Modeling the Impact of Shared Autonomous Vehicles on Travel Behaviors

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, this paper presents 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. The results will assist public agencies in understanding the impacts of SAVs on travel patterns to further consider the special needs of AV technology in long-range cost estimates and programming processes.

• Record URL:
  • https://annualmeeting.mytrb.org/OnlineProgram/Details/15777
• Supplemental Notes:
  • This paper was sponsored by TRB committee AEP15 Standing Committee on Transportation Planning Analysis and Application.
• Corporate Authors:

  Transportation Research Board

  ,    
• Authors:
  • Haghighi, Nima
  • Liu, Xiaoyue Cathy
  • Yi, Zhiyan
• Conference:
  • Transportation Research Board 100th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2021-1-5 to 2021-1-29
• Date: 2021

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 21p

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Case studies; Shared mobility; Traffic forecasting; Travel behavior; Travel demand; Vehicle miles of travel
• Identifier Terms: Mobility-as-a-Service (MaaS)
• Geographic Terms: Wasatch Front (Utah)
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01764075
• Record Type: Publication
• Report/Paper Numbers: TRBAM-21-03018
• Files: TRIS, TRB, ATRI
• Created Date: Feb 4 2021 10:57AM