Mechanical and Electrical Engineering Institute, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
Henan Province International Joint Laboratory for Intelligent Monitoring and Control of Complex Machinery and Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
Sensors (Basel). 2022 Jul 25;22(15):5535. 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.
协同感知作为智能网联汽车的关键技术,旨在利用无线通信技术交互和融合边缘节点获取的环境信息与本地感知信息,可提高车辆感知精度、降低时延、消除感知盲区,已成为当前研究热点。本文通过对车联网相关文献进行分析,总结了车联网环境下自动驾驶协同感知技术中的多传感器信息融合方法、信息共享策略和通信技术。首先,根据传感器信息融合的方式,对协同感知信息融合方法(如图像融合、点云融合、图像-点云融合)进行了总结和对比。其次,详细地对通信技术和协同感知技术的共享策略的最新研究进行了总结和分析。同时,结合 V2X 的实际应用,分析了网络通信性能对协同感知的影响,考虑了时延、丢包率和信道拥塞等因素,并对现有的研究方法进行了讨论。最后,在对上述研究进行总结和分析的基础上,提出了协同感知技术未来的研究问题,并对协同感知技术的发展趋势进行了预测,有助于该领域的研究人员快速了解协同感知技术的研究现状、热点和前景。