Cooperative Perception Technology of Autonomous Driving in the Internet of Vehicles Environment: A Review

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 15; p. 5535
• Main Authors: Cui, Guangzhen, Zhang, Weili, Xiao, Yanqiu, Yao, Lei, Fang, Zhanpeng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.07.2022; MDPI
• Subjects: Accuracy; Automation; autonomous driving; Autonomous vehicles; Blind spot area; C-V2X; Cameras; Communication; Computer vision; cooperative perception; Data integration; DSRC; Image processing; Information sharing; Internet of Vehicles; IoV; multi-sensor information fusion; Multisensor fusion; Network latency; Perception; Review; Sensors; Traffic congestion; Wireless communications
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22155535

Cooperative perception, as a critical technology of intelligent connected vehicles, aims to use wireless communication technology to interact and fuse environmental information obtained by edge nodes with local perception information, which can improve vehicle perception accuracy, reduce latency, and eliminate perception blind spots. It has become a current research hotspot. Based on the analysis of the related literature on the Internet of vehicles (IoV), this paper summarizes the multi-sensor information fusion method, information sharing strategy, and communication technology of autonomous driving cooperative perception technology in the IoV environment. Firstly, cooperative perception information fusion methods, such as image fusion, point cloud fusion, and image–point cloud fusion, are summarized and compared according to the approaches of sensor information fusion. Secondly, recent research on communication technology and the sharing strategies of cooperative perception technology is summarized and analyzed in detail. Simultaneously, combined with the practical application of V2X, the influence of network communication performance on cooperative perception is analyzed, considering factors such as latency, packet loss rate, and channel congestion, and the existing research methods are discussed. Finally, based on the summary and analysis of the above studies, future research issues on cooperative perception are proposed, and the development trend of cooperative perception technology is forecast to help researchers in this field quickly understand the research status, hotspots, and prospects of cooperative perception technology.