Modelling route choice behaviour in a tolled road network with a time surplus maximisation bi-objective user equilibrium model

Wang, Judith Y. T. and Ehrgott, Matthias (2013) Modelling route choice behaviour in a tolled road network with a time surplus maximisation bi-objective user equilibrium model. Transportation Research Part B: Methodological, 57. pp. 342-360. ISSN 0191-2615

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Abstract

In this paper, we propose a novel approach to model route choice behaviour in a tolled road network with a bi-objective approach, assuming that all users have two objectives: (1) minimise travel time; and (2) minimise toll cost. We assume further that users have different preferences in the sense that for any given path with a specific toll, there is a limit on the time that an individual would be willing to spend. Different users can have different preferences represented by this indifference curve between toll and time. Time surplus is defined as the maximum time minus the actual time. Given a set of paths, the one with the highest (or least negative) time surplus will be the preferred path for the individual. This will result in a bi-objective equilibrium solution satisfying the time surplus maximisation bi-objective user equilibrium (TSmaxBUE) condition. That is, for each O–D pair, all individuals are travelling on the path with the highest time surplus value among all the efficient paths between this O–D pair. We show that the TSmaxBUE condition is a proper generalisation of user equilibrium with generalised cost function, and that it is equivalent to bi-objective user equilibrium. We also present a multi-user class version of the TSmaxBUE condition and demonstrate our concepts with illustrative examples.

Item Type:
Journal Article
Journal or Publication Title:
Transportation Research Part B: Methodological
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/aacsb/disciplinebasedresearch
Subjects:
ID Code:
66101
Deposited By:
Deposited On:
19 Aug 2013 10:21
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Mar 2020 03:31