Gianluca Dell’Acqua, Francesca Russo - Safety Performance Functions for Low-Volume Roads (Vol VI, No 4)

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, 2011, Vol VI, No 4, p. 225-234


Gianluca Dell’Acqua, Francesca Russo

Safety Performance Functions for Low-Volume Roads

DOI: 10.3846/bjrbe.2011.29
 
This paper analyzes roadway safety conditions using the network approach for a number of Italian roadways within the Province of Salerno. These roadways are characterized by low-volume conditions with a traffic flow of under 1000 vpd and they are situated partly on flat/rolling terrain covering 231.98 km and partly on mountainous terrain for 751.60 km. Since 2003, the Department of Transportation Engineering at the University of Naples has been conducting a large-scale research program based on crash data collected in Southern Italy. The research study presented here has been used to calibrate crash prediction models (CPMs) per kilometer per year. The coefficients of the CPMs are estimated using a non-linear multi-variable regression analysis utilizing the least – square method. In conclusion, two injurious crash prediction models were performed for two-lane rural roads located on flat/rolling area with a vertical grade of less than 6% and on mountainous terrain with a vertical grade of more than 6%. A residuals analysis was subsequently developed to assess the adjusted coefficient of determination and p-value for each assessable coefficient of the prediction model. CPMs are a useful tool for estimating the expected number of crashes occurring within the roads’ geometric components (intersections and road sections) as a function of infrastructural, environmental, and roadway features. Several procedures exist in the scientific literature to predict the number of crashes per kilometer per year. CPMs can also be used as a tool for safety improvement project prioritization.
 
Keywords: crashes, prediction models, road safety analysis.

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