A Study on the Effects of Redundant Time on the Operation of Different Speed-Grade Trains in Passenger Railway Line Traffic System by Using Cellular Automata Model
As an integrated kind of railway signal-control pattern, the four-aspect fixed autoblock system has been used in many train control systems. This paper takes the four-aspect fixed autoblock system as the research object and proposes the cellular automata model of the fixed autoblock system based on the existing theoretical researches on different train systems and traffic systems by means of the analytical study of the classical cellular automata model. The CA (cellular automata) models combine complexity of passenger railway line with the theory of cellular automata and introduce some new CA models into the existing control systems. After analyzing the relevant simulation results, we study thoroughly and obtain efficiently the needed data for the variation of the section carrying capacity, the average train delay and the train speed which have been affected by redundant time on the operation of passenger trains with different speeds. 1. Introduction In China, there are usually many different speed trains operated in the high-speed railways. Naturally, there are many train operation organizing methods for the different organizational conditions. However, the current railway transport capacity in China still cannot satisfy the huge gap of the transportation requirements. If one train delays, it will make a domino effect for the whole system, which would result in even a worse situation: the more insufficient capacity of the railway transportation. The high speed railway transport system is so complex that it is impossible to describe it completely with the traditional methods and existing theories. The cellular automaton (CA) model is one of the most efficient ways to research the very complex systems and it can simulate the dynamic characters of the train control systems. Many scholars have researched the train operation and organization thoroughly. Carey and Kwieciński, for example, think that, in the train planning and timetabling, the trip time on each link is assumed to depend on the type of train and characteristics of the link and conduct detailed stochastic simulation of the interaction between trains as they traverse sections of the link [1]. Abbink et al. provide a model that can be used to obtain an optimal allocation of train types and subtypes to the lines [2]. Higgins et al. present the analytically based models designed to quantify the amount of delay risk associated with each track segment, the trains, and the scheduling as a whole [3]. Fretter et al. studied the balance of efficiency and robustness in the long-distance railway timetables
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