An Application of a Rank Ordered Probit Modeling Approach to Understanding Level of Interest in Autonomous Vehicles

Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread interest in collecting data on and modeling people’s preferences for choice alternatives, rank-ordered data are rarely collected in travel surveys and very little progress has been made in the ability to rigorously model such data and obtain reliable parameter estimates. This paper presents a rank ordered probit modeling approach that overcomes limitations associated with prior approaches in analyzing rank ordered data. The efficacy of the rank ordered probit modeling methodology is demonstrated through an application of the model to understand preferences for alternative configurations of autonomous vehicles (AV) using the 2015 Puget Sound Regional Travel Study survey data set. The methodology offers behaviorally intuitive model results with a variety of socio-economic and demographic characteristics, including age, gender, household income, education, employment and household structure, significantly influencing preference for alternative configurations of AV adoption, ownership, and shared usage. The ability to estimate rank ordered probit models offers a pathway for better utilizing rank ordered data to understand preferences and recognize that choices may not be absolute in many instances.

• Record URL:
  https://ctr.utexas.edu/wp-content/uploads/148.pdf
• 
• Summary URL:
  https://library.ctr.utexas.edu/Presto/catalogid=36826
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/66296
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Data-Supported Transportation Operations and Planning Center

  University of Texas at Austin
  Austin, TX  United States  78701

  University of Texas, Austin

  Center for Transportation Research
  3925 W. Braker Lane, 4th Floor
  Austin, TX  United States  78759

  US Department of Transportation

  ,    

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Nair, Gopindra S
  • Astroza, Sebastian
  • Bhat, Chandra R
  • 0000-0002-0715-8121
  • Khoeini, Sara
  • Pendyala, Ram M
• Publication Date: 2018-9

Language

• English

Media Info

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

Subject/Index Terms

• TRT Terms: Automobile travel; Autonomous vehicles; Mode choice; Probits; Ranking (Statistics); Stated preferences; Travel demand; Travel surveys
• Identifier Terms: Puget Sound Regional Travel Study
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01699937
• Record Type: Publication
• Report/Paper Numbers: D-STOP/2018/148, Report 148, Technical Report 148
• Contract Numbers: DTRT13-G-UTC58
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Mar 29 2019 9:57AM