A geographically weighted regression to estimate the comprehensive cost of traffic crashes at a zonal level

2019/06/21 by Amin Mohamadi Hezaveh, Ramin Arvin, Christopher R. Cherry +1 · 8 citations
Engineering · Social Sciences · Medicine · #Traffic and Road Safety #Urban Transport and Accessibility #Injury Epidemiology and Prevention

paper · doi:10.1016/j.aap.2019.05.028

Citations

• Spatial analysis of fatal and injury crashes in Pennsylvania
• Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level

Cited by

• Spatial heterogeneity analysis of macro-level crashes using geographically weighted Poisson quantile regression
• Spatial analysis of moving-vehicle crashes and fixed-object crashes based on multi-scale geographically weighted regression
• Examining macro-level traffic crashes considering nonlinear and spatiotemporal spillover effects
• Measuring nonlinear relationships and spatial heterogeneity of influencing factors on traffic crash density using GeoXAI
• Measuring Nonlinear Relationships and Spatial Heterogeneity of Influencing Factors on Traffic Crash Density Using GeoXAI
• Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes. [europepmc]
• A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates. [europepmc]
• Examining spatial heterogeneity in built environment and climate factors affecting motorcycle crashes. [europepmc]