On investigating the potential effects of private autonomous vehicle use on home/work relocations and commute times

The current study is motivated by the need to better understand the potential impacts that vehicular automation may have on individual decisions of residential and work relocation in a future autonomous vehicle (AV) scenario. The study employs a multivariate approach to model five behavioral dimensions simultaneously: (1) technology-savviness (TS) propensity, (2) interest in productive use of travel time (IPTT) propensity, (3) interest in work relocation, (4) interest in residential relocation, and (5) tolerance to an increase in commute travel time. Data from a web-based survey of commuters in 2017 in the Dallas-Fort Worth Metropolitan Area (DFW) is employed. The results show that both TS and IPTT, as well as demographic variables, impact relocation decisions when individuals have a private AV available for their commute. Importantly, there is considerable heterogeneity across individuals in the willingness to relocate and/or accept longer commute times in an AV future. As such, the authors' model results may be used to inform inputs to land use and travel demand models in an AV future. Also, the authors' results suggest that the magnitude of value of travel time savings (VTTS) decrease considered in many earlier AV impact simulation studies may be much higher than reality. Relative to 50% and even 100% VTTS decreases assumed in many studies, the authors' results suggest a much more modest 30% or so overall decrease in VTTS because of the ability to commute in a privately-owned AV. Finally, the authors' results do predict a rather substantial extent of urban sprawl due to AVs, potentially up to a 68% increase in the horizontal spread of cities such as Dallas-Fort Worth, unless proactive planning and policies are implemented to avert such consequences of AVs.

• Record URL:
  https://doi.org/10.1016/j.trc.2019.11.013
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X19311088
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Moore, Michael A
  • Lavieri, Patrícia S
  • Dias, Felipe F
  • Bhat, Chandra R
  • 0000-0002-0715-8121
• Publication Date: 2020-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 166-185
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 110
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Automobile travel; Autonomous vehicles; Commuting; Employment; Location; Mathematical models; Multivariate analysis; Private passenger vehicles; Residential location; Travel time; Urban sprawl; Value of time
• Geographic Terms: Dallas-Fort Worth
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01724807
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 10 2019 5:12PM