Speed profile optimization for train operation based on ant colony algorithm

Abstract

Automatic train operation (ATO) system generally consists of the generation of recommended speed profile and the speed tracking strategy. It determines the tracked trajectory and the energy consumption of trains during the trip. Therefore, the optimization of recommended speed profile and the tracking strategy are regarded as two important means to achieve energy-efficient train operation between the successive stations. With considering the ATO tracking strategy, an optimization method of the recommended speed profile is proposed in this paper. Base on the approximate calculation, a discrete combination optimization model is formulated and a new MAX-MIN ant system (MMAS) is taken as the core algorithm. With the fixed speed tracking strategy, this method achieves the recommended speed profile with optimized energy consumption and a perfect running punctuality along the actual tracked trajectory. The switching times of operation during the cruising phase is reduced by integrating the drivers' experience, which also reduces the energy consumption of train running between stations. The case results based on Beijing Yizhuang Metro Line in China verify the effectiveness of the proposed method, which has a good performance on energy-efficient train operation.