Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing
This paper proposes a novel method for traffic flow detection using distributed optical fiber acoustic sensing (DAS). Different from the traditional traffic flow detection method, this method detects the traffic vibration signal using a fiber optic cable. Distributed fiber-optic acoustic sensing tec...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8453776/ |
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| _version_ | 1849717583198027776 |
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| author | Huiyong Liu Jihui Ma Wenfa Yan Wensheng Liu Xi Zhang Congcong Li |
| author_facet | Huiyong Liu Jihui Ma Wenfa Yan Wensheng Liu Xi Zhang Congcong Li |
| author_sort | Huiyong Liu |
| collection | DOAJ |
| description | This paper proposes a novel method for traffic flow detection using distributed optical fiber acoustic sensing (DAS). Different from the traditional traffic flow detection method, this method detects the traffic vibration signal using a fiber optic cable. Distributed fiber-optic acoustic sensing technology can provide fully distributed acoustic information along the entire fiber link, and thus external acoustic signals from an arbitrary point can be detected and located. This paper uses DAS to obtain traffic vibration data. Using the characteristics of traffic vibration data, this paper proposes an improved wavelet threshold algorithm and an improved dual-threshold algorithm and verifies the feasibility and effectiveness of these methods. Finally, the experimental results from a vehicle-counting test show that the counting error is smaller for a single vehicle passing through the detection area and that the counting error is larger if multiple vehicles pass through the detection area continuously. In vehicle speed estimation, the results show good accuracy, and the error range is controlled to less than 6%. |
| format | Article |
| id | doaj-art-91eba36b8d034df29d8e330b8a9ffba4 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-91eba36b8d034df29d8e330b8a9ffba42025-08-20T03:12:36ZengIEEEIEEE Access2169-35362018-01-016689686898010.1109/ACCESS.2018.28684188453776Traffic Flow Detection Using Distributed Fiber Optic Acoustic SensingHuiyong Liu0Jihui Ma1https://orcid.org/0000-0003-4812-9295Wenfa Yan2Wensheng Liu3Xi Zhang4Congcong Li5MOE Key Laboratory of Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, ChinaMOE Key Laboratory of Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, ChinaMOE Key Laboratory of Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, ChinaNanshan Mine, Magang (Group) Holding Co., Ltd., Ma’anshan, ChinaMOE Key Laboratory of Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, ChinaMOE Key Laboratory of Urban Transportation Complex System Theory and Technology, Beijing Jiaotong University, Beijing, ChinaThis paper proposes a novel method for traffic flow detection using distributed optical fiber acoustic sensing (DAS). Different from the traditional traffic flow detection method, this method detects the traffic vibration signal using a fiber optic cable. Distributed fiber-optic acoustic sensing technology can provide fully distributed acoustic information along the entire fiber link, and thus external acoustic signals from an arbitrary point can be detected and located. This paper uses DAS to obtain traffic vibration data. Using the characteristics of traffic vibration data, this paper proposes an improved wavelet threshold algorithm and an improved dual-threshold algorithm and verifies the feasibility and effectiveness of these methods. Finally, the experimental results from a vehicle-counting test show that the counting error is smaller for a single vehicle passing through the detection area and that the counting error is larger if multiple vehicles pass through the detection area continuously. In vehicle speed estimation, the results show good accuracy, and the error range is controlled to less than 6%.https://ieeexplore.ieee.org/document/8453776/Distributed optical fiber acoustic sensing (DAS)traffic flowvehicle countingvehicle speed estimation |
| spellingShingle | Huiyong Liu Jihui Ma Wenfa Yan Wensheng Liu Xi Zhang Congcong Li Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing IEEE Access Distributed optical fiber acoustic sensing (DAS) traffic flow vehicle counting vehicle speed estimation |
| title | Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing |
| title_full | Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing |
| title_fullStr | Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing |
| title_full_unstemmed | Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing |
| title_short | Traffic Flow Detection Using Distributed Fiber Optic Acoustic Sensing |
| title_sort | traffic flow detection using distributed fiber optic acoustic sensing |
| topic | Distributed optical fiber acoustic sensing (DAS) traffic flow vehicle counting vehicle speed estimation |
| url | https://ieeexplore.ieee.org/document/8453776/ |
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