A Framework for Providing Information about Parking Spaces

Navid Nadimi (), Mohammad Ali Zayandehroodi, Rosalia Camporeale and Morteza Asadamraji
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Navid Nadimi: Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman 76169-14111, Iran
Mohammad Ali Zayandehroodi: Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman 76169-14111, Iran
Rosalia Camporeale: Department of Technology and Society, Lund University, 223 62 Lund, Sweden
Morteza Asadamraji: Faculty of Civil, Water and Environment Engineering, Shahid Beheshti University, Tehran 19839-69411, Iran

Sustainability, 2023, vol. 15, issue 19, 1-16

Abstract: There is a serious imbalance between parking demand and capacity in cities due to limitations in their parking facilities. It is important for drivers to know about parking vacancies before their trips. Meanwhile, administrators need information about parking capacity and demand before a week begins to improve parking management. A method is proposed here for predicting parking demand and capacity by utilizing a Naïve Bayes model and different variables such as drivers’ characteristics and their trips, environmental conditions, parking attributes, and vehicle specifications. Tehran (Iran) is used as a case study etfor testing the model. Using the proposed model, it is possible to identify which parking facilities (and when) might experience spillover. For parking management and policy, demand management, and providing information about parking availability for drivers before their trips, this can be helpful.

Keywords: parking demand; Naïve Bayes; pricing factors; planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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