Emerging Approaches to Autonomous Vehicles in Transportation Policy and Planning

As autonomous vehicles (AVs) emerge, cities must grapple with how to utilize and manage these new disruptive technologies to advance public policy goals and deliver urban services related to public health, equity, economic development, mobility, and sustainability. Yet, cities and their communities and governmental institutions remain largely reactive in how they manage and integrate emerging technologies into policies, regulations and existing socio-technical systems. Instead, urban governments and communities must learn how to anticipate the potential impacts of emerging technologies (Guston 2014) and manage them based on community needs and values. Transportation planning models, for example, form the basis for transportation infrastructure planning, investment and development. The models are typically updated every 5-10 years and based on one-day travel survey data. As a result, AVs are not currently easily captured in the models or in the transportation planning process. AVs offer an opportunity to re-think how people and goods move around. As such, AVs could be a catalyst for new mobility policy and planning. Yet, AVs might also further entrench car culture in automobile dominated cities, drawing people away from other modes, including biking and public transit, with significant implications on land use, equity and mobility access. If cities are to seize the wider opportunity presented by the emergence of AVs, now is the time to develop policy and infrastructure solutions. This study will explore how policy, planning and modeling approaches to AVs are emerging in metropolitan planning organizations in the US. The results will provide the most comprehensive assessment of AV policy and planning to date and offer an opportunity to reflect on the limitations of current approaches and possibilities for future efforts. This study will examine the most recent LRTPs developed by MPOs to analyze how autonomous vehicles are being incorporated. More specifically, the research team will analyze how transportation planners are characterizing the risks and benefits of AVs, identify emerging regulatory frameworks, and analyze early modeling approaches to forecast traveler behavior under alternative AV scenarios. Following this, the team will conduct interviews with management and staff from a sample of ten MPOs to explore in more depth efforts to model AVs, and identify emerging critical barriers and innovations to transportation policy and planning for AVs. Interviews will focus on modeling approaches to AVs and how they are incorporating human attitudes, values, and perceptions in the modeling and forecasting of future travel demand related to AVs. The researchers have strong relationships with the Association of Metropolitan Planning Organizations (AMPO) and will work with them on this project. The outcome of this study will be the most comprehensive analysis of AV policy, modeling and planning to date. This will enable greater reflection on the governance of AVs at this critical time.


  • English


  • Status: Completed
  • Funding: $96,000
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Center for Teaching Old Models New Tricks (TOMNET)

    Arizona State University
    Tempe, AZ  United States  85287
  • Performing Organizations:

    Center for Teaching Old Models New Tricks (TOMNET)

    Arizona State University
    Tempe, AZ  United States  85287
  • Principal Investigators:

    Miller, Thaddeus

    Pendyala, Ram

  • Start Date: 20191001
  • Expected Completion Date: 20211001
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01755255
  • Record Type: Research project
  • Source Agency: Center for Teaching Old Models New Tricks (TOMNET)
  • Contract Numbers: 69A3551747116
  • Files: UTC, RIP
  • Created Date: Oct 21 2020 8:46PM