Research On Petri Net-Based Method For Urban Rail Transit Train Regulation

Urban rail transit (UMT) has already become the main transportation way on releasingurban traffic pressure for its advantages like high speed, convenience, large volume andless pollution. With the rapid development of science and technology, CommunicationBased Train Control (CBTC) comes to be the trend of train control system in the future.Wide use of CBTC brings new challenge to traditional train regulation. So it issignificant to do research on train regulation in CBTC conditions.With the use of CBTC in urban rail transit, train interval becomes much shorter, alsooperating efficiency increases a lot. But issue followed is that higher requirement onreal time ability of regulation is proposed. For this, in the paper, first built a Petri netmodel of train operation system for urban rail transit in moving block (MB) conditions,then used genetic algorithm (GA) to do simulation analysis on train regulationaccording to the results of Petri net model's prediction.The main work in the paper is as following:Firstly, introduced the matrix description of train diagram in CBTC designed by StateKey Laboratory of Rail Traffic Control and Safety; Then analyzed train regulationproblem profoundly, including its function, character, delay situations, optimizationobjective and constraint conditions, then strategies and methods for train regulationwere proposed.Secondly, analyzed train operation control process in urban rail transit; brieflyintroduced the theory of Petri net and its modeling tool, then built the model of trainoperation system in CBTC conditions by CPN Tools. The model not only simulatestrain operation process in normal situation, but also added fault solver unit to the system,objectively reflected the process of train operation in urban rail transit.At last, according to the data predicated by the train operation model built in the paper,used genetic algorithm to do the solving analysis for train regulation problem; Thenbased on Dalian CBTC test line, constructed an environment for simulation experiment;After that experimented and analyzed train regulation in situations of single train delayand train group delay.The experimental results show that, genetic algorithm is effective on solving trainregulation problem, and the Petri net model of train operation system is feasible, that means the method of Petri net model prediction is advantageous for raising the real time ability of train regulation.