Energy Savings in Metropolitan Railway Substations Through Regenerative Energy Recovery and Optimal Design of ATO Speed Profiles
Automatic Train Operation (ATO) is one of the most important functions for an advanced train control system in high-speed railway systems. Research on optimization methods for ATO has been done before it is implemented in a train control system. From a theoretical point of view, it can be formulated as one of the functions of multi-objective Optimal Control Theory. This paper presents a new multi-objective optimization method for an ATO system using Cellular Automata (CA). A CA model for an ATO system is applied to simulate train operation. An optimal method for ATO is proposed. Compared with actual train operation results, the control algorithm can reduce energy consumption and ensure train operation safety such as higher accuracy of train stop. Therefore, it can improve the efficiency and safety of the train operation.