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Tucson, AZ, United States

Khani A.,University of Texas at Austin | Bustillos B.,University of Arizona | Noh H.,Pima Association of Governments | Chiu Y.-C.,University of Arizona | Hickman M.,University of Queensland
Transportation Research Record | Year: 2014

A fixed-point formulation and a simulation-based solution method were developed for modeling intermodal passenger tours in a dynamic transportation network. The model proposed in this paper is a combined model of a dynamic traffic assignment, a schedule-based transit assignment, and a park-and-ride choice model, which assigns intermodal demand (i.e., passengers with drive-to-transit mode) to the optimal park-and-ride station. The proposed model accounts for all segments of passenger tours in the passengers' daily travel, incorporates the constraint on returning to the same park-and-ride location in a tour, and models individual passengers at a disaggregate level. The model has been applied in an integrated travel demand model in Sacramento, California, and feedback to the activity-based demand model is provided through separate time-dependent skim tables for auto, transit, and intermodal trips. Source


Khani A.,University of Texas at Austin | Hickman M.,University of Queensland | Noh H.,Pima Association of Governments
Networks and Spatial Economics | Year: 2014

In this paper, we propose a new network representation for modeling schedule-based transit systems. The proposed network representation, called trip-based, uses transit vehicle trips as network edges and takes into account the transfer stop hierarchy in transit networks. Based on the trip-based network, we propose a set of path algorithms for schedule-based transit networks, including algorithms for the shortest path, a logit-based hyperpath, and a transit A*. The algorithms are applied to a large-scale transit network and shown to have better computational performance compared to the existing labeling algorithms. © 2014 Springer Science+Business Media New York. Source

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