Dynamic Traffic Flow Based on Bibliometrics

doi:10.3969/j.issn.1674-0696.2020.08.05

Abstract

Abstract: Research on dynamic traffic flow is related to the development of intelligent transportation. In order to more systematically understand the status of dynamic traffic flow research in China, the relevant technology of bibliometrics and the literature analysis visualization software CiteSpace were used to analyze 146 core source journals, EI source journals and SCI source journals about dynamic traffic flow research collected by CNKI from 1990 to October 2018, respectively from the general trend of journal publication, journal source distribution, research institutions distribution, fund distribution and keyword co-occurrence network. The study finds that the research related to dynamic traffic flow has been increasing year by year since the 1990s, and has stabilized in recent years. The sources of journals are widely distributed, but the distribution is uneven. The research institutions are single, almost all of them are well-known universities in China, lacking other types of research units. There are many fund projects, but the coverage is not wide, most of them are national-level fund projects. The research models and application fields of dynamic traffic flow are mainly based on cell transmission model and intersection signal control. Generally speaking, the research on dynamic traffic flow in China has not formed a core research institution, and the research depth is not deep enough. Finally, it is suggested that researchers should study the deep learning algorithm more deeply and study the problems related to dynamic traffic flow from the aspect of intelligent model algorithm, so as to form a core research group and lay a solid foundation for ITS.

Key words: traffic engineering, bibliometrics, dynamic traffic flow, keyword co-occurrence network, intelligent transportation

摘要： 动态交通流的相关研究关系到智能交通的发展。为了更系统地了解我国有关动态交通流研究的状况，运用文献计量法的相关技术以及文献分析可视化软件CiteSpace，对中国知网从1990年到2018年10月份收录的146篇有关动态交通流研究的核心来源期刊、EI来源期刊以及SCI来源期刊，分别从期刊发表总趋势、期刊来源分布、研究机构分布、基金分布以及关键词共现网络来进行分析。研究发现，与动态交通流有关的研究从20世纪90年代开始总体上呈逐年上升趋势，近年来趋于稳定；期刊的来源分布较广，但分布不均匀；研究机构单一，几乎都是国内知名高校，缺少其他类型研究单位；基金项目多，但覆盖面不广，大多数都为国家级的基金项目；动态交通流的研究模型和应用领域分别以元胞传输模型和交叉口信号控制为主。总体来说，我国动态交通流的研究还没有形成一个核心的研究机构且研究深度还不够深。最后，建议研究者们更深入地研究深度学习算法，从智能模型算法方面来研究与动态交通流相关的问题，形成有核心的研究群体，为智能交通打下坚实的基础。

关键词: 交通工程, 文献计量法, 动态交通流, 关键词共现网络, 智能交通

CLC Number:

U491.1+12

LIU Wei, LIU Chuan. Dynamic Traffic Flow Based on Bibliometrics[J]. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(08): 29-35.

刘伟，刘川. 基于文献计量的动态交通流研究[J]. 重庆交通大学学报（自然科学版）, 2020, 39(08): 29-35.

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