Exploratory Modeling and Analysis for Automated Vehicles in Utah

Autonomous Vehicles (AVs) have the potential to offer benefits and flexibility in travel, which can lead to significant reductions in the generalized travel cost, and possibly more demand. The combination of the AV technology with Mobility as a Service (MaaS) creates a new disruptive transportation mode – Shared Autonomous Vehicles (SAVs) that have the promise to re-define the transportation landscape by improving mobility and competing with conventional transportation modes. While it is foreseen that SAVs could potentially be on the market in the near future, the long-range transportation planning process has yet to account for their impact. The authors fill this gap by presenting a framework of modeling SAVs to seamlessly integrate them into the four-step travel demand models that are widely used by transportation agencies. Using the Wasatch Front region in the State of Utah as a case study, the authors present such modeling effort for the year 2040 forecast horizon. Delineated by different combinations of trip growth rates and SAV market attractiveness, the designed scenarios revealed that SAVs could increase the total number of trips by 1% to 7%. SAVs could shift travel away from conventional transportation modes. It is estimated that SAVs will increase daily Vehicle Miles Traveled (VMT) by 4% to 9% across designed scenarios due to improved mobility of underserved populations and additional repositioning trips.

• Record URL:
  https://www.ugpti.org/resources/reports/details.php?id=1059
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/61596
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Utah, Salt Lake City

  Department of Civil & Environmental Engineering
  Salt Lake City, UT  United States  84112

  Mountain-Plains Consortium

  North Dakota State University
  Fargo, ND  United States  58108

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Liu, Xiaoyue Cathy
  • Haghighi, Nima
• Publication Date: 2022-3

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; References; Tables;
• Pagination: 29p

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Forecasting; Shared mobility; Travel demand
• Geographic Terms: Utah
• Subject Areas: Highways; Passenger Transportation; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01843778
• Record Type: Publication
• Report/Paper Numbers: MPC-22-452
• Contract Numbers: MPC-542
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Apr 25 2022 3:50PM