VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES

This study provides an overview of the sensor technologies commonly used for automated vehicle classification and counting, with a focus on non-intrusive sensors. Video cameras are found to be the most feasible solution for data collection in traffic census as it can operate in portable mode and use...

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Published in:Planning Malaysia
Main Author: Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
Format: Article
Language:English
Published: Malaysian Institute Of Planners 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173506503&doi=10.21837%2fpm.v21i28.1316&partnerID=40&md5=37a546fd1a9e22db440ee0e54a9cd6ce
id 2-s2.0-85173506503
spelling 2-s2.0-85173506503
Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
2023
Planning Malaysia
21
4
10.21837/pm.v21i28.1316
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173506503&doi=10.21837%2fpm.v21i28.1316&partnerID=40&md5=37a546fd1a9e22db440ee0e54a9cd6ce
This study provides an overview of the sensor technologies commonly used for automated vehicle classification and counting, with a focus on non-intrusive sensors. Video cameras are found to be the most feasible solution for data collection in traffic census as it can operate in portable mode and used at any location. Several factors must be considered to ensure accurate counting. These involve optimum placement of the camera to ensure that all vehicles can be observed, and the lighting conditions must be considered to ensure good videoquality. These further contributes to accurate classification and counting of vehicles by dedicated deep learning algorithm. As the data collection may involve location with poor access to cloud computing and storage, offline processing is therefore recommended. The study also revealed opportunities for solving issues related to strategic placement of video cameras, and development of dedicated deep learning algorithms. © 2023 by MIP.
Malaysian Institute Of Planners
16756215
English
Article
All Open Access; Hybrid Gold Open Access
author Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
spellingShingle Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
author_facet Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
author_sort Shariff K.K.M.; Ali M.Q.Z.M.; Jahidin A.H.; Ali M.S.A.M.; Yassin A.I.M.
title VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
title_short VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
title_full VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
title_fullStr VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
title_full_unstemmed VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
title_sort VIDEO CAMERA TECHNOLOGY FOR VEHICLE COUNTING IN TRAFFIC CENSUS: ISSUES, STRATEGIES AND OPPORTUNITIES
publishDate 2023
container_title Planning Malaysia
container_volume 21
container_issue 4
doi_str_mv 10.21837/pm.v21i28.1316
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173506503&doi=10.21837%2fpm.v21i28.1316&partnerID=40&md5=37a546fd1a9e22db440ee0e54a9cd6ce
description This study provides an overview of the sensor technologies commonly used for automated vehicle classification and counting, with a focus on non-intrusive sensors. Video cameras are found to be the most feasible solution for data collection in traffic census as it can operate in portable mode and used at any location. Several factors must be considered to ensure accurate counting. These involve optimum placement of the camera to ensure that all vehicles can be observed, and the lighting conditions must be considered to ensure good videoquality. These further contributes to accurate classification and counting of vehicles by dedicated deep learning algorithm. As the data collection may involve location with poor access to cloud computing and storage, offline processing is therefore recommended. The study also revealed opportunities for solving issues related to strategic placement of video cameras, and development of dedicated deep learning algorithms. © 2023 by MIP.
publisher Malaysian Institute Of Planners
issn 16756215
language English
format Article
accesstype All Open Access; Hybrid Gold Open Access
record_format scopus
collection Scopus
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