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In recent years, with the improvement of computers, automation, and communication technologies, autonomous driving has developed rapidly and has become a research hotspot in transportation. In order to optimize the existing autonomous driving scheme, this paper investigates the key technologies in 5G-based Telematics autonomous driving, mainly including the millimeter wave communication method and automatic obstacle avoidance strategy design, and tests and analyzes them through simulation experiments. In the simulation experiment, the synchronization rate of rear vehicle 1 of lane <italic>X</italic>1 is 97.56%, that of rear vehicle <italic>X</italic>2 is 98.43%, and that of rear vehicle <italic>X</italic>3 is 97.82%, with an average synchronization rate of 97.94%. The synchronization rates of rear vehicle <italic>Y</italic>1, <italic>Y</italic>2 and <italic>Y</italic>3 of lane 2 are 98.27%, 97.84%, and 96.89%, respectively, with an average synchronization rate of 97.67%. For the local observation latency in Telematics, the 5G Big Data-based scheme reduces 10.22% on average compared to the F-DDQL scheme and 9.76% on average compared to the IF-DDQL scheme. Regarding system latency, the 5G Big Data-based scheme reduces 8.67% and 9.21% on average compared to the other two schemes, respectively. The 5G Big Data-based Telematics autopilot can significantly improve the synchronization rate of vehicles and effectively reduce network latency. The research on the key technologies of 5G big data-based connected vehicle autonomous driving in this paper can overcome the shortcomings of traditional autonomous driving technology with unstable networking and help reduce the reliance on high-precision sensors, thus further improving autonomous driving performance.
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In recent years, with the improvement of computers, automation, and communication technologies, autonomous driving has developed rapidly and has become a research hotspot in transportation. In order to optimize the existing autonomous driving scheme, this paper investigates the key technologies in 5G-based Telematics autonomous driving, mainly including the millimeter wave communication method and automatic obstacle avoidance strategy design, and tests and analyzes them through simulation experiments. In the simulation experiment, the synchronization rate of rear vehicle 1 of lane X1 is 97.56%, that of rear vehicle X2 is 98.43%, and that of rear vehicle X3 is 97.82%, with an average synchronization rate of 97.94%. The synchronization rates of rear vehicle Y1, Y2 and Y3 of lane 2 are 98.27%, 97.84%, and 96.89%, respectively, with an average synchronization rate of 97.67%. For the local observation latency in Telematics, the 5G Big Data-based scheme reduces 10.22% on average compared to the F-DDQL scheme and 9.76% on average compared to the IF-DDQL scheme. Regarding system latency, the 5G Big Data-based scheme reduces 8.67% and 9.21% on average compared to the other two schemes, respectively. The 5G Big Data-based Telematics autopilot can significantly improve the synchronization rate of vehicles and effectively reduce network latency. The research on the key technologies of 5G big data-based connected vehicle autonomous driving in this paper can overcome the shortcomings of traditional autonomous driving technology with unstable networking and help reduce the reliance on high-precision sensors, thus further improving autonomous driving performance.

Research on key technologies for connected vehicle autonomous driving based on 5G big data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In recent years, with the improvement of computers, automation, and communication technologies, autonomous driving has developed rapidly and has become a...

Research on key technologies for connected vehicle autonomous driving based on 5G big data

Pubblicato online: 05 giu 2023

Pagine: -

Ricevuto: 06 lug 2022

Accettato: 09 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00349

Parole chiave
5G network, Big data, Connected vehicle, Autonomous driving, Obstacle avoidance strategy

© 2023 Jiyan Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on key technologies for connected vehicle autonomous driving based on 5G big data

Pubblicato online: 05 giu 2023

Pagine: -

Ricevuto: 06 lug 2022

Accettato: 09 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00349

Parole chiave5G network, Big data, Connected vehicle, Autonomous driving, Obstacle avoidance strategy

© 2023 Jiyan Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
5G network, Big data, Connected vehicle, Autonomous driving, Obstacle avoidance strategy