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Updated: Feb 27, 2026
Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
Published on: June 9, 2020
Examining how different measurement approaches impact safety outcomes in child pedestrian research: Implications for
Michael R Corbett1, Barbara A Morrongiello1
1Department of Psychology, University of Guelph, Ontario, N1G 2W1, Canada.
Insights
Estimating child pedestrian injury risk using average walking speed overestimates danger. Direct measurement of in-road behavior provides a more accurate assessment of child pedestrian safety and injury risk.
Area of Science:
- Pedestrian safety research
- Child behavior analysis
- Injury prevention science
Background:
- Child pedestrian injury is a significant public health concern.
- Current research often estimates crossing outcomes from average walking speeds.
- This method may introduce measurement bias in assessing injury risk.
Purpose of the Study:
- To investigate measurement bias in child pedestrian injury research.
- To compare outcome estimates derived from average walking speed versus direct in-road behavior measurement.
- To quantify the impact of this bias on risk assessment.
Main Methods:
- Utilized a within-subjects design.
- Employed a fully immersive virtual reality pedestrian simulator.
- Collected both average walking speed estimates and direct in-road behavior measures.
Main Results:
- Significant measurement bias was identified when using average walking speed.
- Overestimation of high-risk crossings and underestimation of missed opportunities were observed.
- This bias leads to an overall overestimate of children's pedestrian injury risk.
Conclusions:
- Direct measurement of in-road behavior is crucial for accurate child pedestrian injury risk assessment.
- Reliance on average walking speed introduces bias, potentially skewing prevention strategies.
- Understanding measurement differences is key to refining child safety interventions.
Abstract:
There has been a great deal of research aimed at understanding the causes of child pedestrian injury. Many different methods have been employed with the goal of designing simulations that produce rigorous assessment of children's behaviors without putting children at risk of actual pedestrian injury. Most research has assessed children's pre-crossing decision making and extrapolated crossing outcome measures from estimates of mean walking speed. This study explores the nature and extent of measurement bias that is introduced when average walking speed is used to produce estimates of outcomes versus measuring actual in-road behavior directly. Using a within-subjects design and a fully immersive virtual reality pedestrian simulator, both measures were taken. Comparisons based on regression models revealed the extent of differences in results produced by measurement bias. Results indicated that measurement bias is produced when average walking speed is used such that hits and high risk crossings are overestimated and missed opportunities are underestimated, resulting in an overall overestimate of children's risk for pedestrian injury. The discussion highlights how these two measurement approaches emphasize different underlying processes as determinants of child pedestrian injury risk.
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