Maguire-Day, JackAl-Rubaye, SabaWarrier, AnirudhSen, Muhammet A.Whitworth, HuwSamie, Mohammad2025-03-242025-03-242025-01-15Maguire-Day J, Al-Rubaye S, Warrier A, et al., (2025) Emerging decision-making for transportation safety: collaborative agent performance analysis. Vehicles, Volume 7, Issue 1, January 2025, Article number 42624-8921https://doi.org/10.3390/vehicles7010004https://dspace.lib.cranfield.ac.uk/handle/1826/23657This article belongs to the Special Issue Emerging Transportation Safety and Operations: Practical Perspectives, 2nd EditionThis paper addresses the challenge of improving decision-making capabilities and safety in autonomous vehicles (AVs) using Agent-Based Modelling (ABM). The study evaluates ABM’s effect on Advanced Driver Assistance Systems (ADASs) in challenging driving situations, like lane merging, by incorporating it into a simulation framework designed for autonomous vehicles. Identifying emergent behaviours that enhance safety and efficiency, verifying the efficacy of ABM in AV decision-making, and investigating the function of hardware acceleration to enable practical application in ADASs are some of the major achievements. According to the simulation results, ABM can greatly improve AV performance, providing a practical and scalable means of enhancing safety in future transportation systems.enAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/3509 Transportation, Logistics and Supply Chains40 Engineering4005 Civil Engineering35 Commerce, Management, Tourism and Servicesagent-based modelling (ABM)autonomous vehiclesadvanced driver assistance systemArticle2624-8921562435471