Multi-sensor fusion algorithm in cooperative vehicle-infrastructure system for blind spot warning
With the rapid development of electric vehicles and artificial intelligence technology, the automatic driving industry has entered a rapid development stage. However, there is a risk of traffic accidents due to the blind spot of vision, whether autonomous vehicles or traditional vehicles. In this ar...
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| Veröffentlicht in: | International journal of distributed sensor networks Jg. 18; H. 5; S. 155013292211004 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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London, England
SAGE Publications
01.05.2022
Wiley |
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| ISSN: | 1550-1329, 1550-1477 |
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| Abstract | With the rapid development of electric vehicles and artificial intelligence technology, the automatic driving industry has entered a rapid development stage. However, there is a risk of traffic accidents due to the blind spot of vision, whether autonomous vehicles or traditional vehicles. In this article, a multi-sensor fusion perception method is proposed, in which the semantic information from the camera and the range information from the LiDAR are fused at the data layer and the LiDAR point cloud containing semantic information is clustered to obtain the type and location information of the objects. Based on the sensor equipments deployed on the roadside, the sensing information processed by the fusion method is sent to the nearby vehicles in real-time through 5G and V2X technology for blind spot early warning, and its feasibility is verified by experiments and simulations. The blind spot warning scheme based on roadside multi-sensor fusion perception proposed in this article has been experimentally verified in the closed park, which can obviously reduce the traffic accidents caused by the blind spot of vision, and is of great significance to improve traffic safety. |
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| AbstractList | With the rapid development of electric vehicles and artificial intelligence technology, the automatic driving industry has entered a rapid development stage. However, there is a risk of traffic accidents due to the blind spot of vision, whether autonomous vehicles or traditional vehicles. In this article, a multi-sensor fusion perception method is proposed, in which the semantic information from the camera and the range information from the LiDAR are fused at the data layer and the LiDAR point cloud containing semantic information is clustered to obtain the type and location information of the objects. Based on the sensor equipments deployed on the roadside, the sensing information processed by the fusion method is sent to the nearby vehicles in real-time through 5G and V2X technology for blind spot early warning, and its feasibility is verified by experiments and simulations. The blind spot warning scheme based on roadside multi-sensor fusion perception proposed in this article has been experimentally verified in the closed park, which can obviously reduce the traffic accidents caused by the blind spot of vision, and is of great significance to improve traffic safety. |
| Author | Xie, Xiaopo Xiang, Chao Zhang, Li Ke, Xin Zhao, Longgang Niu, Zhendong Wang, Feng |
| Author_xml | – sequence: 1 givenname: Chao orcidid: 0000-0001-6649-681X surname: Xiang fullname: Xiang, Chao – sequence: 2 givenname: Li surname: Zhang fullname: Zhang, Li – sequence: 3 givenname: Xiaopo surname: Xie fullname: Xie, Xiaopo – sequence: 4 givenname: Longgang surname: Zhao fullname: Zhao, Longgang – sequence: 5 givenname: Xin surname: Ke fullname: Ke, Xin – sequence: 6 givenname: Zhendong surname: Niu fullname: Niu, Zhendong – sequence: 7 givenname: Feng surname: Wang fullname: Wang, Feng email: wangfeng6@chinatelecom.cn |
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| Cites_doi | 10.3390/s18103337 10.1145/3161587.3161593 10.1016/j.trc.2016.03.008 10.1007/978-981-15-1275-9_44 10.1007/978-3-319-46448-0_2 |
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| Keywords | 5G Multi-sensor fusion blind spot warning RSU V2X |
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| References_xml | – volume: 28 start-page: 91 year: 2015 end-page: 99 article-title: Faster R-CNN: towards real-time object detection with region proposal networks publication-title: Adv Neur Inform Process Syst – volume: 21 start-page: 19 issue: 3 year: 2017 end-page: 25 article-title: An overview of 3GPP cellular vehicle-to-everything standards publication-title: Getmobile: Mobile Comput Commun – volume: 18 start-page: 3337 issue: 10 year: 2018 article-title: SECOND: sparsely embedded convolutional detection publication-title: Sensors – volume: 68 start-page: 168 year: 2016 end-page: 184 article-title: Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network: performance evaluation publication-title: Transp Res Part C: Emerg Technol – ident: bibr18-15501329221100412 – start-page: 10529 volume-title: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition ident: bibr23-15501329221100412 – ident: bibr22-15501329221100412 doi: 10.3390/s18103337 – start-page: 779 volume-title: Proceedings of the IEEE conference on computer vision and pattern recognition ident: bibr13-15501329221100412 – start-page: 4604 volume-title: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition ident: bibr25-15501329221100412 – start-page: 580 volume-title: Proceedings of the IEEE conference on computer vision and pattern recognition ident: bibr9-15501329221100412 – start-page: 2980 volume-title: Proceedings of the IEEE international conference on computer vision ident: bibr15-15501329221100412 – ident: bibr16-15501329221100412 – start-page: 11040 volume-title: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition ident: bibr20-15501329221100412 – ident: bibr4-15501329221100412 doi: 10.1145/3161587.3161593 – ident: bibr5-15501329221100412 – volume: 28 start-page: 91 year: 2015 ident: bibr12-15501329221100412 publication-title: Adv Neur Inform Process Syst – ident: bibr1-15501329221100412 – volume-title: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition (CVPR 2001) ident: bibr6-15501329221100412 – ident: bibr2-15501329221100412 doi: 10.1016/j.trc.2016.03.008 – start-page: 1440 volume-title: Proceedings of the IEEE international conference on computer vision ident: bibr11-15501329221100412 – ident: bibr3-15501329221100412 doi: 10.1007/978-981-15-1275-9_44 – start-page: 7345 volume-title: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition ident: bibr24-15501329221100412 – start-page: 652 volume-title: Proceedings of the IEEE conference on computer vision and pattern recognition ident: bibr17-15501329221100412 – start-page: 886 volume-title: Proceedings of the 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR 2005) ident: bibr7-15501329221100412 – ident: bibr10-15501329221100412 – start-page: 1 volume-title: Proceedings of the 2008 IEEE conference on computer vision and pattern recognition ident: bibr8-15501329221100412 – start-page: 4490 volume-title: Proceedings of the IEEE conference on computer vision and pattern recognition ident: bibr21-15501329221100412 – ident: bibr14-15501329221100412 doi: 10.1007/978-3-319-46448-0_2 – start-page: 770 volume-title: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition ident: bibr19-15501329221100412 |
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