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Published VersionCC BY-NC-SA V4.0, Open Access
Journal article
A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas
Transportation Science, Vol.54(3), pp.606-630
2020
Abstract
Understanding factors that drive the parking choice of commercial vehicles at delivery stops in cities can enhance logistics operations and the management of freight parking infrastructure, mitigate illegal parking, and ultimately reduce traffic congestion. In this paper, we focus on this decision-making process at large urban freight traffic generators, such as retail malls and transit terminals, that attract a large share of urban commercial vehicle traffic. Existing literature on parking behavior modeling has focused on passenger vehicles. This paper presents a discrete choice model for commercial vehicle parking choice in urban areas. The model parameters were estimated by using detailed, real-world data on commercial vehicle parking choices collected in two commercial urban areas in Singapore. The model analyzes the effect of several variables on the parking behavior of commercial vehicle drivers, including the presence of congestion and queueing, attitudes toward illegal parking, and pricing (parking fees). The model was validated against real data and applied within a discrete-event simulation to test the economic and environmental impacts of several parking measures, including pricing strategies and parking enforcement.
Details
- Title
- A Policy-Sensitive Model of Parking Choice for Commercial Vehicles in Urban Areas
- Authors
- Giacomo Dalla Chiara (Corresponding Author) - University of WashingtonLynette Cheah - Singapore University of Technology and DesignCarlos Lima Azevedo - Technical University of DenmarkMoshe E. Ben-Akiva - Massachusetts Institute of Technology
- Publication details
- Transportation Science, Vol.54(3), pp.606-630
- Publisher
- Institute for Operations Research and the Management Sciences (INFORMS)
- Date published
- 2020
- DOI
- 10.1287/trsc.2019.0970
- ISSN
- 1526-5447; 0041-1655
- Copyright note
- This work is licensed under a Creative Commons Attribution-NonCommercialShareAlike 4.0 International License. You are free to download this work and share with others for any purpose, except commercially, if you distribute your contributions under the same license as the original, and you must attribute this work as “Transportation Science. Copyright © 2020 The Author(s). https://doi.org/10.1287/trsc.2019.0970, used under a Creative Commons Attribution License: https://creativecommons.org/licenses/by-nc-sa/4.0/.”
- Grant note
- This work was supported in part by the Info-communications Media Development Authority of Singapore
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991029388402621
- Output Type
- Journal article
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- Operations Research & Management Science
- Transportation
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