Home / Current Issue / Paper 1707129
Assessment of the Impact of Parking Pattern on Traffic Flow in Selected Market Centres in Ogbomoso, Oyo State, Nigeria
Subject area: Science,Engineering and Technology · Area of research: Transport Management
Abstract
Analysis of parking patterns serves as a foundational step towards understanding the dynamics of urban mobility and providing valuable insights for policymakers, urban planners, and stakeholders involved in transportation management. Currently, there is no effective parking management system in most of the market centres in Ogbomoso, Oyo state. A structured questionnaire was administered to a sample size comprising 288 traders, 201 drivers and 363 visitors/customers, using a combination of incidental and purposive sampling techniques. Multiple regression analysis was used in analysing the data obtained. The analysis revealed that factors such as parking occupancy rates, parking duration, peak demand periods, limited parking spaces, and access and egress points significantly influence traffic flow.
Keywords
Parking Pattern, Traffic Flow, Parking Demand, Parking Supply, Occupancy Rate, Parking Duration, Drivers, Visitors
How to cite this paper
@article{1707129,
author = {Ayantoyinbo Benedict B., Okekunle Oluwatobi Tosin, Adebanjo Adeola A.},
title = {Assessment of the Impact of Parking Pattern on Traffic Flow in Selected Market Centres in Ogbomoso, Oyo State, Nigeria},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {8},
pages = {326-334},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707129.pdf},
abstract = {Analysis of parking patterns serves as a foundational step towards understanding the dynamics of urban mobility and providing valuable insights for policymakers, urban planners, and stakeholders involved in transportation management. Currently, there is no effective parking management system in most of the market centres in Ogbomoso, Oyo state. A structured questionnaire was administered to a sample size comprising 288 traders, 201 drivers and 363 visitors/customers, using a combination of incidental and purposive sampling techniques. Multiple regression analysis was used in analysing the data obtained. The analysis revealed that factors such as parking occupancy rates, parking duration, peak demand periods, limited parking spaces, and access and egress points significantly influence traffic flow.},
keywords = {Parking Pattern, Traffic Flow, Parking Demand, Parking Supply, Occupancy Rate, Parking Duration, Drivers, Visitors},
month = {February},
}