Developing Train Station Parking Algorithms: New Frameworks Based on Fuzzy Reinforcement Learning

Train station parking (TSP) accuracy is important to enhance the efficiency of train operation and the safety of passengers for urban rail transit. However, TSP is always subject to a series of uncertain factors such as extreme weather and uncertain conditions of rail track resistances. To increase the parking accuracy, robustness, and self-learning ability, the authors propose new train station parking frameworks by using the reinforcement learning (RL) theory combined with the information of balises. Three algorithms were developed, involving a stochastic optimal selection algorithm (SOSA), a Q-learning algorithm (QLA), and a fuzzy function based Q-learning algorithm (FQLA) in order to reduce the parking error in urban rail transit. Meanwhile, five braking rates are adopted as the action vector of the three algorithms and some statistical indices are developed to evaluate parking errors. Simulation results based on real-world data show that the parking errors of the three algorithms are all within the 30cm, which meet the requirement of urban rail transit.

• Record URL:
  • https://doi.org/10.1155/2019/3072495
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
• Supplemental Notes:
  • © 2019 Wei Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
• Authors:
  • Li, Wei
  • 0000-0001-9089-9897
  • Xian, Kai
  • Yin, Jiateng
  • Chen, Dewang
• Publication Date: 2019

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 9p
• Serial:
  • Journal of Advanced Transportation
  • Volume: 2019
  • Issue Number: Article ID 3072495
  • Publisher: John Wiley & Sons, Incorporated
  • ISSN: 0197-6729
  • EISSN: 2042-3195
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Algorithms; Arrivals and departures; Braking; Parking; Rail transit; Rail transit stations; Remote sensing; Urban transit
• Subject Areas: Operations and Traffic Management; Railroads;

Filing Info

• Accession Number: 01717066
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 18 2019 9:17AM