Two-Stage Bicycle Traffic Assignment Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 2
Abstract
Cycling has been considered as a healthy, environmentally friendly, and economical alternative mode of travel to motorized vehicles (especially private motorized vehicles). However, bicycles have often been neglected in the transportation planning and travel demand forecasting modeling processes. The current practice in modeling bicycle trips in a network is either nonexistent or too simplistic. Current practices are simply based on the all-or-nothing (AON) assignment method using single attributes such as distance, safety, or a composite measure of safety multiplied by distance. The purpose of this paper is to develop a two-stage traffic assignment model by considering key factors (or criteria) in cyclist route choice behavior. As an initial effort, the first stage considers two key criteria (distance-related attributes and safety-related attributes) to generate a set of nondominated (or efficient) paths. These two criteria are a composite function of subcriteria. Route distance consists of link distances and intersection turning penalties combined to give the distance-related attribute, while route safety makes use of the bicycle level of service (BLOS) measure developed by the Highway Capacity Manual (HCM) to determine the safety-related attribute. Efficient paths are generated based on the above two key criteria with a biobjective shortest path algorithm. The second stage determines the flow allocation to the set of efficient paths. Several traffic assignment methods are adopted to determine the flow allocations in a network. Numerical experiments are then conducted to demonstrate the two-stage approach for bicycle traffic assignment. Overall, the results of the Winnipeg network demonstrate the applicability of the two-stage bicycle traffic assignment procedure with the flexibility of using different criteria in the first stage to generate efficient paths and different traffic assignment methods in the second stage to allocate flows.
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Acknowledgments
This research was supported by the Mountain-Plains Consortium (MPC) and the Transportation Research Center for Livable Communities (TRCLC) sponsored by the U.S. Department of Transportation, the U.S. Department of Transportation through their Federal Highway Administration Eisenhower Transportation Graduate Fellowship program, the Research Committee of the Hong Kong Polytechnic University (Project No. 1-ZE5T), the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Minis (NRF-2016R1C1B2016254), and the National Research Foundation of Korea grant funded by the Korean government (NRF-2010-0029443). This support is gratefully acknowledged.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 2 • February 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Mar 29, 2017
Accepted: Jul 14, 2017
Published online: Dec 13, 2017
Published in print: Feb 1, 2018
Discussion open until: May 13, 2018
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