Minimal revenue network tolling: system optimisation under stochastic assignment with elastic demand.

Stewart, Kathryn and Maher, Mike (2007) Minimal revenue network tolling: system optimisation under stochastic assignment with elastic demand. In: Mathematics in transport : selected proceedings of the 4th IMA International Conference on Mathematics in Transport : in honour of Richard Allsop. Elsevier, pp. 201-218. ISBN 9780080536767

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The classical road tolling problem is to toll network links such that, under the principles of Wardropian User Equilibrium (UE) assignment, a System Optimising (SO) flow pattern is obtained. Such toll sets are however non-unique, and further optimisation is possible: for example, minimal revenue tolls create the desired SO flow pattern at minimal additional cost to the users. In the case of deterministic assignment, the minimal revenue toll problem is capable of solution by various methods, such as linear programming [BHR97] and heuristically by reduction to a multi-commodity max-flow problem [Dia00]. However, it is generally accepted that deterministic models are less realistic than stochastic, and thus it is of interest to investigate the principles of tolling under stochastic modelling conditions. This paper develops methodologies to examine the minimal revenue toll problem in the case of Stochastic User Equilibrium. Tolling solutions for both ‘true’ System Optimum and Stochastic System Optimum under SUE are derived, using both logit and probit assignment methods.

Item Type: Book Section
ISBN: 9780080536767
Uncontrolled Keywords: Traffic assignment; Stochastic user equilibrium; Probit model; Logit model; Optimal tolls; Marginal social costs;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment
Dewey Decimal Subjects: 300 Social sciences > 380 Commerce, communications & transportation > 388 Transportation; ground transportation
Library of Congress Subjects: H Social Sciences > HE Transportation and Communications
Item ID: 1968
Depositing User: RAE Import
Date Deposited: 13 Jun 2008 09:45
Last Modified: 14 May 2015 10:29

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