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Statements

Subject Item
n2:RIV%2F44994575%3A_____%2F14%3A%230001348%21RIV15-MV0-44994575
rdf:type
n8: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 in the Czech Republic has been recorded crash frequency; however, it has tended to omit the important influence of natural variations known as regression to the mean. Using the expected number of crashes and empirical Bayes adjustment is the recommended solution. This number is calculated with the use of a crash prediction model, taking into account available explanatory factors and controlling for potentially confounding variables at the same time. The aim of this study was to compare both traditional and empirical Bayes approaches to identification of hazardous road locations. A crash prediction model for the regional rural road network was developed for the purpose of the study. The whole 2nd class road network in Czech region of South Moravia was used. The resulting expected injury crash frequency was further adjusted by the empirical Bayes estimate. The empirical Bayes estimate was used as a criterion for the ranking of hazardous road locations list. At the same time, another list was produced using the Czech traditional criterion of recorded crash frequency. Three pairs of lists were developed for three time periods (2007 – 2009, 2008 – 2010 and 2009 – 2011) and compared. The results showed that the predictions models with EB adjustment offered the results which were more stable in time compared to the traditional approach. This proves the potential suitability of empirical Bayes approach identification in the road safety management practice. The first step of the road safety management cycle is the identification of hazardous road locations. Traditionally, the identification criterion in the Czech Republic has been recorded crash frequency; however, it has tended to omit the important influence of natural variations known as regression to the mean. Using the expected number of crashes and empirical Bayes adjustment is the recommended solution. This number is calculated with the use of a crash prediction model, taking into account available explanatory factors and controlling for potentially confounding variables at the same time. The aim of this study was to compare both traditional and empirical Bayes approaches to identification of hazardous road locations. A crash prediction model for the regional rural road network was developed for the purpose of the study. The whole 2nd class road network in Czech region of South Moravia was used. The resulting expected injury crash frequency was further adjusted by the empirical Bayes estimate. The empirical Bayes estimate was used as a criterion for the ranking of hazardous road locations list. At the same time, another list was produced using the Czech traditional criterion of recorded crash frequency. Three pairs of lists were developed for three time periods (2007 – 2009, 2008 – 2010 and 2009 – 2011) and compared. The results showed that the predictions models with EB adjustment offered the results which were more stable in time compared to the traditional approach. This proves the potential suitability of empirical Bayes approach identification in the road safety management practice.
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:_____/14:#0001348!RIV15-MV0-44994575
n3:aktivita
n13:P
n3:aktivity
P(ED2.1.00/03.0064), P(VG20112015013)
n3:cisloPeriodika
34
n3:dodaniDat
n9:2015
n3:domaciTvurceVysledku
n10:4587634 n10:1165100 n10:3863638
n3:druhVysledku
n14:J
n3:duvernostUdaju
n11:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
588
n3:idVysledku
RIV/44994575:_____/14:#0001348
n3:jazykVysledku
n17:eng
n3:klicovaSlova
hazardous road location; crash prediction model; empirical Bayes; regional road; rural road
n3:klicoveSlovo
n5:regional%20road n5:crash%20prediction%20model n5:hazardous%20road%20location n5:rural%20road n5:empirical%20Bayes
n3:kodStatuVydavatele
IT - Italská republika
n3:kontrolniKodProRIV
[3C2FCF8C3B78]
n3:nazevZdroje
Advances in Transportation Studies
n3:obor
n12:JO
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n16:VG20112015013 n16:ED2.1.00%2F03.0064
n3:rokUplatneniVysledku
n9:2014
n3:tvurceVysledku
Valentová, Veronika Janoška, Zbyněk Ambros, Jiří
s:issn
1824-5463
s:numberOfPages
10