• Impacts of Autonomous Vehicle Technology on Transportation Systems

    NCDOT Research Project Number: 2019-11

 Executive Summary


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    Autonomous vehicle (AV) technology is expected to fundamentally change transportation systems. The Transportation Planning Branch at NCDOT, which is responsible for the state’s longrange transportation plan, needs state-of-the-art information and predictions on AV technology and its potential impacts on transport to be better prepared for the upcoming changes and maximize the social benefits that this technology will enable. 

    The Transportation Systems group faculty (Drs. Bardaka, List, Rouphail, and Williams) and Dr. Frey (Environmental Engineering) in the Department of Civil, Construction, and Environmental Engineering at NCSU as well as Dr. Cummings, the Director of the Humans and Autonomy Laboratory at Duke University will work together to leverage existing research in the area of AV technology to evaluate impacts and provide policy and future research recommendations to NCDOT. The study will include a comprehensive literature review on AV technology and its impact on transportation demand, capacity, mobility, traffic safety, emissions, energy use, and land use. 

    The results of previous research will be analyzed and case studies for North Carolina will be developed. The study will also provide recommendations to NCDOT regarding changes in policies and regulations, future test plans and test infrastructure, and research priorities in the area of AV technology. As part of this study, the researchers will work closely with the Transportation Planning Branch to provide guidance on how existing models (such as the statewide demand model) could be adapted to account for the presence of AVs.
  
Eleni Bardaka
Researchers
  
Eleni Bardaka; Nagui M. Rouphail; George F. List; Billy M. Williams; H. Christopher Frey
  
Jamal S. Alavi
  
Lisa E. Penny

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 Report Period

  • August 1, 2018 - July 31, 2020

 Status

  • In Progress

 Category

  • Planning, Policy, Programming and Multi-modal

 Sub Category

  • Traffic Forecasting

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