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A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows

Maher, M.J., Zhang, X. and van Vliet, D. (2001) A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows. Transportation Research Part B : Methodological, 35 (1). pp. 23-40. ISSN 0191-2615

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Abstract

This paper deals with two mathematically similar problems in transport network analysis: trip matrix estimation and traffic signal optimisation on congested road networks. These two problems are formulated as bi-level programming problems with stochastic user equilibrium assignment as the second-level programming problem. We differentiate two types of solutions in the combined matrix estimation and stochastic user equilibrium assignment problem (or, the combined signal optimisation and stochastic user equilibrium assignment problem): one is the solution to the bi-level programming problem and the other the mutually consistent solution where the two sub-problems in the combined problem are solved simultaneously. In this paper, we shall concentrate on the bi-level programming approach although we shall also consider mutually consistent solutions so as to contrast the two types of solutions. The purpose of the paper is to present a solution algorithm for the two bi-level programming problems and to test the algorithm on several networks.

Item Type: Article
Copyright, Publisher and Additional Information: Copyright © 2001 Elsevier Science Ltd. This is an author produced version of a paper subsequently published in 'Transportation Research Part B'. Uploaded in accordance with the self-archiving policy of the publisher.
Keywords: trip matrix estimation, traffic signal optimisation, stochastic user equilibrium assignment, mathematical programming
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Adrian May
Date Deposited: 10 May 2007
Last Modified: 24 Jul 2014 14:01
Published Version: http://dx.doi.org/10.1016/S0191-2615(00)00017-5
Status: Published
Publisher: Elsevier Science
Refereed: Yes
Identification Number: 10.1016/S0191-2615(00)00017-5
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/2459

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