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Related Experiment Video

Updated: May 30, 2026

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
06:38

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

Event-Based Modeling of Driver Yielding Behavior at Unsignalized Crosswalks.

Bastian J Schroeder1, Nagui M Rouphail

  • 1Senior Research Associate Institute for Transportation Research and Education (ITRE) North Carolina State University Centennial Campus, Box 8601 Raleigh, NC 27695-8601 USA Bastian_Schroeder@ncsu.edu Tel.: +1-919-515-8565.

Journal of Transportation Engineering
|August 20, 2011
PubMed
Summary

Drivers are more likely to yield to pedestrians who walk briskly at unsignalized crossings. Pedestrian safety treatments significantly increased yielding, but effectiveness depends on activation.

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Area of Science:

  • Traffic Safety
  • Human Factors in Transportation
  • Predictive Modeling

Background:

  • Unsignalized pedestrian crossings present complex interactions between drivers and pedestrians.
  • Understanding driver yielding behavior is crucial for improving pedestrian safety.
  • Existing research often overlooks vehicle dynamics constraints and concurrent traffic conditions.

Purpose of the Study:

  • To identify factors influencing driver yielding behavior at unsignalized pedestrian crossings.
  • To develop predictive logistic regression models for driver yielding.
  • To evaluate the effectiveness of pedestrian safety treatments.

Main Methods:

  • Collected data at two unsignalized mid-block crosswalks in North Carolina.
  • Utilized 'before' and 'after' observational data for two pedestrian safety treatments.
  • Developed logit models incorporating driver attributes, pedestrian characteristics, and vehicle dynamics constraints.

Main Results:

  • Drivers were more likely to yield to assertive pedestrians (walking briskly).
  • Yield probability decreased with higher vehicle speeds, deceleration rates, and platooning.
  • Pedestrian safety treatments significantly increased driver yielding, contingent on activation.

Conclusions:

  • Driver yielding behavior is influenced by a complex interplay of factors.
  • Predictive models can represent driver yielding in microsimulation environments.
  • Pedestrian safety treatments show promise but require active engagement for maximum effectiveness.