Research on speed profile generation of train automatic driving planning based on improved genetic algorithm

Qinyue Zhu; Runkai Hua; Yichen Yu; Jiyuan Li

doi:10.1117/12.3032033

8 June 2024 Research on speed profile generation of train automatic driving planning based on improved genetic algorithm

Qinyue Zhu, Runkai Hua, Yichen Yu, Jiyuan Li

Author Affiliations +

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131710I (2024) https://doi.org/10.1117/12.3032033
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

Aiming at the problems of punctuality, parking accuracy, energy saving and comfort in the automatic driving of urban rail trains, this paper proposes an algorithm for generating planned speed profile based on improved genetic algorithm. This improved genetic algorithm aims to achieve multi-objective optimization of on-time, accurate parking, energy saving and comfort and improve the optimization efficiency of traditional genetic algorithms. The simulation results show that the proposed algorithm can satisfy the basic constraints of safe, punctual and accurate stopping of trains. The algorithm also reduces the operation energy consumption and improves the operation comfort.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qinyue Zhu, Runkai Hua, Yichen Yu, and Jiyuan Li "Research on speed profile generation of train automatic driving planning based on improved genetic algorithm", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131710I (8 June 2024); https://doi.org/10.1117/12.3032033

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