Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication
The fusion of on-board sensors and transmitted information via inter-vehicle communication has been proved to be an effective way to increase the perception accuracy and extend the perception range of connected intelligent vehicles. The current approaches rely heavily on the accurate self-localizati...
| Autori principali: | , , |
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| Natura: | Articolo |
| Lingua: | English |
| Pubblicazione: |
MDPI AG
2020-06-01
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| Serie: | Sensors |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/1424-8220/20/11/3212 |
| _version_ | 1827715554449817600 |
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| author | Xiaobo Chen Jianyu Ji Yanjun Wang |
| author_facet | Xiaobo Chen Jianyu Ji Yanjun Wang |
| author_sort | Xiaobo Chen |
| collection | DOAJ |
| description | The fusion of on-board sensors and transmitted information via inter-vehicle communication has been proved to be an effective way to increase the perception accuracy and extend the perception range of connected intelligent vehicles. The current approaches rely heavily on the accurate self-localization of both host and cooperative vehicles. However, such information is not always available or accurate enough for effective cooperative sensing. In this paper, we propose a robust cooperative multi-vehicle tracking framework suitable for the situation where the self-localization information is inaccurate. Our framework consists of three stages. First, each vehicle perceives its surrounding environment based on the on-board sensors and exchanges the local tracks through inter-vehicle communication. Then, an algorithm based on Bayes inference is developed to match the tracks from host and cooperative vehicles and simultaneously optimize the relative pose. Finally, the tracks associated with the same target are fused by fast covariance intersection based on information theory. The simulation results based on both synthesized data and a high-quality physics-based platform show that our approach successfully implements cooperative tracking without the assistance of accurate self-localization. |
| first_indexed | 2024-03-10T19:20:36Z |
| format | Article |
| id | doaj.art-2fdf63601a7246c89080d5b535f4dd7f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:20:36Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2fdf63601a7246c89080d5b535f4dd7f2023-11-20T02:58:51ZengMDPI AGSensors1424-82202020-06-012011321210.3390/s20113212Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle CommunicationXiaobo Chen0Jianyu Ji1Yanjun Wang2Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaThe fusion of on-board sensors and transmitted information via inter-vehicle communication has been proved to be an effective way to increase the perception accuracy and extend the perception range of connected intelligent vehicles. The current approaches rely heavily on the accurate self-localization of both host and cooperative vehicles. However, such information is not always available or accurate enough for effective cooperative sensing. In this paper, we propose a robust cooperative multi-vehicle tracking framework suitable for the situation where the self-localization information is inaccurate. Our framework consists of three stages. First, each vehicle perceives its surrounding environment based on the on-board sensors and exchanges the local tracks through inter-vehicle communication. Then, an algorithm based on Bayes inference is developed to match the tracks from host and cooperative vehicles and simultaneously optimize the relative pose. Finally, the tracks associated with the same target are fused by fast covariance intersection based on information theory. The simulation results based on both synthesized data and a high-quality physics-based platform show that our approach successfully implements cooperative tracking without the assistance of accurate self-localization.https://www.mdpi.com/1424-8220/20/11/3212cooperative perceptionmulti-vehicle trackingBayes inferencetrack association |
| spellingShingle | Xiaobo Chen Jianyu Ji Yanjun Wang Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication Sensors cooperative perception multi-vehicle tracking Bayes inference track association |
| title | Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication |
| title_full | Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication |
| title_fullStr | Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication |
| title_full_unstemmed | Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication |
| title_short | Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication |
| title_sort | robust cooperative multi vehicle tracking with inaccurate self localization based on on board sensors and inter vehicle communication |
| topic | cooperative perception multi-vehicle tracking Bayes inference track association |
| url | https://www.mdpi.com/1424-8220/20/11/3212 |
| work_keys_str_mv | AT xiaobochen robustcooperativemultivehicletrackingwithinaccurateselflocalizationbasedononboardsensorsandintervehiclecommunication AT jianyuji robustcooperativemultivehicletrackingwithinaccurateselflocalizationbasedononboardsensorsandintervehiclecommunication AT yanjunwang robustcooperativemultivehicletrackingwithinaccurateselflocalizationbasedononboardsensorsandintervehiclecommunication |