Predictive Logistic Models for Off-Street Parking Policy

The land in city centers is typically used for commercial and industrial purposes, leading to increased traffic congestion. To promote more efficient, sustainable, and accessible land use in city centers, it is necessary to manage incoming traffic flow and travel demands effectively. This can be ach...

Full description

Saved in:
Bibliographic Details
Main Author: Nahla H. Alaswadko
Format: Article
Language:English
Published: Koya University 2025-02-01
Series:ARO-The Scientific Journal of Koya University
Subjects:
Online Access:http://88.198.206.215/index.php/aro/article/view/1851
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832574147642785792
author Nahla H. Alaswadko
author_facet Nahla H. Alaswadko
author_sort Nahla H. Alaswadko
collection DOAJ
description The land in city centers is typically used for commercial and industrial purposes, leading to increased traffic congestion. To promote more efficient, sustainable, and accessible land use in city centers, it is necessary to manage incoming traffic flow and travel demands effectively. This can be achieved by implementing appropriate parking policies, which should be predicted carefully to avoid adverse effects on human and economic activities. A case study is conducted in Duhok city, Iraq, aims to estimate the potential responses of city center travelers to reasonable off-street parking restriction policies. Real data were gathered through interviews with a quantitative sample of drivers to assess their reactions to two policies: increasing parking fees and reducing available parking spaces. The study examines central parkers’ socio-demographic and travel characteristics, including origin, trip purpose, timing, parking duration, search time, payment, income, age, and car occupancy. The study presents the results of two binary logistic models used to estimate the probability of implementing new parking policies to alleviate traffic congestion and improve movement. The findings suggest that travelers are more inclined to change their mode of transportation or travel time of day rather than altering their destination or canceling their trip. The findings contribute to the ongoing discourse on sustainable urban development and offer practical solutions for addressing the complex challenges associated with traffic volume and movement control in developing cities. This study aims to contribute to the growing body of knowledge on sustainable urban transportation planning and offer practical recommendations for transportation authorities.
format Article
id doaj-art-1e1877b1962e429ab9c827dbe8161296
institution Kabale University
issn 2410-9355
2307-549X
language English
publishDate 2025-02-01
publisher Koya University
record_format Article
series ARO-The Scientific Journal of Koya University
spelling doaj-art-1e1877b1962e429ab9c827dbe81612962025-02-02T00:31:24ZengKoya UniversityARO-The Scientific Journal of Koya University2410-93552307-549X2025-02-0113110.14500/aro.11851Predictive Logistic Models for Off-Street Parking PolicyNahla H. Alaswadko0Department of Civil Engineering, College of Engineering, University of Duhok, Duhok, Kurdistan Region – F.R. IraqThe land in city centers is typically used for commercial and industrial purposes, leading to increased traffic congestion. To promote more efficient, sustainable, and accessible land use in city centers, it is necessary to manage incoming traffic flow and travel demands effectively. This can be achieved by implementing appropriate parking policies, which should be predicted carefully to avoid adverse effects on human and economic activities. A case study is conducted in Duhok city, Iraq, aims to estimate the potential responses of city center travelers to reasonable off-street parking restriction policies. Real data were gathered through interviews with a quantitative sample of drivers to assess their reactions to two policies: increasing parking fees and reducing available parking spaces. The study examines central parkers’ socio-demographic and travel characteristics, including origin, trip purpose, timing, parking duration, search time, payment, income, age, and car occupancy. The study presents the results of two binary logistic models used to estimate the probability of implementing new parking policies to alleviate traffic congestion and improve movement. The findings suggest that travelers are more inclined to change their mode of transportation or travel time of day rather than altering their destination or canceling their trip. The findings contribute to the ongoing discourse on sustainable urban development and offer practical solutions for addressing the complex challenges associated with traffic volume and movement control in developing cities. This study aims to contribute to the growing body of knowledge on sustainable urban transportation planning and offer practical recommendations for transportation authorities. http://88.198.206.215/index.php/aro/article/view/1851City center travelerLogistic modelParker travelling decisionParking policyResponse modelling
spellingShingle Nahla H. Alaswadko
Predictive Logistic Models for Off-Street Parking Policy
ARO-The Scientific Journal of Koya University
City center traveler
Logistic model
Parker travelling decision
Parking policy
Response modelling
title Predictive Logistic Models for Off-Street Parking Policy
title_full Predictive Logistic Models for Off-Street Parking Policy
title_fullStr Predictive Logistic Models for Off-Street Parking Policy
title_full_unstemmed Predictive Logistic Models for Off-Street Parking Policy
title_short Predictive Logistic Models for Off-Street Parking Policy
title_sort predictive logistic models for off street parking policy
topic City center traveler
Logistic model
Parker travelling decision
Parking policy
Response modelling
url http://88.198.206.215/index.php/aro/article/view/1851
work_keys_str_mv AT nahlahalaswadko predictivelogisticmodelsforoffstreetparkingpolicy