Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability
Taxis play a critical role in public traffic systems, and they deliver myriad travelers with convenient service due to temporal-spatial availability. However, anomalous trajectories such as trip fraud often occur due to greedy drivers. In this study, we propose an anomalous trajectory detection meth...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/7223646 |
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| _version_ | 1832565373134700544 |
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| author | Pengqian Cao Renxin Zhong Wei Huang |
| author_facet | Pengqian Cao Renxin Zhong Wei Huang |
| author_sort | Pengqian Cao |
| collection | DOAJ |
| description | Taxis play a critical role in public traffic systems, and they deliver myriad travelers with convenient service due to temporal-spatial availability. However, anomalous trajectories such as trip fraud often occur due to greedy drivers. In this study, we propose an anomalous trajectory detection method that incorporates Route Choice analysis into Masked Autoregressive Flow, named MAFRC-ATD. The MAFRC-ATD integrates data-driven and model-based methods. First, we divide the urban traffic network into small grids and represent subtrajectories with a sequence of grids. Second, based on the subtrajectories, we employ the MAFRC-ATD model to calculate the anomaly score of each trajectory. Third, according to the anomaly score, we can identify the anomalous trajectories and distinguish between intentionally and unintentionally anomalous. Finally, we evaluate our method with a real-world dataset in Porto, Portugal. The experiment demonstrates that the MAFRC-ATD can effectively discover anomalous trajectories and can identify the unintentional detours due to traffic congestion. |
| format | Article |
| id | doaj-art-3b76435634f242ef855d4c0094f50000 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-3b76435634f242ef855d4c0094f500002025-02-03T01:07:56ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/7223646Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice ProbabilityPengqian Cao0Renxin Zhong1Wei Huang2School of Intelligent Systems EngineeringSchool of Intelligent Systems EngineeringSchool of Intelligent Systems EngineeringTaxis play a critical role in public traffic systems, and they deliver myriad travelers with convenient service due to temporal-spatial availability. However, anomalous trajectories such as trip fraud often occur due to greedy drivers. In this study, we propose an anomalous trajectory detection method that incorporates Route Choice analysis into Masked Autoregressive Flow, named MAFRC-ATD. The MAFRC-ATD integrates data-driven and model-based methods. First, we divide the urban traffic network into small grids and represent subtrajectories with a sequence of grids. Second, based on the subtrajectories, we employ the MAFRC-ATD model to calculate the anomaly score of each trajectory. Third, according to the anomaly score, we can identify the anomalous trajectories and distinguish between intentionally and unintentionally anomalous. Finally, we evaluate our method with a real-world dataset in Porto, Portugal. The experiment demonstrates that the MAFRC-ATD can effectively discover anomalous trajectories and can identify the unintentional detours due to traffic congestion.http://dx.doi.org/10.1155/2022/7223646 |
| spellingShingle | Pengqian Cao Renxin Zhong Wei Huang Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability Journal of Advanced Transportation |
| title | Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability |
| title_full | Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability |
| title_fullStr | Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability |
| title_full_unstemmed | Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability |
| title_short | Anomalous Trajectory Detection Using Masked Autoregressive Flow Considering Route Choice Probability |
| title_sort | anomalous trajectory detection using masked autoregressive flow considering route choice probability |
| url | http://dx.doi.org/10.1155/2022/7223646 |
| work_keys_str_mv | AT pengqiancao anomaloustrajectorydetectionusingmaskedautoregressiveflowconsideringroutechoiceprobability AT renxinzhong anomaloustrajectorydetectionusingmaskedautoregressiveflowconsideringroutechoiceprobability AT weihuang anomaloustrajectorydetectionusingmaskedautoregressiveflowconsideringroutechoiceprobability |