Road Traffic Crashes on Rural Highways in the Ashanti Region of Ghana
Factors Relating to Road Geometric Design and Traffic Data Characteristics
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Crash Prediction Models (CPMs) have been used in the developed countries as a useful tool by road Engineers and Planners. There is however a limited literature on the prediction of road traffic crashes in Low and Middle Income Countries (LMICs) including Ghana. This book studies crash data and develops a prediction model for injury road traffic crashes occurring on rural highways in the Ashanti Region of Ghana. Data was collected from rural highway sections of varying lengths. Data collected for each segment comprised injury crash data, traffic flow and speed data, and roadway characteristics ...
Crash Prediction Models (CPMs) have been used in the developed countries as a useful tool by road Engineers and Planners. There is however a limited literature on the prediction of road traffic crashes in Low and Middle Income Countries (LMICs) including Ghana. This book studies crash data and develops a prediction model for injury road traffic crashes occurring on rural highways in the Ashanti Region of Ghana. Data was collected from rural highway sections of varying lengths. Data collected for each segment comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM) with Negative Binomial (NB) error structure was used to estimate the model parameters. Crash rates were initially related to each explanatory variable in turn to ascertain if any relationships existed. Two types of models, the 'core' model which included key exposure variables only and the 'full' model which included a wider range ofvariables were developed and interpretations given. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads.
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