Data underlying the publication: Nudging pedestrian walking dynamics using light intensity and color
doi: 10.4121/9b30a3cc-df03-4c06-8ba7-8df4648b2d80
This dataset contains data collected during a Virtual Reality experiments at Delft University of Technology. The experiments took place 15 May 2024 until 2 June 2024. In this study, we studied whether light can be used to `nudge' pedestrians' operational walking dynamics. Specifically, we aimed 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.
This dataset is being made public both to act as supplementary data for publications and in order for other researchers to use this data in their own work.
- 2024-12-20 first online, published, posted
- CrowdIT space (grant code 18183) NWO
DATA
- 3,114 bytesMD5:
0937cba8f87624136a33ed85522a0b20
README_lights_walkingexperiment.txt - 14,761 bytesMD5:
e8b19889cb8eabb517413b48e52ee206
passingpoints_total.csv - 149,831 bytesMD5:
e466d756d90ed8c0d19f51b91769fbc2
step_data.csv - 11,271,252 bytesMD5:
542eb42bc629e2e2c42f8454d92ca0b2
traj_clean.csv -
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