce E Hanif Bhuiyan hanifbhuiyan.c @gmail.com Extended author information available on the last page of the article Springer