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Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

Author

Listed:
  • Zhi Ma

    (School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Songlin Sun

    (School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China)

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.

Suggested Citation

  • Zhi Ma & Songlin Sun, 2021. "Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video," Sustainability, MDPI, vol. 13(10), pages 1-15, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5334-:d:551886
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    Cited by:

    1. Jing Cao & Haichao Ling & Tao Li & Shiyu Wang & Shengchuan Jiang & Cong Zhao, 2024. "A Graph-Based Scheme Generation Method for Variable Traffic Organization in Parking Lots," Sustainability, MDPI, vol. 16(11), pages 1-18, June.

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