Identifying safe intersection design through unsupervised feature extraction from satellite imagery

@article{Wijnands2021IdentifyingSI,
  title={Identifying safe intersection design through unsupervised feature extraction from satellite imagery},
  author={Jasper S. Wijnands and Haifeng Zhao and Kerry A. Nice and Jason Thompson and Katherine Scully and Jingqiu Guo and Mark R. Stevenson},
  journal={Comput. Aided Civ. Infrastructure Eng.},
  year={2021},
  volume={36},
  pages={346-361}
}
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… Expand
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