Author(s)

J. Xun, B. Ning & K. P. Li

Abstract

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. Keywords: Automatic Train Operation (ATO), Cellular Automata (CA), optimal method. 1 Introduction ATO system has been known as one of the most effective methods for saving energy and improving the transportation efficiency. Along with the rapid improvement of technologies, especially with the development of CBTC (Communication Based Train Control) system [1], more and more ATO systems have been put in operation. The control algorithm is the core of ATO system. Many scholars did a lot of researches on ATO control algorithm. C.S.Chang proposed a novel approach of differential evolution (DE) by incorporating the Pareto-optimal set which is presented for optimizing train movement through tuning fuzzy membership functions in mass transit systems [2]. Satoshi Sekine

Keywords

Automatic Train Operation (ATO), Cellular Automata (CA), optimal method.