On freeway traffic density estimation for a jump Markov linear model based on Daganzo's cell transmission model


Reference:
K. Stanková 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.


Downloads:
 * Corresponding technical report: pdf file (1.19 MB)
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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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