A State-of-the-Art Review of Car-Following Models with Particular Considerations of Heavy Vehicles

被引:75
作者
Aghabayk, Kayvan [1 ]
Sarvi, Majid [1 ]
Young, William [1 ]
机构
[1] Monash Univ, Inst Transport Studies, Dept Civil Engn, Clayton, Vic 3800, Australia
关键词
traffic flow modelling; heterogeneous traffic; car-following models; driving behaviour; heavy vehicles; DYNAMICS; BEHAVIOR; DRIVER; TIME; SIMULATION;
D O I
10.1080/01441647.2014.997323
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Car-following (CF) models are fundamental in the replication of traffic flow and thus they have received considerable attention. This attention needs to be reflected upon at particular points in time. CF models are in a continuous state of improvement due to their significant role in traffic micro-simulations, intelligent transportation systems and safety engineering models. This paper presents a review of existing CF models. It classifies them into classic and artificial intelligence models. It discusses the capability of the models and potential limitations that need to be considered in their improvement. This paper also reviews the studies investigating the impacts of heavy vehicles in traffic stream and on CF behaviour. The findings of the study provide promising directions for future research and suggest revisiting the existing models to accommodate different behaviours of drivers in heterogeneous traffic, in particular, heavy vehicles in traffic.
引用
收藏
页码:82 / 105
页数:24
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