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Report numberRA-2013-006
TitleNetwork Safety Management
SubtitleA ranking of dangerous road segments of the TEN-T network in Flanders
AuthorsKurt Van Hout
Stijn Daniels
Tom Brijs
Elke Hermans
Geert Wets
Published byPolicy Research Centre for Traffic Safety 2012-2015
Number of pages54
Date16/07/2013
ISBN
Document languageDutch
Partner(s)Universiteit Hasselt
Work packageWP2: Risk analysis
Summary

The European directive 2008/96/EC on road infrastructure safety management involves the implementation of procedures relating to road safety impact assessment, road safety audits, the management of road network safety and safety inspections by the member states. This Directive was implemented into Flemish legislation by the Decision of the Flemish Government (dd. 3/2/2012) on the execution of the decree of june 17, 2011 on road infrastructure safety management, published in the Belgian Government Gazette on April 19, 2012.

 

This legislation imposes, among others, a classification of road segments with a high number of accidents and a classification of the road safety of the road network. As the first classification is targeted at the number of crashes, the second is targeted at the potential to improve road safety. The application of the decree is limited to those road segments that make up the trans-European road network (TEN-T), which in Flanders resembles mainly the highway network.

 

In this report – as the first step in the process of road safety management – a screening of the TEN-T road network in the Flanders region is carried out. The goal of this screening is the selection of a relatively small group of road segments that afterwards can be subjected to an in-depth investigation that will allow proposing appropriate measures. The network screening as such is therefore not an ultimate goal, but merely the first step to ameliorate the road safety on dangerous locations.

 

The Empirical Bayes (EB) method is considered the state-of-the-art approach in identifying dangerous road segments in scientific literature. Therefore we will be using this approach in this study. The EB approach offers a solution to 2 problems when estimating the number of crashes: it provides for regression to the mean and it improves the accuracy of the estimation by calculating it as a weighted average of the actual number of crashes and the normal number of crashes where the latter is based on the outcomes of a risk model.

 

Such risk model was built for Flemish highways based on the accident and traffic intensity data for the period 2008-2010. The model describes the number of crashes as a function of a number of explanatory variables. In this case the length of the segment (L) and traffic intensity (I) were withheld as explanatory variables. The normal number of crashes μ can be calculated by:

 

μ = e-17,0652 * L0,9532 * I1,0266

 

The number of crashes on Flemish highways increases approximately proportionally with both segment length and traffic intensity since neither of the coefficients significantly differs from 1.

 

Road safety can be expressed in different manners. Therefore 4 indicators were used to construct 4 different rankings: number of crashes, crash density, crash risk and the safety potential (expected-normal number of crashes, expressed per km road length). As mentioned before segment length and traffic intensity are major influential factors. To correct for this and to compare the segments on a more equal basis we only compare the rankings based on crash density, crash risk and safety potential per km. The ranking based on crash numbers is added for completeness and for comparison with the ranking according to the – still fashionable but by scientific literature considered naïve – method based on actual crash numbers.

 

The results show that significant differences exist between the rankings. Not unexpected because the safety indicators that were used illustrate each a different aspect of road safety. The top 25 of the ranking based on crash numbers contains, as expected, mainly longer segments with (relatively) high traffic intensities. The ranking based on crash density gives shorter, but on average busier segments in the top 25. The ranking based on crash risk picks short segments with lower traffic intensities that are often located near on- and off-ramps. Lane changes and manoeuvres are frequent at these locations. The ranking based on safety potential chooses segments that are situated in between those of the 2 previous in terms of average length and intensity. Additional research shows that the ranking based on safety potential depends on the model form that is used to calculate the normal number of crashes for comparable segments.

 

The 3 relevant rankings (based on density, risk and potential; the ranking based on accident numbers is not included in the comparison because this indicator, contrary to the 3 previous, is not normalized on length) contain combined 37 different road segments. 15 segments show up in each of them. These 15 road segments are therefore suggested to be the first to be subjected to an in-depth analysis and inspection to clarify the accident causes that will help define remedial measures.

 

Following road segments are involved:

  • R1, Borgerhout to Antwerp-East
  • R1, Berchem to Borgerhout
  • R1, Borgerhout to Berchem
  • A14, Gent-Centre to Gentbrugge
  • A10, Gent-St.-Pieters to Zwijnaarde
  • R1, node Antwerp-East (Ring 1)
  • A13, Antwerp-East to Wommelgem.
  • R1, node Antwerp-East (Ring 2)
  • A1, complex Mechelen-North (direction Brussels)
  • A13, complex Massenhoven (direction Antwerp)
  • A3, complex Bertem (direction Liège)
  • R1, Linkeroever to Antwerp-Centre
  • A10, complex Erpe-Mere (direction Brussels).
  • R1, Berchem tot Antwerpen-Zuid
  • A3, Bertem tot Heverlee
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The Policy Research Centre for Traffic Safety carries out policy relevant scientific research under the authority of the Flemish Government. The Centre is the result of a

cooperation between Hasselt University, KU Leuven and VITO, the Flemish Institute for Technological Research.

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