The right lane and platoon assignment to a vehicle significantly impacts achieving the desired driving goals to improve occupants’ safety or reduce pollution. Preparing an intelligent assistant to address this issue has exposed researchers’ attention, especially in intelligent transportation systems. Implementing such a system is complex and challenging to design, mainly because of conflicting driving goals possibility and the mixed traffic of autonomous and human-driven vehicles. This paper presents a multi-tier computational architecture to utilize the cloud, fog, and edge computational resources and formulate the lane/platoon assignment as an optimization problem subject to safety combined with any other secondary goal. The problem is then solved by the meta-heuristic Genetic Algorithm. By evaluating the proposed method by real data gathering, machine learning, and numerical experiments, the results show that the proposed method satisfies the minimization of overlapping collision areas during vehicles’ lane/platoon changes and harmonizes the traffic in all lanes and each platoon.
Lane and Platoon Assignment in Intelligent Transportation System: A Novel Heuristic Approach
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 22 , 2 ; 298-315
2024-08-01
18 pages
Article (Journal)
Electronic Resource
English
Intelligent transportation systems , Lane/platoon assignment , Safety , Traffic harmonization , Genetic algorithms Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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