Estimation of Urban Transportation Network Capacity Considering Traveler Road Preferences

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.