Nudging Pedestrian Walking Dynamics Using Light Intensity and Color: A Virtual Reality Study

Dorine Duives; Arco van Beek; Yan Feng

doi:10.17815/CD.2025.186

Authors

Dorine Duives Department of Transport & Planning, Civil Engineering Geosciences, Delft University of Technology, Delft, Netherlands
Arco van Beek Department of Transport & Planning, Civil Engineering Geosciences, Delft University of Technology, Delft, Netherlands
Yan Feng Department of Transport & Planning, Civil Engineering Geosciences, Delft University of Technology, Delft, Netherlands

DOI:

https://doi.org/10.17815/CD.2025.186

Keywords:

Pedestrians, Walking speed, Light conditions, Virtual Reality (VR), Laboratory experiment

Abstract

Crowd management attempts to efficiently and safely guide pedestrian crowds. "Nudging" is one way to steer the crowd, gently coaxing people in the right direction. In this study, we study whether light can be used to "nudge" pedestrians' operational walking dynamics. Specifically, we aim to determine the extent to which light intensity and light color influence the average walking speed of pedestrians. Six light conditions are tested in a VR experiment: regular white light (approx. 100 lux), dark (approx. 1 lux), bright (approx. 300 lux), blue, green, and red light. This study concludes that A) the average walking speed decreases in darker light (10.4%) conditions and increases in brighter light (7.7%) or colored (2.8% - 8%) conditions. In addition, pedestrians decelerate more slowly and cautiously in dark light conditions, while the acceleration and deceleration profile do not significantly change for bright, blue, green, and red light conditions.

In addition, this study assessed whether a wireless HMD can be used to study pedestrians' average walking dynamics because a relatively new type of VR simulator was adopted. The validation analysis concludes that VR experiments featuring wireless HMD and open-plan movements overestimate step time (+7.5%) and step length (+12.8%) and underestimate the average walking speed (-22.8%). In addition, we find that relative trends regarding the impact of socio-demographic characteristics on the mean of the three analyzed metrics can, in most cases, be reproduced.

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