Abstract
This paper on a framework for modeling train control systems is from the proceedings of the 12th International Conference on Computer System Design and Operation in Railways and Other Transit Systems, held in Beijing, China, in 2010. The authors describe train control systems as being geographically and functionally distributed, with subsystems that have a high degree of autonomy. Their model features a two-layer framework for modeling train control systems. The upper-layer is defined by agents, which can include drivers, trains, and signal system, all of which can operate in an autonomous fashion. The lower-layer is the cellular automata (CA) traffic model to simulate the train-following dynamic. The CA model delivers the knowledge needed by the agents to make decisions. The functions of the upper layer decision-making processes are classified into three levels: service functionality, signaling functionality, and train operation functionality. A case study is presented to illustrate the applicability of the proposed framework to analyze the influence on traffic flow.
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