Abstract

This study investigates collaborative route mapping for a collection of connected automated vehicles (CAVs) traversing multi-lane pathways, with a particular emphasis on intersections without traffic signals. A distinctive feature of our research is the prioritization of emergency vehicles, such as ambulances and fire engines, according to their velocity demands. Additionally, a comprehensive analysis of the ethical ramifications of implementing such a prioritised system is engaged, while it is notable that in most of the existing studies, the ethical evaluation of intelligent transportation modalities is neglected. From a technical aspect, trajectories for CAVs in current models tend to be either inflexible or congruent with the collective formation of the fleet. Concurrently, the pre-set velocities for CAVs frequently demonstrate a lack of adaptability, which impedes cohesive operation. Moreover, there exists a pronounced deficiency in catering to the prioritization needs of emergency vehicles within these models. The current research endeavours to address these shortcomings by formulating the intersection management as an optimal control problem (OCP). This formulation enables CAVs to modulate their velocities in response to practical objectives, sidestepping fixed lane regulations at junctions. The control framework also encompasses autonomous vehicles of diverse sizes and velocities. An Adaptive Stepwise Optimization (ASO) methodology is proposed to augment the efficacy of the OCP resolution.

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