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Detection of Geometric Risk Factors Affecting Head-On Collisions through Multiple Logistic Regression: Improving
Laura Cáceres1, Miguel A Fernández1, Alfonso Gordaliza1
1Departamento de Estadística e Investigación Operativa, Escuela de Ingenierías Industriales, Universidad de Valladolid, 47011 Valladolid, Spain.
Abstract:
This study aims to characterize locations on two-way rural roads where head-on crashes are more likely to occur, attending to geometric road design factors. For this purpose, a case-control study was carried out using multiple logistic regression models with variables related to road design parameters, considering several scenarios. The dataset corresponding to cases (places where crashes have occurred) was collected on Spanish "1+1" rural roads over a four-year period. The controls (places where no crashes have occurred in the period) where randomly selected through a specific ad hoc designed method. The obtained model identifies risk factors and allows the computation of the odds of a head-on collision on any specific road section: width of the pavement (when it exceeds 6 m), width of the lanes (for intermediate widths between 3.25 and 3.75 m) and tight curves (less than 250 m of radius) are identified as factors significantly increasing the odds of a crash, whereas a paved shoulder is a protective factor. The identified configurations on two-way rural roads may be susceptible to transformation into "2+1" roads to decrease the odds of a head-on crash, thus preventing possible serious injuries and enhancing transportation safety.
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