Reference
M. Hajiahmadi, B. De Schutter, and H. Hellendoorn, "Model predictive traffic
control: A mixed-logical dynamic approach based on the link transmission
model,"
Proceedings of the 13th IFAC Symposium on Control in
Transportation Systems (CTS'2012), Sofia, Bulgaria, pp. 144-149, Sept.
2012.
Abstract
In this paper, model predictive control of traffic networks using first-order
macroscopic link transmission model (LTM) is considered. The LTM model provides
fast yet accurate predictions for traffic networks compared to other models. In
order to use this model for traffic control, it is extended to include ramp
metering. Using the extended LTM model as prediction model in a model
predictive control framework, one can determine optimal control signals for
metered on-ramps. However, the optimization problem is still nonlinear and
nonconvex, and in general it is not tractable to find its global optimum, as
global or multi-start local optimization techniques take considerable time.
Therefore, in this paper the extended LTM model is transformed into a mixed
logical dynamic model. The resulting optimization problem can be recast as a
mixed integer linear program (MILP) that can be solved much more efficiently
than the nonlinear optimization problem, and it allows to determine a global
optimum efficiently. A simple case study is selected, first to test the
modeling performance of the extended LTM and next to compare the control
performance of the MILP approach and the original nonlinear formulation in
terms of computational efficiency and total cost.
Publisher page
Downloads
BibTeX
@inproceedings{HajDeS:12-033,
author = {Hajiahmadi, Mohammad and De Schutter, Bart and Hellendoorn,
Hans},
title = {Model Predictive Traffic Control: {A} Mixed-Logical Dynamic
Approach Based on the Link Transmission Model},
booktitle = {Proceedings of the 13th IFAC Symposium on Control in
Transportation Systems (CTS'2012)},
address = {Sofia, Bulgaria},
pages = {144--149},
month = sep,
year = {2012}
}