Toggle Main Menu Toggle Search

Open Access padlockePrints

Exploration into the Needs and Requirements of the Remote Driver When Teleoperating the 5G‐Enabled Level 4 Automated Vehicle in the Real World—A Case Study of 5G Connected and Automated Logistics

Lookup NU author(s): Dr Shuo LiORCiD, Dr Yanghanzi ZhangORCiD, Simon Edwards, Professor Phil BlytheORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Connected and automated vehicles have the potential to deliver significant environmental, safety, economic and social benefits. The key advancement for automated vehicles with higher levels of automation (SAE Level 4 and over) is fail-operational. One possible solution for the failsafe mode of automated vehicles is a 5G-enabled teleoperation system controlled by remote drivers. However, knowledge is missing regarding understanding of the human–machine interaction in teleoperation from the perspective of remote drivers. To address this research gap, this study qualitatively investigated the acceptance, attitudes, needs and requirements of remote drivers when teleoperating a 5G-enabled Level 4 automated vehicle (5G L4 AV) in the real world. The results showed that remote drivers are positive towards the 5G L4 AV. They would like to constantly monitor the driving when they are not controlling the vehicle remotely. Improving their field of vision for driving and enhancing the perception of physical motion feedback are the two key supports required by remote drivers in 5G L4 AVs. The knowledge gained in this study provides new insights into facilitating the design and development of safe, effective and user-friendly teleoperation systems in vehicle automation.

Publication metadata

Author(s): Li S, Zhang Y, Edwards S, Blythe P

Publication type: Article

Publication status: Published

Journal: Sensors

Year: 2023

Volume: 23

Issue: 2

Print publication date: 10/01/2023

Online publication date: 10/01/2023

Acceptance date: 07/01/2023

Date deposited: 10/01/2023

ISSN (electronic): 1424-8220

Publisher: MDPI AG


DOI: 10.3390/s23020820


Altmetrics provided by Altmetric


Funder referenceFunder name