Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Analysis of Distracted Pedestrians Crossing Behavior: An Immersive Virtual Reality Application

Methusela Sulle, Judith Mwakalonge, Gurcan Comert, Saidi Siuhi, Nana Kankam Gyimah, Jaylen Roberts, Denis Ruganuza

TL;DR

The paper tackles pedestrian safety at signalized intersections amid rising mobile-device distraction by deploying an immersive VR framework that simulates undistracted, mobile-distraction, and LED-intervention crossing scenarios with eye-tracking. It demonstrates that distraction prolongs crossing duration and increases variability, while LED interventions modestly reduce delays but do not fully counteract distraction effects. ANOVA identifies final walking speed, eye-tracking during mobile crossing, and crossing speed as key predictors of crossing duration, underscoring the need for integrated behavioral and physical safety measures. The study advances VR-based pedestrian safety research and offers actionable guidance for urban planners and policymakers to design multi-sensory interventions and conduct safe, repeatable scenario testing for diverse urban settings.

Abstract

Pedestrian safety is a critical public health priority, with pedestrian fatalities accounting for 18% of all U.S. traffic deaths in 2022. The rising prevalence of distracted walking, exacerbated by mobile device use, poses significant risks at signalized intersections. This study utilized an immersive virtual reality (VR) environment to simulate real-world traffic scenarios and assess pedestrian behavior under three conditions: undistracted crossing, crossing while using a mobile device, and crossing with Light-emitting diode (LED) safety interventions. Analysis using ANOVA models identified speed and mobile-focused eye-tracking as significant predictors of crossing duration, revealing how distractions impair situational awareness and response times. While LED measures reduced delays, their limited effectiveness highlights the need for integrated strategies addressing both behavioral and physical factors. This study showcases VRs potential to analyze complex pedestrian behaviors, offering actionable insights for urban planners and policymakers aiming to enhance pedestrian safety.

Analysis of Distracted Pedestrians Crossing Behavior: An Immersive Virtual Reality Application

TL;DR

The paper tackles pedestrian safety at signalized intersections amid rising mobile-device distraction by deploying an immersive VR framework that simulates undistracted, mobile-distraction, and LED-intervention crossing scenarios with eye-tracking. It demonstrates that distraction prolongs crossing duration and increases variability, while LED interventions modestly reduce delays but do not fully counteract distraction effects. ANOVA identifies final walking speed, eye-tracking during mobile crossing, and crossing speed as key predictors of crossing duration, underscoring the need for integrated behavioral and physical safety measures. The study advances VR-based pedestrian safety research and offers actionable guidance for urban planners and policymakers to design multi-sensory interventions and conduct safe, repeatable scenario testing for diverse urban settings.

Abstract

Pedestrian safety is a critical public health priority, with pedestrian fatalities accounting for 18% of all U.S. traffic deaths in 2022. The rising prevalence of distracted walking, exacerbated by mobile device use, poses significant risks at signalized intersections. This study utilized an immersive virtual reality (VR) environment to simulate real-world traffic scenarios and assess pedestrian behavior under three conditions: undistracted crossing, crossing while using a mobile device, and crossing with Light-emitting diode (LED) safety interventions. Analysis using ANOVA models identified speed and mobile-focused eye-tracking as significant predictors of crossing duration, revealing how distractions impair situational awareness and response times. While LED measures reduced delays, their limited effectiveness highlights the need for integrated strategies addressing both behavioral and physical factors. This study showcases VRs potential to analyze complex pedestrian behaviors, offering actionable insights for urban planners and policymakers aiming to enhance pedestrian safety.

Paper Structure

This paper contains 24 sections, 7 figures, 8 tables.

Table of Contents

  1. Introduction
  2. Related Works
  3. Distraction Types and Behavior Analysis
  4. Methodological Approaches: Simulation Environments
  5. Safety Performance Metrics and Surrogate Measures
  6. Counteractive Measures and Intervention Effectiveness
  7. Methodology
  8. Study Design and Simulated Environment
  9. Data Collection and Study Framework
  10. Immersive VR Application
  11. Data Collection
  12. Operational Variables
  13. Pre and Post-Study Survey
  14. Results and Discussion
  15. Validation and Reliability of VR generated data
  16. ...and 9 more sections

Figures (7)

  • Figure 1: Traffic Crashes Involving Pedestrians (2011–2021) nhtsaPedestrianSafety: (a) Fatal crashes, (b) Injury crashes.
  • Figure 2: Intersection Studied.
  • Figure 3: Simulated Scenarios.
  • Figure 4: Data Collection.
  • Figure 5: Density distributions of pedestrian crossing durations across three scenarios: No Phone, Phone, and Phone & Safety Measure.
  • ...and 2 more figures