Abstract
The development of 5G network slicing technology, combined with the application scenarios of vehicle–road collaborative positioning, provides end-to-end, large-bandwidth, low-latency, and highly reliable flexible customized services for Internet of Vehicle (IoV) services in different business scenarios. Starting from the needs of the network in the business scenario oriented to co-location, we researched the application of 5G network slicing technology in the vehicle–road cooperative localization system. We considered scheduling 5G slice resources. Creating slices to ensure the safety of the system, provided an optimized solution for the application of the vehicle–road coordinated positioning system. On this basis, this paper proposes a vehicle–road coordinated combined positioning method based on Beidou. On the basis of Beidou positioning and track estimation, using the advantages of the volumetric Kalman model, a combined positioning algorithm based on CKF was established. In order to further improve the positioning accuracy, vehicle characteristics could be extracted based on the traffic monitoring video stream to optimize the service-oriented positioning system. Considering that the vehicles in the urban traffic system can theoretically only travel on the road, the plan can be further optimized based on the road network information. It was preliminarily verified by simulation that this research idea has improved the relative single positioning method.
Highlights
Intelligent transportation plays a vital role in smart cities, and it provides solutions to many problems related to road traffic
The business scenarios of the Internet of Vehicles based on vehicle–road collaboration are very rich, and they have different requirements for network performance
This article will first start with the needs of the network in the business scenario oriented to vehicle–road collaborative positioning, and conduct research on the application of 5G network slicing technology in the vehicle–road collaborative system
Summary
In order to better solve urban traffic problems, the development of intelligent transportation systems is a general trend. Intelligent transportation plays a vital role in smart cities, and it provides solutions to many problems related to road traffic It affects safety and quality of life, which is the main goal of smart city development [1]. Among the many key digital technologies for intelligent traffic video, precise positioning and tracking of vehicles is one of the main research directions. The result of vehicle positioning and tracking is the basis for calculating traffic flow and speed, so as to obtain road conditions It is an important basis for judging abnormal events, such as retrograde movement, speeding, and vehicle collisions. Sustainability 2021, 13, 5334 particular, the real-time position, speed and direction of the vehicle are the most important data for vehicle collision avoidance and navigation safety applications. Low-cost, dynamic, and reliable positioning is a condition that this type of application must meet, as well as all-weather low-cost and high-precision requirements [2]
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