<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the estimation of traffic state variables (density and speed), using the so called Super- Twisting Sliding Mode Observer (STSM). Several numerical simulations, using simulated and real data, show the relevance of the proposed approach. In addition, a comparative study with the Extended Kalman Filter (EKF) is carried-out. The comparison indices concern convergence and stability, dynamic performance and robustness. The design of the two observers is achieved using a nonlinear second order traffic flow model in the same highway traffic and geometric conditions.</p></abstract>

Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the estimation of traffic state variables (density and speed), using the so called Super- Twisting Sliding Mode Observer (STSM). Several numerical simulations, using simulated and real data, show the relevance of the proposed approach. In addition, a comparative study with the Extended Kalman Filter (EKF) is carried-out. The comparison indices concern convergence and stability, dynamic performance and robustness. The design of the two observers is achieved using a nonlinear second order traffic flow model in the same highway traffic and geometric conditions.

Comparative Study of a Super-Twisting Sliding Mode Observer and an Extended Kalman Filter for a Freeway Traffic System

University of Sulaimani, Faculty of Engineering Sciences, Department of Civil Engineering, Sulaimani, Iraq

Université Lille Nord France, F-59000 Lille, France U-Artois, LGI2A, (EA. 3926) TechnoparcFutura, F-62400 Béthune, France

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Traffic state estimation represents one of the important ingredients for traffic prediction and forecasting. The work presented in this paper deals with the...

Comparative Study of a Super-Twisting Sliding Mode Observer and an Extended Kalman Filter for a Freeway Traffic System

Pubblicato online: 03 lug 2015

Pagine: 141 - 158

DOI: https://doi.org/10.1515/cait-2015-0034

© by H. Majid

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.