EconPapers    
Economics at your fingertips  
 

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

Kayvan Aghabayk, Majid Sarvi and William Young

Transport Reviews, 2015, vol. 35, issue 1, 82-105

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.

Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/01441647.2014.997323 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:transr:v:35:y:2015:i:1:p:82-105

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TTRV20

DOI: 10.1080/01441647.2014.997323

Access Statistics for this article

Transport Reviews is currently edited by Professor David Banister and Moshe Givoni

More articles in Transport Reviews from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:transr:v:35:y:2015:i:1:p:82-105