Evolutionary game-theoretic model for dynamic congestion pricing in multi-class traffic networks

Dimitriou, L; Tsekeris, T

dc.contributor.author	Dimitriou, L	en
dc.contributor.author	Tsekeris, T	en
dc.date.accessioned	2014-03-01T01:30:27Z
dc.date.available	2014-03-01T01:30:27Z
dc.date.issued	2009	en
dc.identifier.issn	13859587	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19582
dc.subject	Dynamic congestion pricing	en
dc.subject	Evolutionary game theory	en
dc.subject	Routing information	en
dc.subject	Stochastic assignment models	en
dc.subject	Urban road networks	en
dc.title	Evolutionary game-theoretic model for dynamic congestion pricing in multi-class traffic networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11066-008-9027-9	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11066-008-9027-9	en
heal.publicationDate	2009	en
heal.abstract	This paper describes an evolutionary game-theoretic learning model for dynamic congestion pricing in urban road networks, taking into account route choice stochasticity and reliability considerations, and the heterogeneity of users, in terms of their value of travel time and real-time information acquisition. The learning model represents the dynamic adjustments of users to travel cost changes which may take place in the day-to-day as well as the within-day timescales. The implementation into a simplified and a real urban road network signifies the important implications of modeling the dynamic and stochastic learning components of users' behavior for accommodating the efficient deployment of congestion pricing schemes. © Springer Science+Business Media, LLC. 2008.	en
heal.journalName	NETNOMICS: Economic Research and Electronic Networking	en
dc.identifier.doi	10.1007/s11066-008-9027-9	en
dc.identifier.volume	10	en
dc.identifier.issue	1	en
dc.identifier.spage	103	en
dc.identifier.epage	121	en