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Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation

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  • Georges M. Arnaout
  • Jean-Paul Arnaout

Abstract

This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.

Suggested Citation

  • Georges M. Arnaout & Jean-Paul Arnaout, 2014. "Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(2), pages 186-199, March.
    • Handle: RePEc:taf:transp:v:37:y:2014:i:2:p:186-199
    DOI: 10.1080/03081060.2013.870791
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    Cited by:

    1. Sala, Marcel & Soriguera, Francesc, 2021. "Capacity of a freeway lane with platoons of autonomous vehicles mixed with regular traffic," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 116-131.
    2. Guo, Mengting & Bai, Yang & Li, Xia & Zhou, Wei & Wang, Chunyang & Ma, Xinwei & Gao, Huixin & Xiao, Yuewen, 2023. "Freeway capacity modeling and analysis for traffic mixed with human-driven and connected automated vehicles considering driver behavior characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    3. Hannes Sappl & Tibor Kubjatko, 2023. "A Driver Behavior Monitoring System for Sustainable Traffic and Road Construction," Sustainability, MDPI, vol. 15(16), pages 1-13, August.
    4. Shi, Xiaowei & Li, Xiaopeng, 2021. "Constructing a fundamental diagram for traffic flow with automated vehicles: Methodology and demonstration," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 279-292.
    5. Jan Kunkler & Maximilian Braun & Florian Kellner, 2021. "Speed Limit Induced CO 2 Reduction on Motorways: Enhancing Discussion Transparency through Data Enrichment of Road Networks," Sustainability, MDPI, vol. 13(1), pages 1-22, January.
    6. Zhong, Zijia & Lee, Joyoung, 2019. "The effectiveness of managed lane strategies for the near-term deployment of cooperative adaptive cruise control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 257-270.
    7. Marc-Olivier Pepin & Georges A. Tanguay, 2019. "Estimation of Car Trips Generated by the Arrival of Autonomous Vehicles in the Montreal Metropolitan Area," CIRANO Working Papers 2019s-17, CIRANO.
    8. Tanvi Maheshwari & Kay W. Axhausen, 2021. "How Will the Technological Shift in Transportation Impact Cities? A Review of Quantitative Studies on the Impacts of New Transportation Technologies," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    9. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
    10. Yang, Shiyan & Shladover, Steven E. & Lu, Xiao-Yun & Spring, John & Nelson, David & Ramezani, Hani, 2018. "A First Investigation of Truck Drivers’ On-the-Road Experience Using Cooperative Adaptive Cruise Control," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt92359572, Institute of Transportation Studies, UC Berkeley.

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