Abstract
Road safety engineering involves identifying influencing factors causing traffic crashes through accident data, carrying out detailed accident studies at different locations and implementing relevant remedial measures. This study was carried out to establish relationship between traffic accident characteristics (frequency and severity) and traffic and road design characteristics on a two-lane highway. Statistical models applied in traffic accident modeling are Poisson regression, Negative Binomial regression (NB), and Zero-Inflated Negative Binomial regression (ZINB).; Traffic flow and road geometry related variables were the independent variables of the models. Using Ilesha-Akure-Owo highway, South-West, Nigeria accident prediction models were developed on the basis of accident data obtained from Federal Road Safety Commission (FRSC) during a 4-year monitoring period extending between 2012 and 2015. Curve radius (CR), lane width (LW), shoulder factor (SF), access road (CHAR), average annual daily traffic (AADT), parentage heavy good vehicle (HGV) and traffic sign posted (TSP) were the identified effective factors on crash occurrence probability. Finally, a comparison of the three models developed proved the efficiency of ZINB models against traditional Poisson and NB models. Keywords— Traffic accidents. Single carriageway, accident prediction model, road geometric characteristics.
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