Edge-to-Cloud Intelligent Vehicle-Infrastructure Based on 5G Time-Sensitive Network Integration
Peng Ding, Dan Liu, Shen Yun, Huibin Duan, Qiuhong Zheng · 2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) · 2022
With the rapid evolution of communication technology, 5G has begun to enter the stage of large-scale application. Autonomous driving technology is also developing rapidly. At present, it has entered the stage of L2.x and has begun to move towards commercial trial. At present, the vehicle-road coordination technology based on 5G MEC and C-V2X is an important evolution direction of the Internet of Vehicles. Vehicle-Infrastructure coordination means that vehicles communicate with surrounding vehicles, roadside traffic infrastructure, and cloud services to obtain information on the status of surrounding vehicles, roadside traffic signals, traffic signs, etc., in order to improve the safe driving ability of vehicles. To realize L3 level and above vehicle-infrastructure collaborative autonomous driving, it is necessary to collaborate with multiple data sources of “people-vehicle-road-environment”. And one of the requirements of vehicle-infrastructure coordination is to present auxiliary information from multiple data sources obtained by rapid inference of AI technology to vehicles in a more intuitive and comprehensive way. It is also a low-latency, high-speed mobile service that requires end-to-end ultra-low latency and high reliability of network communications. In response to the requirements of vehicle- infrastructure collaborative autonomous driving, this paper proposes a method for dynamic band-width adjustment and TSN channel division based on 5G+TSN network, and applies the method to the cloud-side collaborative vehicle networking system. The system in this paper also applies AI + digital twin technology to generate 3D rendering video streams that are mostly source fusion to assist driving. Finally, the system is tested based on two application scenarios to verify the feasibility of the system.