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Using Cooperative Adaptive Cruise Control (CACC)to Form High-Performance Vehicle Streams. Definitions, Literature Review and Operational Concept Alternatives

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  • Shladover, Steven E.
  • Nowakowski, Christopher
  • Lu, Xiao-Yun

Abstract

Cooperative Adaptive Cruise Control (CACC) is a term that has been used rather loosely in recent years, such that different people visualize different functions and capabilities when discussing CACC systems. Thus, there are now multiple system concepts that have been described under the CACC label, and the functionalities included in these varied concepts can be quite different from each other. At the heart of each CACC concept is the merging of Adaptive Cruise Control (ACC), a subset of the broader class of automated speed control systems, with acooperative element, such a Vehicle-to-Vehicle (V2V) or Infrastructure-to-Vehicle (I2V) communication. The V2V communication could provide information about the vehicle or vehicles directly in front of you, and the I2V communication could provide information about traffic further ahead or about current speed restrictions as part of an active traffic management approach.There are two primary transportation system motivations for the development of CACC. The first motivation is to reduce traffic congestion and the second is to improve fuel efficiency. It may also improve safety, although it is not primarily a safety system. At the individual driver level, CACC can make ACC more attractive and convenient to drivers by providing behavior that is more responsive to preceding vehicle speed changes, that gives an enhanced sense of safety because of its quicker response, and that deters cut-ins at shorter gaps.

Suggested Citation

  • Shladover, Steven E. & Nowakowski, Christopher & Lu, Xiao-Yun, 2018. "Using Cooperative Adaptive Cruise Control (CACC)to Form High-Performance Vehicle Streams. Definitions, Literature Review and Operational Concept Alternatives," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3w6920wz, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt3w6920wz
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    References listed on IDEAS

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    1. Lu, Xiao-Yun & Shladover, Steven E, 2011. "Automated Truck Platoon Control," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7c55g2qs, Institute of Transportation Studies, UC Berkeley.
    2. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    3. Shladover, Steven E & Lu, Xiao-Yun & Nowakowski, Christopher, 2011. "Development and Assessment of Selected Mobility Applications for VII: Principal Findings," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5r33k6wk, Institute of Transportation Studies, UC Berkeley.
    4. Browand, Fred & McArthur, John & Radovich, Charles, 2004. "Fuel Saving Achieved in the Field Test of Two Tandem Trucks," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt29v570mm, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Vivek Sujan & Perry T. Jones & Adam Siekmann, 2022. "Characterizing the Payback and Profitability for Automated Heavy Duty Vehicle Platooning," Sustainability, MDPI, vol. 14(4), pages 1-35, February.

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