Ghana employs the Microcomputer Accident Analysis Package (MAAP 5) software which only provides basic synthesis of accident information for analysis. However, recent studies on accidents have centered on the use of models to describe data, explain and also forecast the phenomenon. This study sought to develop a prediction model for pedestrian accidents on trunk roads. Following the delineation of four (4) trunk roads into one hundred and sixty-one (161) road sections made up of ninety-nine (99) settlements and sixty-two (62) non-settlement units, data was collected on accidents and risk factors representing variables extracted from pedestrian and vehicular traffic, road and environment-related features of the study road sections. Using the Negative Binomial error structure within the Generalized Linear Model framework, a basic (flow-based) model was formulated based on accident data and exposure variables (road section, vehicle and pedestrian flows). Incremental addition of relevant explanatory variables further expanded the basic model into a comprehensive model. The developed models were then validated and tested using appropriate statistical measures. Findings indicate that the main risk factors influencing pedestrian accidents on trunk roads are predominantly flow variables, namely; daily pedestrian flow and total vehicle kilometers driven. To ameliorate the incidence of pedestrian accidents require the segregation of vehicles and pedestrian, traffic calming measures and land use control within settlements featuring trunk roads.
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