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...
Published in: | Planning Malaysia |
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Malaysian Institute Of Planners
2023
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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 |
_version_ |
1809677588826685440 |