A Generalized Stochastic Petri Net Model for A-Priori Performance Analysis of Railway Station Areas under Uncertainty
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Abstract
The paper presents a stochastic, infrastructure centered modeling approach for capacity analysis applications in long term planning of railway stations. A formal modeling approach of train operations using generalized stochastic Petri nets is proposed. The model is analyzed based on the embedded Markov chain, which allows for quality based performance metrics including utilization, blocking probabilities and waiting times. The model is validated and tested against simulation in an application scenario for a medium size railway station. In addition, model extensions to large-scale systems are discussed.
BibTEX Reference Entry
@inproceedings{WeScZiScNi19, author = {Norman Weik and Malte Leonard Schmidt and Stephan Zieger and Anke Schmeink and Nils Nie{\"s}en}, title = "A Generalized Stochastic Petri Net Model for A-Priori Performance Analysis of Railway Station Areas under Uncertainty", pages = "1-6", booktitle = "{IEEE} Intelligent Transportation Systems Conference (ITSC19)", address = {Auckland, New Zealand}, doi = 10.1109/ITSC.2019.8917459, month = Oct, year = 2019, hsb = RWTH-2020-01082, }
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