Development of Models for Crash Prediction and Collision Estimation- A Case Study for Hyderabad City

Road traffic crash is a cause of unnatural death and occupies fifth position in the world as per WHO records.Road crashes in India are alarming in situation while road safety is professionally lacking and politicallymissing. Hyderabad city, the capital of newly formed Telangana State occupies sixth position in occurrenceof road crashes. An attempt is made to understand which model is suitable for road crash prediction andestimation of collision type which is influencing road crashes in the city. A retrospective observational studywas conducted in the city of considering factors as roadway geometrics, traffic data and type of collision.Regression models like Multiple Linear Regression, Poisson Regression, Logit Model and MultinomialLogistic Model are considered for arriving crash prediction models. The suitability of model is based on R2and chi-square test. It is observed from the analysis through comparison of above model; Logit model has anR2 of 0.7 and is significant for chi-square test. Shoulder condition is an affecting factor for non-fatal crashesin the city which is ascertained by Logit model. Further analysis is also carried for arriving on type ofcollision influencing on road crashes. It is observed from the results that sideswipe is more significant forroad crashes.

Keywords:

Road crash , collision , regression models