An Analytical Framework for Evaluating Potential Truck Parking Locations

International Journal for Innovation Education and Research

View Publication Info
 
 
Field Value
 
Title An Analytical Framework for Evaluating Potential Truck Parking Locations
 
Creator Bai, Yun
Higgins, Christian
Cui, Na
Hwang, Taesung
 
Subject truck parking
location analysis
cost-benefit analysis
 
Description 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.
 
Publisher International Educative Research Foundation Publisher (IERFP)
 
Date 2021-09-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://ijier.net/ijier/article/view/3334
10.31686/ijier.vol9.iss9.3334
 
Source International Journal for Innovation Education and Research; Vol. 9 No. 9 (2021): International Journal for Innovation Education and Research; 240-253
2411-2933
2411-3123
 
Language eng
 
Relation https://ijier.net/ijier/article/view/3334/2276
 
Rights Copyright (c) 2021 Yun Bai, Christian Higgins, Na Cui, Taesung Hwang
https://creativecommons.org/licenses/by-nd/4.0
 

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