Pedestrian Behavior and Interaction with Autonomous Vehicles (Phase II)
Automobiles are being more advanced with improving the automotive support system such as adaptive cruise control, forward collision warning, lane detections, which are already influencing the automotive industry. 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. Gartner, Inc. Mc Kinsey & 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. This scenario will reduce vehicle insurance with time. It is expected that self-driving technology will enable the efficient use of traffic patterns, reduce traffic congestion, and increase roadway capacity. Autonomous vehicles will have the ability to understand the environment around them without any human involvement. For example, the headway distance of an upcoming vehicle, presence of non-motorized road users can be tracked by an autonomous vehicle. The interaction between pedestrian and autonomous vehicles are always challenging due to the complexity of this interaction process. While crossing a road, a pedestrian always checks the oncoming vehicles. Non-motorized users often rely on eye contact, hand motions, or audible dialogue with human drivers to accomplish roadway crossings. However, for autonomous vehicles (AVs), there is no driver with whom to interact, and in that case, the pedestrian can only check the surroundings. Human interaction and communication elimination with AV technology could influence unpredictable pedestrian behavior. Autonomous vehicles are expected to be designed in such a manner that it can create a similar situation as the human driver does. Mutual communication between the AV and pedestrians is important to understand pedestrian behavior. Currently, intensive research activity is being conducted for the autonomous vehicle technology; however, how an autonomous vehicle would interact with pedestrians is relatively ignored. Hence, the study of autonomous vehicle interaction with pedestrians is crucial. The first step of this research work is to understand the behavior of the pedestrian towards the AVs. 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. (2) This research work compares the human behavior changes with the automation level of the vehicle. (3) To understand 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: Completed
- Funding: $90007
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Contract Numbers:
69A3551747133
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Sponsor Organizations:
Center for Advanced Multimodal Mobility Solutions and Education
University of North Carolina, Charlotte
Charlotte, NC United States 28223Office 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
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Performing Organizations:
Sponsored Programs Services
438 Whitney Road Ext 1133
Storrs, CT United States 06269-1133 -
Principal Investigators:
Lownes, Nicholas
- Start Date: 20211001
- Expected Completion Date: 20230930
- Actual Completion Date: 20230930
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Behavior; Connected vehicles; Crosswalks; Pedestrian movement; Pedestrian vehicle interface; Pedestrians; Psychophysics; Virtual reality
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01784135
- Record Type: Research project
- Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
- Contract Numbers: 69A3551747133
- Files: UTC, RIP
- Created Date: Oct 4 2021 12:04PM