The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm
As one of the largest Internet of Things systems in the world, China’s expressway electronic toll collection (ETC) generates nearly one billion pieces of transaction data every day, recording the traffic trajectories of almost all vehicles on the expressway, which has great potential application val...
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| Format: | Article |
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MDPI AG
2022-06-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/13/1981 |
| _version_ | 1797480423620608000 |
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| author | Feng Guo Fumin Zou Sijie Luo Lyuchao Liao Jinshan Wu Xiang Yu Cheng Zhang |
| author_facet | Feng Guo Fumin Zou Sijie Luo Lyuchao Liao Jinshan Wu Xiang Yu Cheng Zhang |
| author_sort | Feng Guo |
| collection | DOAJ |
| description | As one of the largest Internet of Things systems in the world, China’s expressway electronic toll collection (ETC) generates nearly one billion pieces of transaction data every day, recording the traffic trajectories of almost all vehicles on the expressway, which has great potential application value. However, there are inevitable missed transactions and false transactions in the expressway ETC system, which leads to certain false and missing rates in ETC data. In this work, a dynamic search step SegrDTW algorithm based on an improved DTW algorithm is proposed according to the characteristics of expressway ETC data with origin–destination (OD) data constraints and coupling between the gantry path and the vehicle trajectory. Through constructing the spatial window of segment retrieval, the spatial complexity of the DTW algorithm is effectively reduced, and the efficiency of the abnormal ETC data detection is greatly improved. In real traffic data experiments, the SegrDTW algorithm only needs 3.36 s to measure the abnormal events of a single set of OD path data for 10 days. Compared with the mainstream algorithms, the SegrDTW performs best. Therefore, the proposal provides a feasible method for the abnormal event detection of expressway ETC data in a province and even the whole country. |
| first_indexed | 2024-03-09T22:00:50Z |
| format | Article |
| id | doaj.art-a464fa27d8104775872d6608286e221d |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T22:00:50Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-a464fa27d8104775872d6608286e221d2023-11-23T19:50:56ZengMDPI AGElectronics2079-92922022-06-011113198110.3390/electronics11131981The Fast Detection of Abnormal ETC Data Based on an Improved DTW AlgorithmFeng Guo0Fumin Zou1Sijie Luo2Lyuchao Liao3Jinshan Wu4Xiang Yu5Cheng Zhang6College of Computer and Data Science, Fuzhou University, Fuzhou 350108, ChinaCollege of Computer and Data Science, Fuzhou University, Fuzhou 350108, ChinaFujian Key Laboratory for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350118, ChinaFujian Key Laboratory for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350118, ChinaFujian Key Laboratory for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350118, ChinaFujian Key Laboratory for Automotive Electronics and Electric Drive, Fujian University of Technology, Fuzhou 350118, ChinaCollege of Information Technology and Management, Hunan University of Finance and Economics, Changsha 410205, ChinaAs one of the largest Internet of Things systems in the world, China’s expressway electronic toll collection (ETC) generates nearly one billion pieces of transaction data every day, recording the traffic trajectories of almost all vehicles on the expressway, which has great potential application value. However, there are inevitable missed transactions and false transactions in the expressway ETC system, which leads to certain false and missing rates in ETC data. In this work, a dynamic search step SegrDTW algorithm based on an improved DTW algorithm is proposed according to the characteristics of expressway ETC data with origin–destination (OD) data constraints and coupling between the gantry path and the vehicle trajectory. Through constructing the spatial window of segment retrieval, the spatial complexity of the DTW algorithm is effectively reduced, and the efficiency of the abnormal ETC data detection is greatly improved. In real traffic data experiments, the SegrDTW algorithm only needs 3.36 s to measure the abnormal events of a single set of OD path data for 10 days. Compared with the mainstream algorithms, the SegrDTW performs best. Therefore, the proposal provides a feasible method for the abnormal event detection of expressway ETC data in a province and even the whole country.https://www.mdpi.com/2079-9292/11/13/1981data governanceelectronic toll collection datatrajectory similaritydynamic time warpinganomaly detectionexpressway |
| spellingShingle | Feng Guo Fumin Zou Sijie Luo Lyuchao Liao Jinshan Wu Xiang Yu Cheng Zhang The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm Electronics data governance electronic toll collection data trajectory similarity dynamic time warping anomaly detection expressway |
| title | The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm |
| title_full | The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm |
| title_fullStr | The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm |
| title_full_unstemmed | The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm |
| title_short | The Fast Detection of Abnormal ETC Data Based on an Improved DTW Algorithm |
| title_sort | fast detection of abnormal etc data based on an improved dtw algorithm |
| topic | data governance electronic toll collection data trajectory similarity dynamic time warping anomaly detection expressway |
| url | https://www.mdpi.com/2079-9292/11/13/1981 |
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