A state-of-the-art review of car-following models with particular considerations of heavy vehicles

Kayvan Aghabayk, Majid Sarvi, William Young

Research output: Contribution to journalArticleResearchpeer-review

78 Citations (Scopus)


Abstract: 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.

Original languageEnglish
Pages (from-to)82-105
Number of pages24
JournalTransport Reviews
Issue number1
Publication statusPublished - 2 Jan 2015


  • car-following models
  • driving behaviour
  • heavy vehicles
  • heterogeneous traffic
  • traffic flow modelling

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