Genetic Algorithm Based Energy-Saving ATO Control Algorithm for CBTC


  • Zheng WANG Zhejiang University
  • Xiangxian CHEN Zhejiang University
  • Hai HUANG Zhejiang University
  • Yue ZHANG Southwest China Research Institute of Electronic Equipment


CBTC, Energy-Saving, Genetic Algorithm, Automatic Train Operation


To improve their carrying capacities, multiple trains can operate on one line. Urban rail transit employs a Communication-Based Train Control (CBTC) system to realize a movable block, which is applied to decrease the headway. In a CBTC system, trains only know the speed limit within the scope of the Movement Authority Limit (MAL). An energy-saving Automatic Train Operation (ATO) control algorithm based on a genetic algorithm (GA) is proposed to control multi-train movements with incomplete information about speed limits. This algorithm is composed of two layers: a search layer that applies a GA to search for the optimal control solution and a protection layer that helps trains prevent overspeed. The GA in this paper tends to achieve optimal solutions using variable length chromosomes and a novel fitness function. The simulation results indicate that the proposed algorithm achieves optimal energy-saving benefits compared with other control strategies.

Author Biographies

Zheng WANG, Zhejiang University

Department of Instrument Science and Engineering

Xiangxian CHEN, Zhejiang University

Department of Instrument Science and Engineering

Hai HUANG, Zhejiang University

Department of Instrument Science and Engineering


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