Spatio-temporal modeling of traffic accidents incidence on urban road networks based on an explicit network triangulation

Traffic deaths and injuries are one of the major global public health concerns. The present study considers accident records in an urban environment to explore analyze spatial temporal incidence road traffic accidents. We propose a spatio-temporal model provide predictions number collisions on any given segment, further generate risk map entire network. A Bayesian methodology using Integrated nested Laplace approximations with stochastic partial differential equations (SPDE) has been applied modeling process. As novelty, we have introduced SPDE network triangulation estimate autocorrelation restricted linear resulting maps information identify safe routes between source destination points, can be useful for prevention multi-disciplinary safety measures.