Technical Papers
Jun 15, 2012

Estimation of Urban Transportation Network Capacity Considering Traveler Road Preferences

Publication: Journal of Urban Planning and Development
Volume 138, Issue 2

Abstract

Network capacity is one of the most important ways to measure the transportation system’s capacity to accommodate traffic demand. This paper presents an approach to estimate the capacity of urban transportation network considering more realistic traveler route choices. Different from previous studies, this research introduces a set of determinants that may reflect realistic traveler route choices including not only travel times but also traveler preferences (e.g., road familiarity, road configuration). This study formulates the route choice model with the new set of determinants and incorporates it into the network capacity model. An improved iterative assignment approach is designed to solve the network capacity model in which unrealistic detours by travelers will be eliminated. The proposed model and algorithm are applied in a test network; numerical results have revealed that the proposed model is not only capable of realistically estimating the network capacity under various levels of service, but also identifying critical links that are neglected by traditional approaches. Research findings offer guidelines for transportation agencies in preparing better and more pertinent management strategies to accommodate various traffic demand situations.

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 138Issue 2June 2012
Pages: 133 - 142

History

Received: May 8, 2011
Accepted: Nov 22, 2011
Published online: Nov 24, 2011
Published in print: Jun 1, 2012
Published ahead of production: Jun 15, 2012

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Authors

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Graduate Student, Dept. of Civil Engineering and Mechanics, Univ. of Wisconsin at Milwaukee, P.O. Box 784, Milwaukee, WI 53201-0784. E-mail: [email protected]
Yue Liu, A.M.ASCE [email protected]
Assistant Professor, Dept. of Civil Engineering and Mechanics, Univ. of Wisconsin at Milwaukee, P.O. Box 784, Milwaukee, WI 53201-0784 (corresponding author). E-mail: [email protected]
Associate Professor, School of Control Science and Engineering, Shandong Univ., No. 17923 Jingshi Rd., Jinan, Shandong, China. E-mail: [email protected]

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