Heuristic Algorithms for Train Station Parking Using Information of Transponders

Train Station Parking (TSP) has received increasing concentration as Platform Screen Doors (PSDs) are widely used in Urban Rail Transit. Aiming to enhance the accuracy and robustness of TSP, we proposed three algorithms which are Newton Dynamics based Algorithm (NDA), Heuristic Learning based Algorithm (HLA) and Heuristic Algorithm based on deceleration deviations Sequences (HAS) by using the information of transponders, essential locating equipments in subway. Then we verify the three algorithms on time-delay of the braking system and the initial speed of the train in TSP simulation platform. The result indicates that HLA and HAS can keep parking errors in 30cm while NDA can’t. Furthermore HAS achieves the best performance compared with NDA and HLA.