Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (2): 179-184.doi: 10.11959/j.issn.2096-6652.202118

• Special Topic: Intelligent Transportation Systems and Applications • Previous Articles     Next Articles

Algorithm for automatically generating a large number of speed curves of subway trains based on AlphaZero

Yuqi LU1, Dewang CHEN2,3, Zhaolin ZHAO2   

  1. 1 School of Computer Science and Mathematics, Fujian University of Technology, Fuzhou 350118, China
    2 School of Transportation, Fujian University of Technology, Fuzhou 350118, China
    3 College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
  • Revised:2021-05-13 Online:2021-06-15 Published:2021-06-01
  • Supported by:
    The National Natural Science Foundation of China(61976055);Special Fund of Education and Scientific Research of Fujian Provincial Finance Department(GY-Z21001)

Abstract:

In the previous research on subway trains automatic driving, subway driving data is usually obtained through simulation to generate a single operating curve and manual driving data sampling.Not only is the implementation method more complicated, but also the efficiency is low and the versatility is not strong.Inspired by AlphaZero system, the idea of artificial generation of virtual metro operation data was put forward.Firstly, according to a running method of five section subway trains speed curve, the calculation of virtual data was realized.Then, combined with the experience of human experts, the actual parameters such as the classification of traction braking section, the classification of actual running speed, the classification of station spacing and variable speed distance were set to narrow the range of curve data and rationalize it.Finally, a large amount of data was obtained by Python programming, saved as a data set, and the frequency distribution map of subway trains operation time was drawn.It can be observed that the virtual data covers all kinds of operation time, which is more conducive to the research of subway trains intelligent driving algorithm than traditional data.

Key words: human-machine hybrid enhanced intelligence, subway trains speed curve, AlphaZero idea, virtual data gen-eration

CLC Number: 

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