Citation

Ji W, Yuan Q, Cheng G, Yu S, Wang M, Shen Z, Yang T. J. Traffic Transp. Eng. Engl. Ed. 2023; 10(6): 1061-1073.

Copyright

(Copyright © 2023, Periodical Offices of Chang'an University, Publisher Elsevier Publishing)

DOI

10.1016/j.jtte.2023.09.003

PMID

unavailable

Abstract

As a characteristic representative of the new generation of vehicles, autonomous driving is expected to improve people's driving experience. The study on traffic accident of autonomous vehicles (AVs) helps provide suggestions for autonomous driving safety from multiple disciplines and perspectives, and provide support for formulating traffic accident treatment schemes. Knowledge mapping, as a cutting-edge research method in bibliometrics, scientifically and objectively displays the relevant research status using visual means. This paper uses CiteSpace 6.1.r3 to analyze 5068 related literature on the Web of Science database from 1991 to 2022 and finds out major thematic clusters, important documents and representative journals according to citation frequency. The results show that research on traffic accidents involving AVs focuses on accident preventing technologies, including how to avoid collisions, track lane-position, and enhance vehicle-to-everything (V2X) communication. This paper extracts the mean research topics and key points involved in the field and illustrates journals related to AVs and traffic accidents, which provides guidance for subsequent researchers to carry out in-depth research and contribute their papers. Popular journals are in disciplines of mathematics, systems, computer, economics, and social science. This paper also suggests scholars to consider the aspects of scene reconstruction, cause analysis, and injury of vulnerable road users, so as to investigate traffic accidents and put forward effective treatment schemes to reduce AV accidents, and ultimately improve road safety.

Language: en

Keywords

Autonomous vehicle; Bibliometric; CiteSpace; Knowledge mapping; Traffic accident