Traffic Congestion Forecasting Based on Possibility Theory

Abstract

Traffic congestion state identification is one of the most important tasks of ITS. Traffic flow is a nonlinear complicated system. Traffic congestion state is affected by many factors, such as road channelization, weather condition, drivers’ different driving behavior and so on. It is difficult to collect all necessary traffic information. Traffic… (More)
DOI: 10.1007/s13177-014-0104-1

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Cite this paper

@article{Sun2016TrafficCF, title={Traffic Congestion Forecasting Based on Possibility Theory}, author={Zhanquan Sun and Zhao Li and Yanling Zhao}, journal={Int. J. Intelligent Transportation Systems Research}, year={2016}, volume={14}, pages={85-91} }