Salvatore Cafiso, Alessandro Di Graziano, Giuseppina Pappalardo - How to compare different national databases of HGV accidents to identify issues for safety improvements (Vol VIII, No 2)

Vilnius Gediminas Technical UniversityRiga Technical UniversityTallinn University of TechnologyBaltic Road Association

 

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ISSN 1822-427X print
ISSN 1822-4288 online
 

 

 
 

"The Baltic Journal of Road and Bridge Engineering"
Vilnius: Technika, 2013, Vol VIII, No 2, p. 124-132


Salvatore Cafiso, Alessandro Di Graziano, Giuseppina Pappalardo

How to compare different national databases of HGV accidents to identify issues for safety improvements

DOI: 10.3846/bjrbe.2013.16
 
The objective of this paper is to present a methodological approach and a case study for an international comparison of accident data coming from different national databases. Safety levels and the characteristics of severe crashes involving heavy goods vehicles in different European countries (Italy, France, Germany, Great Britain and Spain) are analysed. Considering that all the countries involved have different inventory structures for the variables reported in their national accident databases, the taxonomy theory was used in order to create a comparable structure for the database used in the analysis. The taxonomy is non-exclusive and the codes are categorical, denoting the absence or presence of a certain feature. Based on the data available in each national database the five European Union databases of accidents involving heavy goods vehicles have been referenced to only one, composed of 11 items (casualty class, injury number and severity, location, light conditions, road conditions, junction, vehicle type, driver age, driver gender, accident type and manoeuvres) , which capture common features of heavy goods vehicles accidents. A statistical analysis was carried out in order to highlight significant differences in the proportions of heavy goods vehicles crash categories.
 
Keywords: accident data, heavy goods vehicle, database, taxonomy, statistical analysis, proportion method.

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