Train Headway Adjustment Using Potential Function Based on Multi-agent Formation Control

Train headway has a significant impact on the train operation efficiency and operating safety. Headway irregularity will decrease the rail traffic systems performances (e.g., line capacity, passengers waiting time, et al), which result from external disturbances (e.g., weather condition, passengers reasons). This paper proposes a real-time dynamical headway adjustment algorithm. By using artificial potential function, trains with different position can gain various potential fields. In this field, each train is attracted or repelled by other trains. Train speed and headway can converge to expected target point under the potential function. Finally, two case studies considering external disturbance are given to verify the availability of the algorithm. The simulation results show the potential function has good robustness against interference.