Supplementary material for the paper "Pedestrian Planet: What YouTube Driving from 233 Countries and Territories Teaches Us About the World"

DOI:10.4121/fe366b3a-5053-4b90-9f78-cc6d3056aaa2.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/fe366b3a-5053-4b90-9f78-cc6d3056aaa2

Datacite citation style

Alam, Md Shadab; Martens, Marieke; Bazilinskyy, Pavlo (2025): Supplementary material for the paper "Pedestrian Planet: What YouTube Driving from 233 Countries and Territories Teaches Us About the World". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/fe366b3a-5053-4b90-9f78-cc6d3056aaa2.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Pedestrian crossing behaviour varies globally. This study analyses dashcam footage from the CROWD dataset, covering 233 countries and territories, to examine crossing initiation time, crossing speed, and contextual variables, including detected vehicles, traffic mortality, GDP, and Gini coefficient. Qatar had the longest mean crossing initiation time (6.44~s), while China exhibited the fastest crossing speed (1.69~m/s). On average, worldwide, pedestrians exhibited a crossing initiation time of 3.18~s and crossing speed 1.20~m/s. Crossing speed and crossing initiation time are negatively correlated ($r = -0.18$), indicating slower crossings after longer hesitation. Crossing speed is negatively correlated with Gini coefficient ($r = -0.19$) and positively correlated with traffic mortality ($r = 0.18$). Similar crossing times in countries with different infrastructures, such as Bangladesh (3.42~s) and the Netherlands (3.40~s), underscore the complex interaction between infrastructure and behavioural adaptation. These findings emphasise the importance of culturally aware road design and the development of adaptive interfaces for vehicles.

History

  • 2025-09-12 first online, published, posted

Publisher

4TU.ResearchData

Format

csv; .py; .txt

Organizations

Eindhoven University of Technology, Department of Industrial Design

DATA

Files (1)