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The racial composition of road users, traffic citations, and police stops.

Wenfei XuMichael J SmartNebiyou TilahunSajad AskariZachary DennisHoupu LiDavid M Levinson
Published in: Proceedings of the National Academy of Sciences of the United States of America (2024)
This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.
Keyphrases
  • african american
  • healthcare
  • air pollution
  • public health
  • electronic health record
  • machine learning
  • deep learning
  • high throughput
  • mass spectrometry
  • high speed