A Parametric Model for Accident Prediction Along Ado Ekiti – Ikole Ekiti Road, Ekiti State, Nigeria
Authors: Aderinola Olumuyiwa Samson 
Published: September 2020

Road Accident Prediction Models have been used in different countries as a useful tool by road engineers and planners to predict the safety levels of roads, given their potential for determining both the crash frequency occurrence and the degree severity of crashes. The research looked into developing a parametric model for predicting accidents at specific locations along Ado-Ekiti to Ikole-Ekiti road. The reconnaissance survey of the road and the identified accident vulnerable points along the road was carried out and the factors aiding the occurrence of accidents were isolated  as Spot speed [S],  Pavement condition [P], Condition of shoulder [C], Width of the road [W], Elevation(super)/cambering [E], Gradient [G] and Accident Vulnerability [AV] which form an acronym SPCWEG-AV. The spot speed in each of the locations was gotten by measuring a 60m length and noting the time vehicles covered the distance. The pavement and shoulder conditions were evaluated to determine their conditions. The width of the road, the elevation (super)/cambering and the gradient (horizontal) were measured using tape, twine and plumb. When the analyzed data from the investigated factors from the field were imputed into SPCWEG-AV Rating system and Weights, the index (which is a multiplication of the rating and weight) of each of the parameters was got and the addition of these indices produced what is called Total SPCWEG-AV Index (T.SPCWEG-AV.I) which defines the degree of accident vulnerability of the point in question. The higher the T.SPCWEG-AV.I is, the more vulnerable the location is. The results showed ten accident prone areas. They are Federal Government College, Ikole-Ekiti (Ch 0+000), NNPC, Ikole-Ekiti (Ch 3+200), Olokonla, Ikole-Ekiti (Ch 7+000), The Nigeria Police station, Oye-Ekiti (Ch 23+2000), Federal University, Oye-Ekiti (Ch 25+600), Ifaki-Ekiti (Ch 35+400), Iworoko-Ekiti (Ch 52+100), Iworoko market (Ch 53+100), Ekiti State  University, Iworoko-Ekiti (Ch 62+750), Ilasa-Ekiti (Ch 64+800). Federal University, Oye Ekiti, Oye Ekiti (Ch 25+600) and Ilasa-Ekiti (Ch 64+800) have the highest number of accidents each having 24 and 22 and also has highest T.SPCWEG—AV.I of 71 and 70 respectively and other points show similar pattern. It is therefore, reasonable to conclude that the parametric model can replicate and predict the occurrence of accidents along Ado-Ekiti to Ikole-Ekiti road and other roads with similar features. It is recommended that the results of researches should be put to use and that agencies in charge of roads should ensure proper design, supervision and construction and to make sure the roads are properly maintained. Road Accident Prediction Models have been used in different countries as a useful tool by road engineers and planners to predict the safety levels of roads, given their potential for determining both the crash frequency occurrence and the degree severity of crashes. The research looked into developing a parametric model for predicting accidents at specific locations along Ado-Ekiti to Ikole-Ekiti road. The reconnaissance survey of the road and the identified accident vulnerable points along the road was carried out and the factors aiding the occurrence of accidents were isolated  as Spot speed [S],  Pavement condition [P], Condition of shoulder [C], Width of the road [W], Elevation(super)/cambering [E], Gradient [G] and Accident Vulnerability [AV] which form an acronym SPCWEG-AV. The spot speed in each of the locations was gotten by measuring a 60m length and noting the time vehicles covered the distance. The pavement and shoulder conditions were evaluated to determine their conditions. The width of the road, the elevation (super)/cambering and the gradient (horizontal) were measured using tape, twine and plumb. When the analyzed data from the investigated factors from the field were imputed into SPCWEG-AV Rating system and Weights, the index (which is a multiplication of the rating and weight) of each of the parameters was got and the addition of these indices produced what is called Total SPCWEG-AV Index (T.SPCWEG-AV.I) which defines the degree of accident vulnerability of the point in question. The higher the T.SPCWEG-AV.I is, the more vulnerable the location is. The results showed ten accident prone areas. They are Federal Government College, Ikole-Ekiti (Ch 0+000), NNPC, Ikole-Ekiti (Ch 3+200), Olokonla, Ikole-Ekiti (Ch 7+000), The Nigeria Police station, Oye-Ekiti (Ch 23+2000), Federal University, Oye-Ekiti (Ch 25+600), Ifaki-Ekiti (Ch 35+400), Iworoko-Ekiti (Ch 52+100), Iworoko market (Ch 53+100), Ekiti State  University, Iworoko-Ekiti (Ch 62+750), Ilasa-Ekiti (Ch 64+800). Federal University, Oye Ekiti, Oye Ekiti (Ch 25+600) and Ilasa-Ekiti (Ch 64+800) have the highest number of accidents each having 24 and 22 and also has highest T.SPCWEG—AV.I of 71 and 70 respectively and other points show similar pattern. It is therefore, reasonable to conclude that the parametric model can replicate and predict the occurrence of accidents along Ado-Ekiti to Ikole-Ekiti road and other roads with similar features. It is recommended that the results of researches should be put to use and that agencies in charge of roads should ensure proper design, supervision and construction and to make sure the roads are properly maintained.