Reference
S. Lin, B. De Schutter, Y. Xi, and H. Hellendoorn, "Study on fast model
predictive controllers for large urban traffic networks,"
Proceedings of the 12th International IEEE Conference on Intelligent
Transportation Systems (ITSC 2009), St. Louis, Missouri, pp. 691-696,
Oct. 2009.
Abstract
Traffic control is both an efficient and effective way to alleviate the traffic
congestion in urban areas. Model Predictive Control (MPC) has advantages in
controlling and coordinating urban traffic networks. But, the real-time
computational complexity of MPC increases exponentially, when the network scale
and the predictive time horizon grow. To improve the real-time feasibility of
MPC, a simplified macroscopic urban traffic model is developed. Two MPC
controllers are built based on the simplified model and a more detailed model.
Simulation results of the two controllers show that the on-line optimization
time is reduced dramatically by applying the simplified model, only losing a
limited amount of control effectiveness. Additional techniques, like applying a
control time horizon and an aggregation scheme, are implemented to reduce the
computational complexity further. Simulation results show positive effects of
these techniques.
Downloads
BibTeX
@inproceedings{LinDeS:09-040,
author = {Lin, Shu and De Schutter, Bart and Xi, Yugeng and Hellendoorn,
Hans},
title = {Study on Fast Model Predictive Controllers for Large Urban
Traffic Networks},
booktitle = {Proceedings of the 12th International IEEE Conference on
Intelligent Transportation Systems (ITSC 2009)},
address = {St.\ Louis, Missouri},
pages = {691--696},
month = oct,
year = {2009}
}