On Freeway Traffic Density Estimation for a Jump Markov Linear Model Based on Daganzo's Cell Transmission Model

Reference

K. Staňková and B. De Schutter, "On Freeway Traffic Density Estimation for a Jump Markov Linear Model Based on Daganzo's Cell Transmission Model," Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC 2010), Madeira Island, Portugal, pp. 13-18, Sept. 2010.

Abstract

This paper deals with problem of the real-time freeway traffic density estimation/prediction for a jump Markov linear model based on Daganzo's cell transmission variant of the Lighthill-Whitham-Richards continuous macroscopic freeway model. To solve the problem we propose a particle-filtering-based estimation/prediction method. Its performance is illustrated on case studies involving a four-cell freeway segment. The case studies suggest that the proposed methodology can be used for real-time traffic density estimation/prediction. Possible pitfalls of our approach are also discussed.

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Bibtex entry

@inproceedings{StaDeS:10-045,
author={K. Sta{\v{n}}kov{\'{a}} and B. {D}e Schutter},
title={On Freeway Traffic Density Estimation for a Jump {Markov} Linear Model Based on {Daganzo}'s Cell Transmission Model},
booktitle={Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC 2010)},
address={Madeira Island, Portugal},
pages={13--18},
month=sep,
year={2010}
}

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