Understanding the Impact of Autonomous Vehicles on Long-Distance Passenger and Freight Travel in Texas: Project Summary

Details

• Creators:
  Kockelman, Kara ; Fakhrmoosavi, Fatemeh ; Huang, Yantao ; Paithankar, Priyanka ; Perrine, Kenneth A. ; Zuniga-Garcia, Natalia ; Hawkins, Jason
• Corporate Creators:
  University of Texas at Austin. Center for Transportation Research
• Corporate Contributors:
  Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  Autonomous Vehicles Choice Models Distance Freight Traffic Market Penetration Mode Choice Public Health Travel Demand Travel Modes Vehicle Sharing
• Publication/ Report Number:
  0-7081
• Resource Type:
  Brief
• Geographical Coverage:
  Texas ; United States
• Edition:
  Project Summary Report
• Corporate Publisher:
  University of Texas at Austin. Center for Transportation Research
• Abstract:
  Researchers simulated US transportation systems and forecasted the impacts of AVs and shared AVs (SAVs) on destination and mode choices of long-distance passenger and freight trips within the US, targeting a future 20+ years from now. They created demand sub-models for vehicle ownership, trip timing/scheduling and frequency, trip purpose and travel party size, plus mode and destination choices. Datasets used include a survey designed and administered as part of this project (with 1,004 adult Americans responding to roughly 70 questions), the 2016/2017 National Household Travel Survey data, the Federal Highway Administration’s journey travel skim data (for cost and time values between 4,486 zones across the US), data, and the Environmental Protection Agency’s Smart Location data (for land use information on 84,000+ US Census tracts). Researchers used high-performance computing to generate a 10% synthetic (microscopic) US population of 12.1M households and 28.1M individuals across 73,056 census tracts to microsimulate passenger travel shifts in the presence of AVs and SAVs.
• Format:
  PDF
• Collection(s):
  US Transportation Collection Autonomous Vehicles
• Main Document Checksum:
  urn:sha-512:f88dedef892c8299a36cf0b0a8b90232758fbe1f0bf4cafe1cedbe32ca2c64558983ad11babbed461879b9fb1316844ae4a5fc05230633d16b417581ad5c6ec7
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/68790/dot_68790_DS1.pdf
• File Type:
  [PDF - 121.71 KB ]