Pedestrian Behavior and Interaction with Autonomous Vehicles

Connected and autonomous vehicles (CAV) are advancing in many ways in the current automobile market, such as adaptive cruise control, forward collision warning, and lane detection. By 2023, worldwide net additions of vehicles equipped with hardware that could enable autonomous driving without human supervision may exceed 700,000 units, which is up from 137,129 units in 2018. McKinsey & Co estimated that self-driving vehicles would eliminate 90% of the vehicle accidents in the United States and save up to US$190 billion of the expenses related to damages and health costs while also saving thousands of lives. It is expected that self-driving technology will enable the efficient use of traffic patterns, reduce traffic congestion, and increase roadway capacity. CAV will have the ability to understand the environment around them without any human involvement. Studying the interactions between pedestrians and autonomous vehicles is challenging due to the complexity of this interaction process. Pedestrians often rely on eye contact, hand motions, or audible dialogue with human drivers to accomplish roadway crossings. However with CAVs there is no driver with whom to interact. The lack of human interaction and communication inherent with CAV technology could influence unpredictable pedestrian behavior. Autonomous vehicles are expected to be designed to attempt to overcome this challenge. Communication systems between CAV and pedestrian are being developed and tested. However, how CAVs interact with pedestrians is a relatively unexplored topic due to the difficulty in replicating pedestrian-CAV interactions in a safe manner. This study proposes the use of virtual reality (VR) as a means to overcome the safety challenges inherent in studying pedestrian-vehicle interactions and will focus on identifying any differences in pedestrian behavior when CAV are introduced to the traffic stream. The central research question of this proposal is: Are there significant behavioral changes in the way pedestrians interact with vehicles at a crossing when a portion of the vehicles is autonomous? The proposed research will focus on the following topics: (1) To determine the impact of autonomous vehicles on pedestrian measures such as gap acceptance, waiting time while crossing the road and pedestrian acceleration. (2) Measuring any pedestrian behavior changes with the automation level of the vehicle. (3) Measuring the psychophysiological (e.g., Electrodermal Activity-EDA, blood pressure, and heart rate change) changes of the pedestrians’ while interacting with AV.

    Language

    • English

    Project

    • Status: Active
    • Funding: $90007
    • Contract Numbers:

      69A3551747133

    • Sponsor Organizations:

      Center for Advanced Multimodal Mobility Solutions and Education

      University of North Carolina, Charlotte
      Charlotte, NC  United States  28223

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      University of North Carolina - Charlotte

      9201 University City Blvd
      Charlotte, North Carolina  United States  28223-0001
    • Project Managers:

      Fan, Wei

    • Performing Organizations:

      University of Connecticut

      Sponsored Programs Services
      438 Whitney Road Ext 1133
      Storrs, CT  United States  06269-1133
    • Principal Investigators:

      Lownes, Nicholas

    • Start Date: 20201001
    • Expected Completion Date: 20210930
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01754808
    • Record Type: Research project
    • Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
    • Contract Numbers: 69A3551747133
    • Files: UTC, RiP
    • Created Date: Oct 16 2020 3:42PM