Paper Info
Title
Visualization Analysis of Intelligent Vehicles Research Field Based on Mapping Knowledge Domain
Abstract
This study combines applied mathematics, visual analysis technology, information science with an approach of Scientometrics to systematically analyze the development status, research distribution and future trend of intelligent vehicles research. A total number of 3933 published paper index by SCIE and SSCI from 2000 to 2019 are researched based on Mapping Knowledge Domain (MKD) and Scientometrics approaches. Firstly, this paper analyzes the literature content in the field of intelligent vehicles by including the literature number, literature productive countries, research organization, co-authorship of main research groups and the journals from which the articles are mainly sourced. Then, co-citation analysis is used to obtain five major research directions in the field of intelligent vehicles, which include “system framework”, “internet of vehicles”, “intersection control algorithms”, “influence on traffic flow”, and “policies and barriers”, respectively. The keyword co-occurrence analysis is applied to identify four dominant clusters: “planning and control system”, “autonomous vehicle questionnaire”, “sensor and vision”, and “connected vehicles”. Finally, we divide burst keywords into three phases according to the publication date to show more clearly the change of research focus and direction over time.
Year
DOI
Venue
2021
10.1109/TITS.2020.2991642
IEEE Transactions on Intelligent Transportation Systems
Keywords
DocType
Volume
CiteSpace,intelligent vehicles,mapping knowledge domain,visualization analysis,VOSviewer
Journal
22
Issue
ISSN
Citations 
9
1524-9050
1
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Yi He161.17
Shuo Yang210.34
Ching-Yao Chan37923.48
Long Chen4336.34
Chao-zhong Wu58014.18