Abstract: On the basis of organizing and analyzing previous literature on traffic language, the concepts of generalized traffic language and narrowed traffic language were put forward. Based on 1083 literatures published from 2012 to 2022, CiteSpace was used to conduct a visual analysis of the research on traffic language in China in the past ten years, including institutional cooperation network analysis, keyword co-occurrence network analysis, keyword clustering analysis and highlight word analysis. The research shows that in the past decade, the annual publication volume of traffic language literature in China has shown a slow growth trend. The research direction has gradually transitioned from the early concept of “intelligent transportation” to the intersection of computer science and other disciplines for in-depth research. The hotspots of traffic language research are concentrated in areas such as traffic sign detection and recognition and intelligent traffic signal systems. Finally, the future research trend is predicted through highlighting of key words.

Key words: transport engineering; traffic language; CiteSpace; knowledge atlas; visualization

摘要： 在整理分析前人对交通语言文献研究的基础上，提出广义交通语言与狭义交通语言的概念。以2012年到2022年发表的1 083篇文献为分析对象，通过CiteSpace以可视化的方式对我国近十年来的交通语言研究进行了机构合作网络分析、关键词共现网络分析、关键词聚类分析和突显词分析。研究表明，近十年来，我国的交通语言文献年发文量呈缓慢增长的趋势，研究方向从早期“智能交通”概念的提出逐渐过渡到与计算机等学科交叉从而进行深入研究，交通语言研究的热点集中于交通标志检测与识别和智能交通信号灯系统等领域。最后通过关键词的突显情况对未来研究走向做出预测。

关键词: 交通工程；交通语言；CiteSpace；知识图谱；可视化