The Centre for Computational Law has merged with the Centre for AI and Data Governance to form the Centre for Digital Law. The new Centre examines the transformative impact of digital technologies on legal systems, government, society, and economy. Our research, including the Research Programme on Computational Law, continue under its ambit. Our current website will remain operational in this transitional period but we strongly encourage you to visit our new website at cdl.smu.edu.sg and explore the updated features and content. If you have any questions or need assistance, please contact our support team at cclawadmin@smu.edu.sg.
Driving-Decision Making of Autonomous Vehicle according to Queensland Overtaking Traffic Rules
Making a driving decision according to traffic rules is a challenging task for improving the safety of Autonomous Vehicles (AVs). Traffic rules often contain open texture expressions and exceptions, which makes it hard for AVs to follow them. This paper introduces a Defeasible Deontic Logic (DDL) based driving decision-making methodology for AVs. We use DDL to formalize traffic rules and facilitate automated reasoning. DDL is used to effectively handle rule exceptions and resolve open texture expressions in rules. Furthermore, we sup-plement the information provided by the traffic rules by an ontology for AV driv-ing behaviour and environment information. This methodology performs auto-mated reasoning on formalized traffic rules and ontology-based AV driving in-formation to make the driving decision by following the traffic rule. The over-taking traffic rule is our case study to illustrate the usefulness of our methodol-ogy. The case study evaluation showed the effectiveness of this proposed driving decision-making methodology.
