ESTIMATION OF STATE AND PARAMETERS OF TRAFFIC SYSTEM

Pavla Pecherková, Jitka Homolová, Jindřich Duník

Abstract

This paper deals with the problem of traffic flow modelling and state estimation for historical urban areas. The most important properties of the traffic system are described. Then the model of the traffic system is presented. The weakness of the model is pointed out and subsequently rectified. Various estimation and identification techniques, used in the traffic problem, are introduced. The performance of various filters is validated, using the derived model and synthetic and real data coming from the center of Prague, with respect to filter accuracy and complexity.

References

  1. Anderson, B. D. O. and Moore, S. B. (1979). Optimal Filtering. Englewood Cliffs, New Jersey: Prentice Hall Ins.
  2. Duník, J., S?imandl, M., Straka, O., and Král, L. (2005). Performance analysis of derivative-free filters. In Proceedings of the 44th IEEE Conference on Decision and Control, and European Control Conference ECC'05, pages 1941-1946, Seville, Spain. ISBN: 0- 7803-9568-9, ISSN: 0191-2216.
  3. Homolová, J. and Nagy, I. (2005). Traffic model of a microregion. In Preprints of the 16th IFAC World Congress, pages 1-6, Prague, Czech Republic.
  4. Julier, S. J., Uhlmann, J. K., and Durrant-White, H. F. (2000). A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE Transactions On AC, 45(3):477-482.
  5. Kratochvílová, J. and Nagy, I. (2004). Traffic control of microregion. In Andr Ések, J., KárnÉ, M., and Kracík, J., editors, CMP'04: Multiple Participant Decision Making, Theory, algorithms, software and app., pages 161-171, Adelaide. Advanced Knowledge Int.
  6. Ljung, L. (1999). System identification: theory for the user. UpperSaddle River, NJ: Prentice-Hall.
  7. Nørgaard, M., Poulsen, N. K., and Ravn, O. (2000). New developments in state estimation for nonlinear systems. Automatica, 36(11):1627-1638.
  8. Söderstr öm, T. and Stoica, P. (2002). Instrumental variable methods for system identification. Circuits, Systems, and Signal Processing, 21(1):1-9.
  9. Sorenson, H. W. (1974). On the development of practical nonlinear filters. Inf. Sci., 7:230-270.
  10. Viberg, M. (2002). Subspace-based state-space system identification. Circuits, Systems, and Signal Processing, 21(1):23-37.
  11. S?imandl, M. and Duník, J. (2007). Multi-step prediction and its application for estimation of state and measurement noise covariance matrices. Technical report. University of West Bohemia in Pilsen, Department of Cybernetics.
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Paper Citation


in Harvard Style

Pecherková P., Homolová J. and Duník J. (2007). ESTIMATION OF STATE AND PARAMETERS OF TRAFFIC SYSTEM . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 978-972-8865-83-2, pages 223-228. DOI: 10.5220/0001648402230228


in Bibtex Style

@conference{icinco07,
author={Pavla Pecherková and Jitka Homolová and Jindřich Duník},
title={ESTIMATION OF STATE AND PARAMETERS OF TRAFFIC SYSTEM},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2007},
pages={223-228},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001648402230228},
isbn={978-972-8865-83-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - ESTIMATION OF STATE AND PARAMETERS OF TRAFFIC SYSTEM
SN - 978-972-8865-83-2
AU - Pecherková P.
AU - Homolová J.
AU - Duník J.
PY - 2007
SP - 223
EP - 228
DO - 10.5220/0001648402230228