Traditional automatic train operation (ATO) system performs well on automatic driving. In the current researches of ATO, most of the scholars take the whole line as an object. But the final speed curve is very different from the actual speed. This paper proposes a developed strategy based on working condition to analyze and optimize parameter of energy consumption, driving comfort, punctuality, and precise parking. The model is built by optimized genetic algorithm and then get the speed curve. Finally, all speed curves are combined to get ATO multi-objective optimization speed curve. Through the test of example simulation, the strategy is proved to have a good optimization effect and maneuverability.


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    Title :

    The Multi-Objective Optimization Strategy of Urban Railway Train Automatic Train Operation (ATO)


    Contributors:
    Lin, Xinyu (author) / He, Ruichun (author)

    Conference:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Published in:

    CICTP 2017 ; 860-870


    Publication date :

    2018-01-18




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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