SEMI-STOCHASTIC MIXTURE MODEL FOR PREDICTING THE RATE OF ROAD CARNAGES IN KENYA

In this paper we consider the problem of modeling and predicting the rate of road carnage in Kenya inthe presence of randomly changing road conditions. In the literature review, accident prediction ratemodels are typically regression models and discrete time series models. We study such models andexamine their strengths and weaknesses and propose a Semi-stochastic Mixture Model to describethe relation between the highway accidents and the road environment dynamics.The aim of theresearch paper is to propose a model that captures both the deterministic and stochastic nature ofroad parameters to explain the cause of high rate of road accidents in Kenya. We apply the proposedmodel to a simulated data set for the local condition. Our analysis from show that apart from annualaverage daily traffic (AADT), road curvature is an important component of road carnage. Keywords : Road system, Semi-stochastic mixture model, road curvature, road carnage,Simulation.