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Statements

Subject Item
n2:RIV%2F44994575%3A_____%2F13%3A%230001097%21RIV14-MSM-44994575
rdf:type
n16:Vysledek skos:Concept
dcterms:description
The first step of the road safety management cycle is the identification of hazardous road locations. Traditionally, the identification criterion was recorded accident frequency or rate; however, it has tended to omit the significant influence of natural fluctuation known as regression to the mean. Using the expected number of accidents and empirical Bayes adjustment is the recommended solution; see e. g. Hauer (1997). This number is calculated with the use of an accident prediction model, taking into account several explanatory factors and controlling for potential confounding variables at the same time. An accident prediction model for the regional rural road network was developed for the purpose of this study. The whole 2nd class road network in one of the Czech regions (South Moravia) was used. This network is used as a traffic connection between towns and larger territorial units in the region. The resulting expected accident frequency was further adjusted by the empirical Bayes estimate (Hauer et al., 2002). The empirical Bayes estimate was used as a criterion for the ranking of hazardous road locations producing the list using top 5% as a threshold. At the same time, the ranking was performed using the Czech traditional criterion of recorded accident frequency, resulting in another list. This way three pairs of lists were developed for three time periods (2007 - 2009, 2008 - 2010 and 2009 - 2011). The paper discusses the results of this comparison of hazardous road location lists. In the end, conclusions about the differences are made. Recommendations are provided with regards to using the hazardous road locations identification based on recorded or expected accident frequency. The first step of the road safety management cycle is the identification of hazardous road locations. Traditionally, the identification criterion was recorded accident frequency or rate; however, it has tended to omit the significant influence of natural fluctuation known as regression to the mean. Using the expected number of accidents and empirical Bayes adjustment is the recommended solution; see e. g. Hauer (1997). This number is calculated with the use of an accident prediction model, taking into account several explanatory factors and controlling for potential confounding variables at the same time. An accident prediction model for the regional rural road network was developed for the purpose of this study. The whole 2nd class road network in one of the Czech regions (South Moravia) was used. This network is used as a traffic connection between towns and larger territorial units in the region. The resulting expected accident frequency was further adjusted by the empirical Bayes estimate (Hauer et al., 2002). The empirical Bayes estimate was used as a criterion for the ranking of hazardous road locations producing the list using top 5% as a threshold. At the same time, the ranking was performed using the Czech traditional criterion of recorded accident frequency, resulting in another list. This way three pairs of lists were developed for three time periods (2007 - 2009, 2008 - 2010 and 2009 - 2011). The paper discusses the results of this comparison of hazardous road location lists. In the end, conclusions about the differences are made. Recommendations are provided with regards to using the hazardous road locations identification based on recorded or expected accident frequency.
dcterms:title
A Comparative Analysis of Identification of Hazardous Locations in Regional Rural Road Network A Comparative Analysis of Identification of Hazardous Locations in Regional Rural Road Network
skos:prefLabel
A Comparative Analysis of Identification of Hazardous Locations in Regional Rural Road Network A Comparative Analysis of Identification of Hazardous Locations in Regional Rural Road Network
skos:notation
RIV/44994575:_____/13:#0001097!RIV14-MSM-44994575
n16:predkladatel
n17:ico%3A44994575
n4:aktivita
n8:P
n4:aktivity
P(ED2.1.00/03.0064), P(VG20112015013)
n4:dodaniDat
n15:2014
n4:domaciTvurceVysledku
n12:4587634 n12:1165100 n12:3863638
n4:druhVysledku
n11:D
n4:duvernostUdaju
n19:S
n4:entitaPredkladatele
n18:predkladatel
n4:idSjednocenehoVysledku
58482
n4:idVysledku
RIV/44994575:_____/13:#0001097
n4:jazykVysledku
n13:eng
n4:klicovaSlova
hazardous road locations; accident prediction model; empirical Bayes; regional roads; rural roads
n4:klicoveSlovo
n5:empirical%20Bayes n5:accident%20prediction%20model n5:hazardous%20road%20locations n5:rural%20roads n5:regional%20roads
n4:kontrolniKodProRIV
[0449206AB8D2]
n4:mistoKonaniAkce
Řím
n4:nazevZdroje
Road Safety and Simulation, International Conference RSS2013
n4:obor
n9:JO
n4:pocetDomacichTvurcuVysledku
3
n4:pocetTvurcuVysledku
3
n4:projekt
n7:ED2.1.00%2F03.0064 n7:VG20112015013
n4:rokUplatneniVysledku
n15:2013
n4:tvurceVysledku
Ambros, Jiří Valentová, Veronika Janoška, Zbyněk
n4:typAkce
n21:WRD
n4:zahajeniAkce
2013-10-23+02:00
s:numberOfPages
13
n14:hasPublisher
Neuveden
n10:isbn
978-88-548-6415-3