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Lane and Platoon Assignment in Intelligent Transportation System: A Novel Heuristic Approach

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Abstract

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.

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Authors and Affiliations

  1. Department of Computer Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran

    Hamidreza Mahini & Alireza Mahini

  2. Vrije Universiteit Brussel, Brussels, Belgium

    Mehrdad Asadi

  3. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, 64002, Douliou, Yunlin, Taiwan

    Amir Masoud Rahmani

  4. Department of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

    Mahmood Fathy

Authors
  1. Hamidreza Mahini
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  2. Mehrdad Asadi
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  4. Amir Masoud Rahmani
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  5. Mahmood Fathy
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Correspondence to Mehrdad Asadi.

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Mahini, H., Asadi, M., Mahini, A. et al. Lane and Platoon Assignment in Intelligent Transportation System: A Novel Heuristic Approach. Int. J. ITS Res. (2024). https://doi.org/10.1007/s13177-024-00397-1

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