@inproceedings{ebacdcadbc61414fbe0cb5de446ab947,
title = "Formalise Regulations for Autonomous Vehicles with Right-Open Temporal Deontic Defeasible Logic",
abstract = "To negotiate the safety and liability concerns of Autonomous Vehicles (AVs), manufacturers desire AVs to conform to traffic laws and regulations with auto-reasoning capabilities and the ability to detect passengers{\textquoteright} misbehaviour. Our study focuses on formalising regulations for AVs based on Temporal Deontic Defeasible Logic (TDDL). We adopt a directed obligation to introduce the person in charge of events that can differ from the event executor. We also relax the time intervals from bounded to right-open to enable AVs to conduct auto-reasoning even without knowing when events end. Based on the modified deontic and temporal features, a Right-Open TDDL (RTDDL) is developed. The UK Highway Code is selected to illustrate the proposed RTDDL to ensure the behaviours of AVs obey traffic laws in complex traffic scenarios.",
keywords = "Autonomous Vehicles, Directed Obligation, Formalisation, Temporal Deontic Defeasible Logic",
author = "Chan, {Pak Yin} and Xue Li and Yiwei Lu and Yuhui Lin and Alan Bundy",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 44th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence 2024, SGAI 2024 ; Conference date: 17-12-2024 Through 19-12-2024",
year = "2025",
doi = "10.1007/978-3-031-77918-3_14",
language = "English",
isbn = "9783031779176",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "194--207",
editor = "Max Bramer and Frederic Stahl",
booktitle = "Artificial Intelligence XLI. SGAI 2024",
}