DocumentCode
2820862
Title
Modeling Correlation between Origin-Destination Traffic Demands in Stochastic Transportation Networks
Author
Song, Xiaoqiu ; Shao, Hu ; Wang, Guodong
Author_Institution
Sch. of Sci., China Univ. of Min. & Technol., Xuzhou, China
Volume
2
fYear
2009
fDate
24-26 April 2009
Firstpage
147
Lastpage
149
Abstract
This paper proposes an analytical method to investigate the correlation between origin-destination (OD) demands in stochastic transportation network with demand uncertainty. Different from the existing researches, the OD traffic demand is assumed to follow a multivariate probability distribution, which explicitly considers the correlation between OD demands. Under this assumption, the correlation between path flows and correlation between link flows are also deduced using the proposed analytical method. As a result, the multivariate distribution of link flows and path flows can be obtained, which are further applied in a reliability-based traffic assignment problem. The numerical examples indicate that the correlation between OD demands will influence not only the flow patterns but also the total network travel time. Moreover, the ignorance of correlations between OD demands can either underestimate or overestimate the network congestion.
Keywords
correlation methods; road traffic; statistical distributions; stochastic processes; transportation; analytical method; correlation method; demand uncertainty; link flow; multivariate probability distribution; origin-destination traffic demand; path flow; stochastic transportation network; Analytical models; Computer networks; Large-scale systems; Probability distribution; Random variables; Stochastic processes; Telecommunication traffic; Traffic control; Transportation; Uncertainty; Correlation; Origin-Destination Traffic Demand; Stochastic Transportation Network;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location
Sanya, Hainan
Print_ISBN
978-0-7695-3605-7
Type
conf
DOI
10.1109/CSO.2009.268
Filename
5193918
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