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Stochastic congestion and pricing model with endogenous departure time selection and heterogeneous travelers

Wuping Xin and David Levinson

No 29, Working Papers from University of Minnesota: Nexus Research Group

Abstract: This paper proposes a stochastic congestion and pricing model that combines a bottleneck model with stochastic queuing to study roadway congestion and pricing. Employing this model, two pricing schemes are developed: one is omniscient pricing for which the transportation administrative agency is assumed to be aware of each and every traveler's cost structure (i.e., their detailed valuation of journey cost as well as early and late penalties), and the other is observable pricing, for which only queuing delay is considered. Travelers are characterized by their late-acceptance level and the effects of various compositions of late-averse, late-tolerant and late-neutral travelers on congestion patterns with and without pricing are discussed. Numerical simulation indicates that omniscient pricing scheme is most effective in suppressing peak hour congestion and distributing demands over longer time horizon. Also, congestion pricing is found to be more effective when travelers have diversified cost structures than identical cost structures, and congestion is better reduced with heterogeneous traveler composition than with single composition. This is consistent with earlier studies in the literature. In addition, the simulation results indicate that omniscient pricing in general reduces Expected Total Social Cost

Keywords: Agent-based Model; Game Theory; Congestion; Queueing; Traffic Flow; Congestion Pricing; Road Pricing; Value Pricing (search for similar items in EconPapers)
JEL-codes: C72 D10 D81 D83 R41 R42 R48 (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-cmp, nep-net and nep-tur
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Published in Mathematical Population Studies 22(1) pp.37- 52.

Downloads: (external link) Second version, 2015 (application/pdf)

Related works:
Journal Article: Stochastic Congestion and Pricing Model with Endogenous Departure Time Selection and Heterogeneous Travelers (2015) Downloads
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