2013
DOI: 10.1016/j.endm.2013.05.100
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Optimizing Toll Enforcement in Transportation Networks: a Game-Theoretic Approach

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Cited by 13 publications
(23 citation statements)
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“…Usually, the quality of service measurement is estimated using surveys sent to costumers. A notable exception is the work of Borndörfer et al (2013), who write about a highway with tolls. In their case, the control decision is how often one should check whether drivers had paid the toll in a highway to minimize evasion.…”
Section: Mathematical Programmingmentioning
confidence: 95%
“…Usually, the quality of service measurement is estimated using surveys sent to costumers. A notable exception is the work of Borndörfer et al (2013), who write about a highway with tolls. In their case, the control decision is how often one should check whether drivers had paid the toll in a highway to minimize evasion.…”
Section: Mathematical Programmingmentioning
confidence: 95%
“…As an alternative approach, we have proposed in a companion work a game theoretic approach that takes into account the behavior of drivers and fare evaders to distribute the controls in a more strategic way, see Borndörfer et al (2012aBorndörfer et al ( , 2013. The output there is not a roster or a tour plan but a probability distribution of the inspectors force over all arcs of the network.…”
Section: Problem Classificationmentioning
confidence: 98%
“…In addition, advanced problem specific algorithmic approaches like heuristics, multi-level algorithms or branch and price can be developed and investigated. A further aspect is the generation of rosters based on a mixed strategy of the inspectors which is the output of the game-theoretic approach from a companion paper (Borndörfer et al 2013). The mixed strategy corresponds to a probability distribution over the arcs of the toll network.…”
Section: Conclusion and Future Researchmentioning
confidence: 99%
“…A SC game G = ( G , C , W , Q , α ) is formally defined by the following elements: A directed graph G = ( V , E ); A set of weighted commodities C : = { ( s k , d k , x k ) , k K } , representing origin‐destination pairs ( s k , d k ) V 2 with x k > 0 users; A set of arc weights W : = { ( w e , β e , σ e ) , e E } , representing: A set Q [ 0 , 1 ] | E | described by linear inequalities, representing possible distributions of the inspectors over the arcs of the graph. The quantity q e corresponds to the probability that some inspector is present on arc e ; A fraction α of penalties to be considered in the inspector's payoff. …”
Section: Spot‐checking Gamesmentioning
confidence: 99%
“…We start by showing that the model used in the conference paper at the origin of this article can be cast as a SC game. Here, the network users are assumed to travel over a network G 0 = ( V 0 , E 0 ) with arc costs w e and expected penalties σ e (conditionally to the presence of a controller on arc e ).…”
Section: Handling Practical Situations With Sc Gamesmentioning
confidence: 99%