Driving Decision Making of Autonomous Vehicle According to Queensland Overtaking Traffic Rules
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Governatori, Guido
Rakotonirainy, Andry
Wong, Meng Weng
Mahajan, Avishkar
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Abstract
Improving the safety of autonomous vehicles (AVs) by making driving decisions in accordance with traffic rules is a complex task. Traffic rules are often expressed in a way that allows for interpretation and exceptions, making it difficult for AVs to follow them. This paper proposes a novel methodology for driving decision making in AVs based on defeasible deontic logic (DDL). We use DDL to formalize traffic rules and facilitate automated reasoning, allowing for the effective handling of rule exceptions and the resolution of vague terms in rules. To supplement the information provided by traffic rules, we incorporate an ontology for AV driving behaviour and environment information. By applying automated reasoning to formalized traffic rules and ontology-based AV driving information, our methodology enables AVs to make driving decisions in accordance with traffic rules. We present a case study focussing on the overtaking traffic rule to illustrate the usefulness of our methodology. Our evaluation demonstrates the effectiveness of the proposed driving decision-making methodology, highlighting its potential to improve the safety of AVs on the road.
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The Review of Socionetwork Strategies
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17
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2
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© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Road transportation and freight services
Automotive safety engineering
Science & Technology
Technology
Computer Science, Information Systems
Computer Science
Autonomous vehicle
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Bhuiyan, H; Governatori, G; Rakotonirainy, A; Wong, MW; Mahajan, A, Driving Decision Making of Autonomous Vehicle According to Queensland Overtaking Traffic Rules, The Review of Socionetwork Strategies, 2023, 17 (2), pp. 233-254