Land Use and Transportation Policies for a Sustainable Future with Autonomous Vehicles: Scenario Analysis with Simulations

Liming Wang, Portland State University



Even though there are tremendous uncertainties in the timing and evolution path of the Autonomous Vehicles (AV) technology, it may become a likely reality within most MPOs' long-range regional transportation plan horizon of twenty years. Yet a recent survey of largest MPOs in the US indicates only one of them "even mentions driverless, automated, or autonomous vehicles in its most recent RTP" (Guerra, 2016 page 211). One of the uncertainties in assessing the impacts of AV is their direction: on one hand, self-driving cars could increase VMT by increasing roadway capacity, lowering costs of travel; on the other, they may reduce VMT by enabling more car-sharing, improving access to transit, eliminating the fixed costs of car ownership, and reclaiming parking space. To date, there is no suitable conceptual framework or modeling tools available to MPOs for quantitatively assessing the likely long-term effects of AV or potential policy scenarios.

Built on a phase I research project funded by NITC studying emerging transportation modes including AV, this proposal will investigate long-term travel and land use outcomes in response to various policy and technology scenarios by simulations with an aim of identifying policy scenarios that help promote sustainable and equitable future patterns of travel and land use. The products of the project include working papers and conference presentations of the methodology and outcomes of the scenario simulations, as well as an open source software tool that will be made available to researchers and practitioners to create and run simulations of their own scenarios.

This project touches upon three of NITC's sub-themes for the goal of improving the mobility of people and goods to build strong communities. In particular, it helps advance innovations and smart cities and develops data, models, and tools for assessing the likely impacts of AV with the goal of identifying policies that shape the evolution of the AV technology and builds sustainable and equitable communities.

Project Details

Project Type:
Project Status:
In Progress
End Date:
August 15,2020
UTC Grant Cycle:
NITC 16 Round 2
UTC Funding:

Other Products

  • Gehrke, S. R., & Wang, L. M. (2020). Operationalizing the neighborhood effects of the built environment on travel behavior. Journal of Transport Geography, 82. doi:10.1016/j.jtrangeo.2019.102561 (PUBLICATION)
  • Influence of Autonomous Vehicles on Travel Behavior of 50+ Years Population (PRESENTATION)