A framework for the impact of highly automated vehicles with limited operational design domains

Highly automated vehicles (AV) are in the early stages of deployment and are likely to have significant impacts on the United States transportation system. In particular, a broad deployment of shared, on-demand AVs might significantly impact vehicle ownership and transportation energy consumption; projecting these impacts is essential for climate, infrastructure, and policy planning. However, it seems increasingly likely that AVs will be deployed gradually over a period of decades, in which case there may be geographic or functional variation in their availability. This might occur for a combination of technological, policy, and economic reasons.This manuscript seeks to advance a new framework for projecting AV impacts, with a particular focus on energy consumption impacts. Specifically, the authors introduce a framework for AV impacts that allows for AVs catering to specific operating environments or ride types. As a demonstration of this framework, the authors use the 2009 National Household Transportation Survey (NHTS) to segment US household travel demand based on built environment and ride length. The authors' framework allows them to specify AV “availability” for each population segment and ride type and use that information to predict the impact of AVs. The authors analyze a case scenario where shared, on-demand AVs are mostly suited for short trips in highly urbanized environments. They project the impact on household relocation, private vehicle ownership, induced travel demand, and fuel consumption. Utilization of this framework would help identify policy levers for sustainable deployment of AVs.

• Record URL:
  https://doi.org/10.1016/j.tra.2020.06.024
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856420306431
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Bin-Nun, Amitai Y
  • Binamira, Isabel
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 174-188
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 139
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Automobile ownership; Autonomous vehicles; Built environment; Economic impacts; Environmental impacts; Forecasting; Fuel consumption; Households; Ridesharing; Sustainable transportation; Urban areas
• Subject Areas: Economics; Environment; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01747682
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 7 2020 5:34PM