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| rdf:type
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| 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. (en)
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| 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 (en)
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| 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 (en)
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| skos:notation
| - RIV/44994575:_____/13:#0001097!RIV14-MSM-44994575
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| http://linked.open...avai/predkladatel
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| http://linked.open...avai/riv/aktivita
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| http://linked.open...avai/riv/aktivity
| - P(ED2.1.00/03.0064), P(VG20112015013)
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| http://linked.open...vai/riv/dodaniDat
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| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
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| http://linked.open...iv/duvernostUdaju
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| http://linked.open...titaPredkladatele
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| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/44994575:_____/13:#0001097
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| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - hazardous road locations; accident prediction model; empirical Bayes; regional roads; rural roads (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...v/mistoKonaniAkce
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| http://linked.open...i/riv/nazevZdroje
| - Road Safety and Simulation, International Conference RSS2013
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| http://linked.open...in/vavai/riv/obor
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| http://linked.open...ichTvurcuVysledku
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| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...vavai/riv/projekt
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| http://linked.open...UplatneniVysledku
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| http://linked.open...iv/tvurceVysledku
| - Ambros, Jiří
- Janoška, Zbyněk
- Valentová, Veronika
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| http://linked.open...vavai/riv/typAkce
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| http://linked.open.../riv/zahajeniAkce
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| number of pages
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| http://purl.org/ne...btex#hasPublisher
| |
| https://schema.org/isbn
| |
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