An Analytical Framework for Evaluating Potential Truck Parking Locations

Authors

  • Yun Bai Rutgers University
  • Christian Higgins Rutgers University
  • Na Cui University of Jinan
  • Taesung Hwang Inha University https://orcid.org/0000-0003-1723-4498

DOI:

https://doi.org/10.31686/ijier.vol9.iss9.3334

Keywords:

truck parking, location analysis, cost-benefit analysis

Abstract

As the number of trucks on the road continues to increase, mandatory rest periods combined with a decreasing number of parking spaces and amenities geared towards truck drivers have created a paradoxical yet often overlooked issue of truck parking shortage. Especially within the urbanized landscape of New Jersey, truck stops are rarely considered as the highest and best use form of development and those that exist are often expensive to operate. Most of the existing research on this issue has focused on parking demand modeling or applications of the intelligent transportation system technology to improve the use of existing truck stops. Nonetheless, limited previous research has focused on expanding truck parking capacity. This study develops a methodological framework for evaluating some of the important social, economic, and environmental factors when planning the development of a new truck parking facility. With an example application to the State of New Jersey, this study presents a step-by-step analytical process to help prioritize potential truck parking locations.

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Author Biographies

Yun Bai, Rutgers University

Center for Advanced Infrastructure and Transportation

Christian Higgins, Rutgers University

Center for Advanced Infrastructure and Transportation

Na Cui, University of Jinan

School of Civil Engineering and Architecture

Taesung Hwang, Inha University

Asia Pacific School of Logistics

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Published

01-09-2021

How to Cite

Bai, Y., Higgins, C., Cui, N., & Hwang, T. (2021). An Analytical Framework for Evaluating Potential Truck Parking Locations. International Journal for Innovation Education and Research, 9(9), 240–253. https://doi.org/10.31686/ijier.vol9.iss9.3334