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Control Concepts for Facilitating Motorway On-ramp Merging Using Intelligent Vehicles

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  • Riccardo Scarinci
  • Benjamin Heydecker

Abstract

Congestion at motorway junctions is a traffic phenomenon that degrades operation of infrastructure and can lead to breakdown of traffic flow and associated reduction in capacity. Advanced communication technologies open new possibilities to prevent or at least delay this phenomenon, and innovative active traffic management systems have been developed in the recent years for better control of motorway traffic. This paper presents a review of control strategies for facilitating motorway on-ramp merging using intelligent vehicles. First, the concepts of the control algorithms are reviewed chronologically divided into three types of intelligent vehicle: completely automated, equipped with cooperative adaptive cruise control and equipped with on-board display. Then, a common structure is identified, and the algorithms are presented based on their characteristics in order to identify similarities, dissimilarities, trends and possible future research directions. Finally, using a similar approach, a review of the methods used to evaluate these control strategies identifies important aspects that should be considered by further research on this topic.

Suggested Citation

  • Riccardo Scarinci & Benjamin Heydecker, 2014. "Control Concepts for Facilitating Motorway On-ramp Merging Using Intelligent Vehicles," Transport Reviews, Taylor & Francis Journals, vol. 34(6), pages 775-797, November.
    • Handle: RePEc:taf:transr:v:34:y:2014:i:6:p:775-797
    DOI: 10.1080/01441647.2014.983210
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    Cited by:

    1. Zhang, Hanyu & Du, Lili & Shen, Jinglai, 2022. "Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 104-142.
    2. Davis, L.C., 2016. "Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 320-332.
    3. Davis, L.C., 2020. "Optimal merging into a high-speed lane dedicated to connected autonomous vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    4. Zhouqiao Zhao & Guoyuan Wu & Matthew Barth, 2021. "Corridor-Wise Eco-Friendly Cooperative Ramp Management System for Connected and Automated Vehicles," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    5. Li, Jie & Fotouhi, Abbas & Liu, Yonggang & Zhang, Yuanjian & Chen, Zheng, 2024. "Review on eco-driving control for connected and automated vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    6. Zhongtai Jiang & Dexin Yu & Huxing Zhou & Siliang Luan & Xue Xing, 2021. "A Trajectory Optimization Strategy for Connected and Automated Vehicles at Junction of Freeway and Urban Road," Sustainability, MDPI, vol. 13(17), pages 1-22, September.
    7. Xin, Qi & Fu, Rui & Ukkusuri, Satish V. & Yu, Shaowei & Jiang, Rui, 2021. "Modeling and impact analysis of connected vehicle merging accounting for mainline random length tight-platoon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

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