Empirical Analysis of Consumer Aspects of Autonomous Cars

Evidence is rapidly accumulating that attaining the full set of benefits from Automated Vehicles (AVs) will require that they do not merely mimic human-driving behavior. For instance, in recently-completed early-stage research, Le Vine and colleagues demonstrated three prospective novel traffic-operations regimes associated with AVs, each of which have the potential to deliver a unique stream of benefits: (1) Vehicular kinematics (trajectories) to balance, in novel ways, between comfort and capacity; (2) A dynamic, voluntary and de-centralized (peer-to-peer) congestion pricing mechanism; and (3) Alternative vehicle-speed regimes (in some circumstances slower, while faster in others) The findings of this previous phase of research were purely theoretical, and what is therefore now required are empirical results through which AV-occupants' preference structures for these prospective behavioral regimes can be established.

Language

  • English

Project

  • Status: Active
  • Funding: $5388.00
  • Contract Numbers:

    49997-52-25

  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590

    University Transportation Research Center

    City College of New York
    Marshak Hall, Suite 910, 160 Convent Avenue
    New York, NY  United States  10031
  • Project Managers:

    Thorson, Ellen

    Eickemeyer, Penny

  • Performing Organizations:

    State University of New York, New Paltz

    1 Hawk Drive
    New Paltz, NY  United States  12561
  • Principal Investigators:

    LeVine, Scott

  • Start Date: 20150601
  • Expected Completion Date: 0
  • Actual Completion Date: 20160531
  • Source Data: RiP Project 39631

Subject/Index Terms

Filing Info

  • Accession Number: 01562706
  • Record Type: Research project
  • Source Agency: University Transportation Research Center
  • Contract Numbers: 49997-52-25
  • Files: UTC, RiP
  • Created Date: May 5 2015 1:00AM