Title :
Model-based traffic and emission control using PWA models — A mixed-logical dynamic approach
Author :
Groot, Noortje ; De Schutter, Bart ; Zegeye, Solomon Kidane ; Hellendoorn, Hans
Author_Institution :
Delft Center for Syst. & Control, Delft Univ. of Technol., Delft, Netherlands
Abstract :
For the purpose of traffic control a piecewise-affine (PWA) approximation of the METANET model is proposed and tested in a model-based predictive control (MPC) framework. This approximation is provided as an alternative to the rather intensive computations when using the original nonlinear nonconvex METANET traffic flow model extended with a model for vehicular emissions and fuel consumption in an MPC context. As a direct PWA-MPC computation turned out to be intractable for on-line applications due to the size of the final, full PWA model that consists of a large number of PWA regions, the PWA model equations were additionally converted into a mixed-logical dynamic (MLD) model. The resulting MLD-MPC problem - written as a mixed-integer linear program (MILP) - can be solved much more efficiently as it does not explicitly state all model equations for each particular region. In a simple case study on a traffic network including a variable speed limit and an un-metered on-ramp while optimizing the total time spent (TTS), we compared the performance of the approximate MLD-MPC approach to that of model predictive traffic control when using the original nonlinear formulation of the METANET model.
Keywords :
air pollution control; approximation theory; integer programming; linear programming; predictive control; traffic control; traffic engineering computing; MILP; MLD model; MPC framework; PWA approximation; PWA model; TTS; emission control; fuel consumption; mixed-integer linear program; mixed-logical dynamic approach; mixed-logical dynamic model; model-based predictive control; model-based traffic control; nonconvex METANET traffic flow model; piecewise-affine approximation; total time spent; vehicular emission; Adaptation models; Approximation methods; Computational modeling; Equations; Fuels; Mathematical model; Optimization;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4577-2198-4
DOI :
10.1109/ITSC.2011.6082809