Land Use and Transportation Policies for a Sustainable Future with Autonomous Vehicles: Scenario Analysis with Simulations
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 metropolitan planning organizations (MPOs) long-range regional transportation plan horizons 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 vehicle miles of travel (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.
- Record URL:
Language
- English
Project
- Status: Active
- Funding: $310342
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Contract Numbers:
NITC 1242
69A3551747112
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 Urban Studies and Planning
P.O. Box 751
Portland, Oregon United States 97207Metro
600 NE Grand Ave.
Portland, OR United States 97232-2736Oregon Department of Transportation
555 13th Street NE
Salem, OR United States 97301TREC at Portland State University
1900 SW Fourth Ave, Suite 175
P.O. Box 751
Portland, Oregon United States 97201 Department of Transportation
PO Box 27210
Tucson, Arizona United States 85726-7210Pima County Traffic Engineering
Tucson, AZ United StatesInstitute for Sustainable Solutions
Portland State University
Portland, Oregon United States 97201 -
Managing Organizations:
TREC at Portland State University
1900 SW Fourth Ave, Suite 175
P.O. Box 751
Portland, Oregon United States 97201 -
Project Managers:
Hagedorn, Hau
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Performing Organizations:
Urban Studies and Planning
P.O. Box 751
Portland, Oregon United States 97207 College of Engineering
1209 East 2nd Street
Tucson, AZ United States 85721 -
Principal Investigators:
Wang, Liming
Wu, Yao-Jan
- Start Date: 20180815
- Expected Completion Date: 20200930
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Forecasting; Intelligent vehicles; Land use; Metropolitan planning organizations; Simulation; Software; Transportation policy
- Subject Areas: Highways; Planning and Forecasting; Policy; Vehicles and Equipment;
Filing Info
- Accession Number: 01674839
- Record Type: Research project
- Source Agency: National Institute for Transportation and Communities
- Contract Numbers: NITC 1242, 69A3551747112
- Files: UTC, RIP
- Created Date: Jul 5 2018 7:54PM