The Future of Fully Automated Vehicles : Opportunities for Vehicle- and Ride-Sharing, with Cost and Emissions Savings
Fully automated or autonomous vehicles (AVs) hold great promise for the future of transportation. By 2020 Google, auto manufacturers and other technology providers intend to introduce self-driving cars to the public with either limited or fully autonomous capabilities. AVs may be able to save the U.S. economy up to $37.7 billion in comprehensive costs from safety, mobility and parking improvements at the 10% market penetration, and potentially up to $447.1 billion with 90% market penetration. Even with only 10% market share, over 1,000 lives could be saved annually. However, realizing these potential benefits while avoiding potential pitfalls requires more than just technology advancements: significant barriers to a successful rollout include AV costs, liability, security, and privacy. Once fully self-driving vehicles can safely and legally drive unoccupied on U.S. streets, a new transportation mode for personal travel looks set to arrive. This new mode is the shared automated vehicle (SAV), combining on-demand service with self-driving capabilities. This work simulates a fleet of SAVs operating within the city of Austin, using Austin’s transportation network and travel demand flows. This model incorporates dynamic ride-sharing (DRS), allowing two or more travelers with similar origins, destinations and departure times to share a ride. Model results indicate that each SAV could replace around 10 conventionally-owned household vehicles while serving over 56,000 person-trips. SAVs’ ability to relocate while unoccupied between serving one traveler and the next may cause an increase of 4-8% more travel; however, DRS can result in reduced overall vehicle-miles traveled (VMT), given enough SAV-using travelers willing to ride-share. SAVs should produce favorable emissions outcomes, with an estimated 16% less energy use and 48% lower volatile organic compound (VOC) emissions, per person-trip formerly served by a household vehicle.
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- Summary URL:
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Project Title: Anticipating Long-Term Energy and GHG Emissions Impacts of Autonomous Vehicles.
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Corporate Authors:
University of Texas, Austin
Center for Transportation Research, 1616 Guadalupe Street
Austin, TX United States 78701-1255Southwest Region University Transportation Center
Texas A&M University
3135 TAMU
College Station, TX United States 77843-3135Research and Innovative Technology Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Authors:
- Fagnant, Daniel J
- Kockelman, Kara M
- Publication Date: 2014-8
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 102p
Subject/Index Terms
- TRT Terms: Costs; Intelligent vehicles; Pollutants; Ridesharing; Simulation; Travel demand; Vehicle miles of travel; Vehicle sharing
- Geographic Terms: Austin (Texas)
- Subject Areas: Economics; Environment; Highways; Planning and Forecasting; Vehicles and Equipment; I10: Economics and Administration; I15: Environment; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01538222
- Record Type: Publication
- Report/Paper Numbers: SWUTC/2014/600451-00081-1, 600451-00081-1
- Contract Numbers: DTRT12-G-UTC06
- Files: UTC, TRIS, RITA, ATRI, USDOT
- Created Date: Sep 25 2014 8:59AM