Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors
Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs),...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/5/1860 |
| _version_ | 1797412626677891072 |
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| author | Minjin Baek Jungwi Mun Woojoong Kim Dongho Choi Janghyuk Yim Sangsun Lee |
| author_facet | Minjin Baek Jungwi Mun Woojoong Kim Dongho Choi Janghyuk Yim Sangsun Lee |
| author_sort | Minjin Baek |
| collection | DOAJ |
| description | Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs), which are capable of sharing information with each other and also with the surrounding infrastructure. In this paper, we present the design and implementation of driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors. A track-to-track fusion of high-level sensor data and vehicular wireless communication data was performed to accurately and reliably locate the remote target in the vehicle surroundings and predict the future trajectory. The proposed approach was implemented and evaluated in vehicle tests conducted at a proving ground. The experimental results demonstrate that using vehicular wireless communications in conjunction with the on-board sensors enables improved perception of the surrounding vehicle located at varying longitudinal and lateral distances. The results also indicate that vehicle future trajectory and potential crash involvement can be reliably predicted with the proposed system in different cut-in driving scenarios. |
| first_indexed | 2024-03-09T05:05:52Z |
| format | Article |
| id | doaj.art-42b1c68e1a824585a1479e47e0a51083 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T05:05:52Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-42b1c68e1a824585a1479e47e0a510832023-12-03T12:55:00ZengMDPI AGSensors1424-82202021-03-01215186010.3390/s21051860Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote SensorsMinjin Baek0Jungwi Mun1Woojoong Kim2Dongho Choi3Janghyuk Yim4Sangsun Lee5Department of Electronics and Computer Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Automotive Electronics and Control Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Electronics and Computer Engineering, Hanyang University, Seoul 04763, KoreaDriving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs), which are capable of sharing information with each other and also with the surrounding infrastructure. In this paper, we present the design and implementation of driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors. A track-to-track fusion of high-level sensor data and vehicular wireless communication data was performed to accurately and reliably locate the remote target in the vehicle surroundings and predict the future trajectory. The proposed approach was implemented and evaluated in vehicle tests conducted at a proving ground. The experimental results demonstrate that using vehicular wireless communications in conjunction with the on-board sensors enables improved perception of the surrounding vehicle located at varying longitudinal and lateral distances. The results also indicate that vehicle future trajectory and potential crash involvement can be reliably predicted with the proposed system in different cut-in driving scenarios.https://www.mdpi.com/1424-8220/21/5/1860connected and automated vehiclecooperative perceptionV2X communicationssensor fusionadvanced driver assistance systemtrajectory prediction |
| spellingShingle | Minjin Baek Jungwi Mun Woojoong Kim Dongho Choi Janghyuk Yim Sangsun Lee Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors Sensors connected and automated vehicle cooperative perception V2X communications sensor fusion advanced driver assistance system trajectory prediction |
| title | Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors |
| title_full | Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors |
| title_fullStr | Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors |
| title_full_unstemmed | Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors |
| title_short | Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors |
| title_sort | driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors |
| topic | connected and automated vehicle cooperative perception V2X communications sensor fusion advanced driver assistance system trajectory prediction |
| url | https://www.mdpi.com/1424-8220/21/5/1860 |
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