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 (1.23 MB)
Note: More information on the pdf file format mentioned above can be found here.

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}
        }

Go to the publications overview page.

This page is maintained by Bart De Schutter. Last update: March 21, 2022.