Pareto-optimal lane-changing trajectory planning in mixed traffic

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Citation

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@article{
    Yang Li, 2022, arXiv:2109.06080, 2021.
    title={Pareto-optimal lane-changing trajectory planning in mixed traffic}, 
    author={Yang Li and Linbo Li and Daiheng Ni},
    year={2022},
    archivePrefix={arXiv},
    primaryClass={cs.RO}
}

Abstract

This paper applies the pareto-optimal concept to LC (lane-changing) motion planning in the presence of mixed traffic including manual and autonomous vehicles. Firstly, a multiobjective optimization problem is presented, in which the comfort, efficiency and safety of the LC vehicle and the surrounding vehicles are jointly modelled. Thereafter, the pareto-optimal solutions are obtained through employing the NSGA-II (Non-dominated Sorting Genetic -II) algorithm. Finally, the experiment section analyzes the (macroscopic and microscopic) lane-changing impact from a pareto-optimal perspective. Also, a comprehensive sensitivity analysis is conducted. Our results demonstrate that our algorithm could significantly reduce the lane-changing impact within its region, and the total costs are reduced in the range of 10.94% to 48.66%. This paper could be considered as a preliminary research framework for the application of the pareto-optimal concept. We hope this research will provide valuable insights into autonomous driving technology.

Framework

Results