A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand

Hu Shao (), William Lam and Mei Tam

Networks and Spatial Economics, 2006, vol. 6, issue 3, 173-204

Abstract: This paper presents a novel reliability-based stochastic user equilibrium traffic assignment model in view of the day-to-day demand fluctuations for multi-class transportation networks. In the model, each class of travelers has a different safety margin for on-time arrival in response to the stochastic travel times raised from demand variations. Travelers' perception errors on travel time are also considered in the model. This model is formulated as an equivalent variational inequality problem, which is solved by the proposed heuristic solution algorithm. Numerical examples are presented to illustrate the applications of the proposed model and the efficiency of solution algorithm. Copyright Springer Science + Business Media, LLC 2006

Keywords: Reliability-based; Multiple user classes; Demand variations; Variational inequality; Traffic assignment problem (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (55)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11067-006-9279-6 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:netspa:v:6:y:2006:i:3:p:173-204

Ordering information: This journal article can be ordered from
http://www.springer. ... ce/journal/11067/PS2

DOI: 10.1007/s11067-006-9279-6

Access Statistics for this article

Networks and Spatial Economics is currently edited by Terry L. Friesz

More articles in Networks and Spatial Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().