Journal of Jilin University(Engineering and Technology Edition) ›› 2026, Vol. 56 ›› Issue (2): 313-332.doi: 10.13229/j.cnki.jdxbgxb.20240853

Previous Articles    

Overview of intersection vehicle-infrastructure integration based on bibliometrics

Yu-sheng CI1(),Yi-kang HUANG2   

  1. 1.School of Transportation Science and Engineering,Harbin Institute of Technology,Harbin 150090,China
    2.School of Architecture,Harbin Institute of Technology (Shenzhen),Shenzhen 518055,China
  • Received:2024-07-29 Online:2026-02-01 Published:2026-03-17

Abstract:

To understand the research status and future research hotspots in the field of vehicle-infrastructure integration at intersections, the Web of Science and CNKI databases were used as data sources to retrieve core journal articles from January 2000 to September 2024, totaling 427 articles. Through bibliometric analysis, statistics and visualization were performed from the perspectives of publication trends, literature sources, and keyword co-word analysis. The statistical results show that the number of publications in this field has been increasing in recent years, and the sample documents are highly representative. Keyword co-occurrence analysis shows that the research directions in this field mainly include intersection control, path and speed guidance, signal-vehicle collaborative optimization, modeling and simulation, multi-vehicle interaction safety, single vehicle safety, vulnerable road user safety, network communication, and roadside perception. The development context and specific methods of the above research directions were sorted out and summarized, and based on this, the future research hotspots in the field of intersection vehicle-infrastructure integration were prospected.

Key words: engineering of communication and transportation system, vehicle-infrastructure integration, bibliometrics, intersection, visual analysis

CLC Number: 

  • U491.1

Fig. 1

Distribution of documents issued in the field of intersection vehicle-infrastructure integration"

Table 1

Top 5 articles published in international journals"

期刊

文章数

/篇

占比

/%

总被引/次平均被引/次
IEEE Transactions on Intelligent Transportation Systems4011.331 79444.85

Transportation Research

Record

349.6343212.71
IEEE Access226.2336916.77

Transportation Research Part

C: Emerging Technologies

185.101 08960.50
Sensors174.8117510.29

Table 2

Top 5 articles published in domestic journals"

期刊文章数/篇

占比

/%

总被引/次平均被引/次
中国公路学报810.8119023.75
交通信息与安全79.4622031.43
交通运输工程学报56.76306.00
交通运输系统工程与信息45.4115238.00
系统仿真学报45.41102.50

Fig.2

Co-occurrence map of all literature keywords"

Fig.3

Summary of overall research direction"

Table 3

Signal control optimization algorithm"

优化算法分类优化算法算法特性

精确

解法

穷举法

分支定界法

能够得到精确解,但是要求模型简单或控制参数取值固定,求解效率难保证

数值

解法

迭代网格搜索法求解效率高,但是要求模型简单,并可能陷入局部最优

启发式

算法

遗传算法

免疫遗传算法

智能树搜索算法

求解效率高,可求解NP难问题,但是可能陷入局部最优,依赖人工参数调优
机器学习算法强化学习方法可求解NP难问题,可输出最优规则,可能陷入局部最优,对数据规模和计算资源要求高,结果可解释性差
模型预测方法模型预测方法可求解NP难问题,可预测系统状况提高控制准确性,但是需要构建系统预测模型

Table 4

Autonomous intersection management system"

AIM

分类

协调方法

系统

核心

系统特性

时空资源预约

虚拟货币交易

通行顺序拍卖

直接统筹规划

控制

中心

控制中心统筹优化能够确保整体最优,但系统高度依赖控制中心,计算负载较高、系统稳定性较弱

通行权协商

车辆互斥竞争

博弈论车辆优先

轨迹无碰撞优化

车辆整体计算效率高,系统灵活且鲁棒性高,但是对通信质量要求高

车辆集群分层式控制

分层模型预测控制

控制

中心、

车辆

将集中式与分布式相结合,兼具两者特性,能较好平衡计算效率、鲁棒性和通信质量要求

Fig.4

Research process of speed guidance"

Table 5

Traffic safety research"

交通安全

分类

被控

对象

研究

内容

研究出发点

多车交

互安全

交叉口、

车辆

交叉口整体安全碰撞预警与避免考虑车与车之间的相互影响,从交叉口系统以及车辆碰撞事故角度优化交通安全

单一车辆

安全

交叉口、

车辆

两难区决策支持闯红灯避免从单一车辆行为出发,辅助驾驶员安全通过交叉口,减少安全隐患

VRU

安全

车辆、

VRU

感知增强的主动安全充分考虑VRU随机性强、易受伤害等特点,保护VRU过街安全

Fig.5

Research process of single vehicle safety"

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