Systematic Review on Classical Car-Following Models

被引:1
作者
Yin, Jiacheng [1 ,2 ]
Li, Zongping [1 ,2 ]
Cao, Peng [2 ]
机构
[1] Southwest Jiaotong Univ, Natl United Engn Lab Integrated & Intelligent Tra, Sch Transportat & Logist, Chengdu, Peoples R China
[2] Southwest Jiaotong Univ, Yibin Res Inst, Yibin, Peoples R China
来源
2022 IEEE 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING, ICITE | 2022年
基金
中国国家自然科学基金;
关键词
review; traffic engineering; car-following models; PRISMA; CELLULAR-AUTOMATON MODEL; TRAFFIC OSCILLATIONS; DYNAMICAL MODEL; CAPACITY; STATES; WAVES; FLOW;
D O I
10.1109/ICITE56321.2022.10101483
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To further clarify the ideas and methods of the classical car-following model, this paper systematically combs the modeling methods of the classical car-following model. The PRISMA ( Preferred Reporting Items for Systematic Reviews and Meta-analysis) is applied to To improve the quality of literature review. The "car-following model" was used as a keyword to search literature related to GHR, OVM, IDM, SDM, NEWELL and CA models from 11 electronic databases. By constructing the literature quality evaluation index system, 40 papers meeting the requirements were selected. The modeling ideas, model structure, advantages and disadvantages, application scope and expansion of six classical models were summarized. Finally, the development trend and research direction of car-following model are envisioned, providing a reference for further improvement of model construction.
引用
收藏
页码:40 / 45
页数:6
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