North Carolina Department of Transportation
Research & Innovation Summit – 2020

Exploring pedestrian injury severities at pedestrian vehicle crash hotspots with an annual upward trend: a spatiotemporal analysis with latent class random parameter approach

Authors: Li Song, Wei (David) Fan, Yang Li, Peijie Wu
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With the increasing trend of pedestrian deaths among all traffic fatalities in the past decade, there is an urgent need for identifying and investigating hotspots of pedestrian-vehicle crashes with an upward trend.


  • Pedestrian-injury severities at pedestrian-vehicle crash hotspots with an annual upward trend are modeled.
  • Spatiotemporal trend analysis is used to identify spatial aggregated pedestrian-vehicle crash hotspots with annual uptrends.
  • Average nearest neighbor and spatial autocorrelation tests are used to give a reference for grid and neighborhood distances.
  • Latent class random parameter logit models are utilized to explore the heterogeneity within and between the subgroups.
  • Contributing factors to the pedestrian-injury severity are identified and analyzed with specific countermeasures.


For questions about this research, contact Li Song at