A Framework for Providing Information about Parking Spaces
(2023) In Sustainability (Switzerland) 15(19).- 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... (More)
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.
(Less)
- author
- Nadimi, Navid ; Zayandehroodi, Mohammad Ali ; Camporeale, Rosalia LU and Asadamraji, Morteza
- organization
- publishing date
- 2023-10
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Naïve Bayes, parking demand, planning, pricing factors
- in
- Sustainability (Switzerland)
- volume
- 15
- issue
- 19
- article number
- 14505
- publisher
- MDPI AG
- external identifiers
-
- scopus:85174172262
- ISSN
- 2071-1050
- DOI
- 10.3390/su151914505
- language
- English
- LU publication?
- yes
- id
- 4dbdc176-a5c9-4f63-bc38-4e946da2b67c
- date added to LUP
- 2023-12-11 14:36:55
- date last changed
- 2023-12-11 14:38:19
@article{4dbdc176-a5c9-4f63-bc38-4e946da2b67c,
abstract = {{<p>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.</p>}},
author = {{Nadimi, Navid and Zayandehroodi, Mohammad Ali and Camporeale, Rosalia and Asadamraji, Morteza}},
issn = {{2071-1050}},
keywords = {{Naïve Bayes; parking demand; planning; pricing factors}},
language = {{eng}},
number = {{19}},
publisher = {{MDPI AG}},
series = {{Sustainability (Switzerland)}},
title = {{A Framework for Providing Information about Parking Spaces}},
url = {{http://dx.doi.org/10.3390/su151914505}},
doi = {{10.3390/su151914505}},
volume = {{15}},
year = {{2023}},
}