Intelligent transport systems provide great possibilities to mitigate traffic congestion and intensify driving efficiency. The design of these systems requires a clear understanding of traffic dynamics. In this respect, this study focuses on describing and analysing traffic conditions at junctions in urban environments from a macroscopic level of description. As a first step, our method attempts to interpret the traffic scenario at intersections as a queuing system. Then, a Continuous Time Markov Chain to predict the future traffic condition at intersections is developed, and afterwards the pertaining steady-state probabilities are obtained. Given the equilibrium vector, significant performance measures are inferred for monitoring and planning purposes.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Continuous Time Markov Chain Traffic Model for Urban Environments


    Contributors:


    Publication date :

    2020-12-01


    Size :

    416874 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Traffic Load Forecast Model by Optimally Combined Markov Chain

    Anhong, D. / Shihua, Z. / Jiang, C. | British Library Online Contents | 2001


    Short-term traffic flow forecasting based on Markov chain model

    Guoqiang Yu, / Jianming Hu, / Changshui Zhang, et al. | IEEE | 2003


    Urban Short-Term Traffic Flow Forecasting Using the Markov Switching Model

    Sun, Xianghai / Liu, Tanqiu / Basu, Biswajit | ASCE | 2008


    Urban Short-Term Traffic Flow Forecasting Using the Markov Switching Model

    Sun, X. / Liu, T. / Basu, B. et al. | British Library Conference Proceedings | 2008


    Spatial Markov Chain simulation model of accident risk for marine traffic

    Xuan, S. / Xi, Y. / Huang, C. et al. | IEEE | 2017