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An unscented Kalman filter for freeway traffic estimation

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An unscented Kalman filter for freeway traffic estimation. / Mihaylova, L.; Boel, R.; Hegiy, A.

Proceedings of the 11th IFAC Symposium on Control in Transportation Systems. IFAC, 2006. p. 31-36.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Mihaylova, L, Boel, R & Hegiy, A 2006, An unscented Kalman filter for freeway traffic estimation. in Proceedings of the 11th IFAC Symposium on Control in Transportation Systems. IFAC, pp. 31-36, 11th IFAC Symposium on Control in Transportation Systems, Delft, Netherlands, 29/08/06. https://doi.org/10.3182/20060829-3-NL-2908.00006

APA

Mihaylova, L., Boel, R., & Hegiy, A. (2006). An unscented Kalman filter for freeway traffic estimation. In Proceedings of the 11th IFAC Symposium on Control in Transportation Systems (pp. 31-36). IFAC. https://doi.org/10.3182/20060829-3-NL-2908.00006

Vancouver

Mihaylova L, Boel R, Hegiy A. An unscented Kalman filter for freeway traffic estimation. In Proceedings of the 11th IFAC Symposium on Control in Transportation Systems. IFAC. 2006. p. 31-36 https://doi.org/10.3182/20060829-3-NL-2908.00006

Author

Mihaylova, L. ; Boel, R. ; Hegiy, A. / An unscented Kalman filter for freeway traffic estimation. Proceedings of the 11th IFAC Symposium on Control in Transportation Systems. IFAC, 2006. pp. 31-36

Bibtex

@inproceedings{233e6bed026b4675ac36297973a574ba,
title = "An unscented Kalman filter for freeway traffic estimation",
abstract = "This paper addresses the problem of freeway tra±c flow estimation. The freeway is considered as a network of components representing different freeway stretches called segments. The evolution of the traffic in a segment is modelled as a dynamic stochastic system, influenced by states of neighbour segments. Measurements are received only at boundaries between some segments and averaged within regular time intervals. An Unscented Kalman filter is developed and its performance is compared with a particle filter both for synthetic data and for real traffc data. The intended application is to supply traffc control systems with the estimated traffc state.",
keywords = "macroscopic traffic models, unscented Kalman filter, particle filter",
author = "L. Mihaylova and R. Boel and A. Hegiy",
year = "2006",
month = aug,
day = "29",
doi = "10.3182/20060829-3-NL-2908.00006",
language = "English",
pages = "31--36",
booktitle = "Proceedings of the 11th IFAC Symposium on Control in Transportation Systems",
publisher = "IFAC",
note = "11th IFAC Symposium on Control in Transportation Systems ; Conference date: 29-08-2006 Through 31-08-2006",

}

RIS

TY - GEN

T1 - An unscented Kalman filter for freeway traffic estimation

AU - Mihaylova, L.

AU - Boel, R.

AU - Hegiy, A.

PY - 2006/8/29

Y1 - 2006/8/29

N2 - This paper addresses the problem of freeway tra±c flow estimation. The freeway is considered as a network of components representing different freeway stretches called segments. The evolution of the traffic in a segment is modelled as a dynamic stochastic system, influenced by states of neighbour segments. Measurements are received only at boundaries between some segments and averaged within regular time intervals. An Unscented Kalman filter is developed and its performance is compared with a particle filter both for synthetic data and for real traffc data. The intended application is to supply traffc control systems with the estimated traffc state.

AB - This paper addresses the problem of freeway tra±c flow estimation. The freeway is considered as a network of components representing different freeway stretches called segments. The evolution of the traffic in a segment is modelled as a dynamic stochastic system, influenced by states of neighbour segments. Measurements are received only at boundaries between some segments and averaged within regular time intervals. An Unscented Kalman filter is developed and its performance is compared with a particle filter both for synthetic data and for real traffc data. The intended application is to supply traffc control systems with the estimated traffc state.

KW - macroscopic traffic models

KW - unscented Kalman filter

KW - particle filter

U2 - 10.3182/20060829-3-NL-2908.00006

DO - 10.3182/20060829-3-NL-2908.00006

M3 - Conference contribution/Paper

SP - 31

EP - 36

BT - Proceedings of the 11th IFAC Symposium on Control in Transportation Systems

PB - IFAC

T2 - 11th IFAC Symposium on Control in Transportation Systems

Y2 - 29 August 2006 through 31 August 2006

ER -