Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions
Speed measurement is essential for the development of Intelligent Traffic Systems (ITS), and the adoption and enforcement of appropriate speed limits are among the most effective strategies to improve road safety. This review offers an exhaustive exploration of vehicle speed measurement methods and...
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| Format: | Article |
| Language: | English |
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ELS Publishing (ELSP)
2024-07-01
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| Series: | Artificial Intelligence and Autonomous Systems |
| Subjects: | |
| Online Access: | https://elsp-homepage.oss-cn-hongkong.aliyuncs.compaper/journal/open/AIAS/2024/aias20240004.pdf |
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| _version_ | 1849762702095810560 |
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| author | Zhili Chen Fang Guo Longmei Luo |
| author_facet | Zhili Chen Fang Guo Longmei Luo |
| author_sort | Zhili Chen |
| collection | DOAJ |
| description | Speed measurement is essential for the development of Intelligent Traffic Systems (ITS), and the adoption and enforcement of appropriate speed limits are among the most effective strategies to improve road safety. This review offers an exhaustive exploration of vehicle speed measurement methods and technologies within traffic applications. While inductive loop detectors and radar are mature technologies in traffic speed measurement, cameras are typically used to facilitate license plate recognition. This paper delves into the principles and technologies behind traditional speed measurement systems such as inductive loop detectors, wireless radar, LiDAR, and the Global Positioning System, alongside computer vision-based speed measurement. It examines the evolution of computer vision, reviews common datasets, and explores the feasibility of using cameras for direct speed measurement. Furthermore, this paper evaluates the precision, cost, and practicality of these technologies and discusses future research directions, providing crucial references and guidance for advancing Intelligent Traffic Systems. |
| format | Article |
| id | doaj-art-595d0799bb9f41eaa28fd82946c732f3 |
| institution | DOAJ |
| issn | 2959-0744 2959-0752 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | ELS Publishing (ELSP) |
| record_format | Article |
| series | Artificial Intelligence and Autonomous Systems |
| spelling | doaj-art-595d0799bb9f41eaa28fd82946c732f32025-08-20T03:05:41ZengELS Publishing (ELSP)Artificial Intelligence and Autonomous Systems2959-07442959-07522024-07-011213010.55092/aias202400041751411039036493824Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directionsZhili Chen0Fang Guo1Longmei Luo2School of Computer Science and Mathematics, FuJian University of Technology, Fuzhou, ChinaSchool of Computer Science and Mathematics, FuJian University of Technology, Fuzhou, ChinaSchool of Computer Science and Mathematics, FuJian University of Technology, Fuzhou, ChinaSpeed measurement is essential for the development of Intelligent Traffic Systems (ITS), and the adoption and enforcement of appropriate speed limits are among the most effective strategies to improve road safety. This review offers an exhaustive exploration of vehicle speed measurement methods and technologies within traffic applications. While inductive loop detectors and radar are mature technologies in traffic speed measurement, cameras are typically used to facilitate license plate recognition. This paper delves into the principles and technologies behind traditional speed measurement systems such as inductive loop detectors, wireless radar, LiDAR, and the Global Positioning System, alongside computer vision-based speed measurement. It examines the evolution of computer vision, reviews common datasets, and explores the feasibility of using cameras for direct speed measurement. Furthermore, this paper evaluates the precision, cost, and practicality of these technologies and discusses future research directions, providing crucial references and guidance for advancing Intelligent Traffic Systems.https://elsp-homepage.oss-cn-hongkong.aliyuncs.compaper/journal/open/AIAS/2024/aias20240004.pdfintelligent trafficvehicle speed measurementaccuracymulti-sensor fusionlong-range |
| spellingShingle | Zhili Chen Fang Guo Longmei Luo Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions Artificial Intelligence and Autonomous Systems intelligent traffic vehicle speed measurement accuracy multi-sensor fusion long-range |
| title | Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions |
| title_full | Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions |
| title_fullStr | Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions |
| title_full_unstemmed | Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions |
| title_short | Vehicle speed measurement technologies in Intelligent Transportation Systems: current status, challenges and future directions |
| title_sort | vehicle speed measurement technologies in intelligent transportation systems current status challenges and future directions |
| topic | intelligent traffic vehicle speed measurement accuracy multi-sensor fusion long-range |
| url | https://elsp-homepage.oss-cn-hongkong.aliyuncs.compaper/journal/open/AIAS/2024/aias20240004.pdf |
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