<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper applies a bi-level formalism for the optimal control of an urban transportation network. The well known store-and-forward model in traffic control is utilized in order to increase the control space of the optimization problem. Mainly, the store-and-forward models apply the split as a control argument, assuming the traffic light cycle as a constant parameter. The paper shows that by using a bi-level formalism the control problem can be defined within increased control space comprising both the split and the cycle. Both are found as optimal solutions of a bi-level optimization problem.</p></abstract>

This paper applies a bi-level formalism for the optimal control of an urban transportation network. The well known store-and-forward model in traffic control is utilized in order to increase the control space of the optimization problem. Mainly, the store-and-forward models apply the split as a control argument, assuming the traffic light cycle as a constant parameter. The paper shows that by using a bi-level formalism the control problem can be defined within increased control space comprising both the split and the cycle. Both are found as optimal solutions of a bi-level optimization problem.

Bi-Level Optimization in a Transport Network

Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia 1113

Dynamic Systems and Simulation Laboratory, Technical University of Crete, Chania, Greece

Cybernetics and Information Technologies

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

{"article-title":"Bi-Level Optimization in a Transport Network"}

This paper applies a bi-level formalism for the optimal control of an urban transportation network. The well known store-and-forward model in traffic control...

Bi-Level Optimization in a Transport Network

Publié en ligne: 30 avr. 2015

Pages: 37 - 49

DOI: https://doi.org/10.1515/cait-2015-0015

© by Todor Stoilov

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