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

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  • Kayvan Aghabayk
  • Majid Sarvi
  • William Young

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.

Suggested Citation

  • Kayvan Aghabayk & Majid Sarvi & William Young, 2015. "A State-of-the-Art Review of Car-Following Models with Particular Considerations of Heavy Vehicles," Transport Reviews, Taylor & Francis Journals, vol. 35(1), pages 82-105, January.
    • Handle: RePEc:taf:transr:v:35:y:2015:i:1:p:82-105
    DOI: 10.1080/01441647.2014.997323
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    Cited by:

    1. Giovanni Pau & Tiziana Campisi & Antonino Canale & Alessandro Severino & Mario Collotta & Giovanni Tesoriere, 2018. "Smart Pedestrian Crossing Management at Traffic Light Junctions through a Fuzzy-Based Approach," Future Internet, MDPI, vol. 10(2), pages 1-19, February.
    2. Shuaiyang Jiao & Shengrui Zhang & Bei Zhou & Zixuan Zhang & Liyuan Xue, 2020. "An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    3. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    4. Xin Tian & Mengmeng Shi & Mengyu Shao & Binghong Pan, 2023. "Calculation Method of Deceleration Lane Length and Slope Based on Reliability Theory," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    5. Wang, Pengcheng & Yu, Guizhen & Wu, Xinkai & Qin, Hongmao & Wang, Yunpeng, 2018. "An extended car-following model to describe connected traffic dynamics under cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 351-370.

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