EFFECT OF ROAD GEOMETRY AND SPEED ON ROAD SAFFTY AND IDENTIFICATION OF HAZARDOUS ROAD SECTION (CASE STUDY ON THE WUKRO-ADIGRAT-ZALAMBESA ROAD

Abstract

In Ethiopia road traffic crashes are causing heavy loss of human and economic resources with the relatively low road network and motorization level. The risk is increasing with the increase in population, the road network expansion with little consideration of safety, and the increase in motorization with the vehicle fleet generally in poor conditions.This thesis deals with the most essential issue of road traffic accident related to geometric characteristics, flow and speed and identification of hazardous road section on the Eastern Tigray Zone (Wukro-Adigrat Zela'ambesa ) two lane road. The main objective of the study is to develop a prediction model for road traffic crashes occurring on a two lane road and to identify the hazardous road section.The study area has a total length of 96 km. Data such as crash data, traffic flow data, speed data, roadway characteristics and road geometry data was collected from offices and the site. Two models were developed one for the geometric characteristics of the road and flow model, the second for the speed model. The statistical analyses were performed using statistical software package SPSS version 20. The Generalized Linear Model (GLM) with Poisson regression and Negative Binomial (NB) the error structure was used to estimate the model parameters. From the two models the negative binomial model was fit to the data. The results show that number of vertical curve, number of vertical grade, no of horizontal curve, speed, shoulder width, were found to be statistically significant explanatory variables (p < 0.05) for crash involvement and when the crash rate relates to the speed it is statically significant for the crash rate. After calibration the model was validated using data from similar road on Mekelle-AbiAdi road. And the result has shown it is not validate on the similar road. For the identification of hazardous road section Empirical bays method was used. Results indicate that from the total 96 km road sections 25 sections were highly prone to accidents with PI EB values. Possible solutions are using traffic signs, user awareness campaigns, policy revisions, and permanent geometry and pavement modifications.