• DOI:10.1111/mice.12623
Corpus ID: 225103031

Identifying safe intersection design through unsupervised feature extraction from satellite imagery

@article{Wijnands2020IdentifyingSI,
  title={Identifying safe intersection design through unsupervised feature extraction from satellite imagery},
  author={Jasper S. Wijnands and Haifeng Zhao and Kerry A. Nice and J. Thompson and Katherine Scully and Jingqiu Guo and M. Stevenson},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.15343}
}

Jasper S. Wijnands, Haifeng Zhao, +4 authors M. Stevenson

Published 2020

Computer Science, Engineering

ArXiv

The World Health Organization has listed the design of safer intersections as a key intervention to reduce global road trauma. This article presents the first study to systematically analyze the design of all intersections in a large country, based on aerial imagery and deep learning. Approximately 900,000 satellite images were downloaded for all intersections in Australia and customized computer vision techniques emphasized the road infrastructure. A deep autoencoder extracted high-level… CONTINUE READING

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