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Application of Genetic Algorithm in Automatic Train Operation

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Abstract

This paper designs the performance index of the automatic train operation (ATO) speed curve model. In addition, based on the principle of genetic algorithm, it optimizes the ATO speed curve. At last, combined with train operation route and train parameters, we design the optimization process of the ATO speed curve in details. System speed protection index, punctuality index, accurate parking index, comfort index and energy saving index meet the requirements, and at the same time achieve the purpose of optimal optimization. The result of this paper shows that using the characteristics of global optimization of genetic algorithm has significant advantages in solving the optimization of complex nonlinear ATO speed curve. Therefore, it can be concluded that it is feasible and advantageous to apply genetic algorithm to the optimization of ATO speed curve, which has reference value in the practical application of ATO speed curve optimization.

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Acknowledgements

The authors acknowledge the National Natural Science Funds of China (Grant: 51674245), Research and Practice Project on the Reform of Graduate Education and Teaching in China University of Mining and Technology (Grant: 2017Y05), and the Natural Science Foundation of Jiangsu Province (Grant: BK20150193).

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Authors and Affiliations

  1. School of Mines, China University of Mining and Technology, Xuzhou, China

    Guiyang Wang & Xin Li

  2. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China

    Shuo Xiao

  3. Xuzhou Metrological Verification and Testing Center, Xuzhou, China

    Xi Chen

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  1. Guiyang Wang
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  2. Shuo Xiao
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  3. Xi Chen
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  4. Xin Li
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Correspondence to Xi Chen.

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Wang, G., Xiao, S., Chen, X. et al. Application of Genetic Algorithm in Automatic Train Operation. Wireless Pers Commun 102, 1695–1704 (2018). https://doi.org/10.1007/s11277-017-5228-6

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  • DOI: https://doi.org/10.1007/s11277-017-5228-6

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