he object of this research is to develop one and only injury crash rate prediction model differentiable for three main crash types (head-on/side collisions, rear-end collisions, single-vehicle run-off-road crashes) observed on the selected Italian two-lane rural roads in low-volume conditions. An explanatory variable reflecting road “Surface” conditions (dry/wet), “Light” conditions (day/night), and geometric “Element” (tangent segment/circular curve) when the crash happened and referred to the police reports has been proposed within the safety performance function all together (Surface, Light and Element) with three other significant variables (lane width, horizontal curvature indicator and mean speed) as consistent factors to predict crashes and their degree of seriousness for different kind of crashes. Among different statistical approaches introduced in the past few years to deal with the data and methodological issues associated with crash-frequency data, a generalized estimating equation has been implemented to take into account over-dispersion of the crash data, with a negative binomial distribution additional log linkage equation. Residual plots were combined with the validation procedure and other goodness-of-fit measurements to determine the reliability of the results. Potential countermeasures have been proposed for the critical crash types surveyed on the studied roads; these countermeasures have had positive effects on the road segments where the serious crash types have occurred over an eight-year period of analysis.

Consistent approach to predictive modeling and countermeasure determination by crash type for low-volume roads

RUSSO, FRANCESCA;Biancardo, Salvatore Antonio;DELL'ACQUA, GIANLUCA
2014

Abstract

he object of this research is to develop one and only injury crash rate prediction model differentiable for three main crash types (head-on/side collisions, rear-end collisions, single-vehicle run-off-road crashes) observed on the selected Italian two-lane rural roads in low-volume conditions. An explanatory variable reflecting road “Surface” conditions (dry/wet), “Light” conditions (day/night), and geometric “Element” (tangent segment/circular curve) when the crash happened and referred to the police reports has been proposed within the safety performance function all together (Surface, Light and Element) with three other significant variables (lane width, horizontal curvature indicator and mean speed) as consistent factors to predict crashes and their degree of seriousness for different kind of crashes. Among different statistical approaches introduced in the past few years to deal with the data and methodological issues associated with crash-frequency data, a generalized estimating equation has been implemented to take into account over-dispersion of the crash data, with a negative binomial distribution additional log linkage equation. Residual plots were combined with the validation procedure and other goodness-of-fit measurements to determine the reliability of the results. Potential countermeasures have been proposed for the critical crash types surveyed on the studied roads; these countermeasures have had positive effects on the road segments where the serious crash types have occurred over an eight-year period of analysis.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/581654
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 13
  • ???jsp.display-item.citation.isi??? 14
social impact