Smart automotive technology adherence to the law: (De)constructing road rules for autonomous system development, verification and safety

Scott Mclachlan*, Martin Neil, Kudakwashe Dube, Ronny Bogani, Norman Fenton, Burkhard Schafer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Driving is an intuitive task that requires skill, constant alertness and vigilance for unexpected events. The driving task also requires long concentration spans, focusing on the entire task for prolonged periods, and sophisticated negotiation skills with other road users including wild animals. Modern motor vehicles include an array of smart assistive and autonomous driving systems capable of subsuming some, most, or in limited cases, all of the driving task. Building these smart automotive systems requires software developers with highly technical software engineering skills, and now a lawyer’s in-depth knowledge of traffic legislation as well. This article presents an approach for deconstructing the complicated legalese of traffic law and representing its requirements and flow. Our approach (de)constructs road rules in legal terminology and specifies them in ‘structured English logic’ that is expressed as ‘Boolean logic’ for automation and ‘Lawmaps’ for visualization. We demonstrate an example using these tools leading to the construction and validation of a ‘Bayesian Network model’. We strongly believe these tools to be approachable by programmers and the general public, useful in development of Artificial Intelligence to underpin motor vehicle smart systems, and in validation to ensure these systems are considerate of the law when making decisions.
Original languageEnglish
Article numbereaac002
Pages (from-to)255-295
Number of pages40
JournalInternational Journal of Law and Information Technology
Volume29
Issue number4
Early online date22 Feb 2022
DOIs
Publication statusPublished - 12 Mar 2022

Keywords

  • autonomous systems
  • legal tech
  • AI and law

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