Traffic accidents: Random or pattern occurrence

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44994575%3A_____%2F15%3A%230001614" target="_blank" >RIV/44994575:_____/15:#0001614 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Traffic accidents: Random or pattern occurrence

Popis výsledku v původním jazyce

Two primary types of traffic accident causes can be identified. The first cause is connected to local conditions of the road infrastructure. The second cause is global and includes factors such as driver behaviour, vehicle state and weather conditions. While the global causes can increase the probability of traffic accident occurrences anywhere within road network, the local factors are tightly bound to a specific place. We studied patterns of traffic accidents which occurred in the Czech Republic during the period 2009 ? 2013. We used the novel KDE+ method which determines and classifies the significant clusters according to their strength. The results enabled us to effectively localize the most dangerous places within the road network. The overall length of clusters covers only a short part (approximately 2.8 %) of the entire road network. We also developed the KDE+ software, which is a programmed version of the KDE+ method, for the effective hotspots of traffic accidents identificat

Název v anglickém jazyce

Traffic accidents: Random or pattern occurrence

Popis výsledku anglicky

Two primary types of traffic accident causes can be identified. The first cause is connected to local conditions of the road infrastructure. The second cause is global and includes factors such as driver behaviour, vehicle state and weather conditions. While the global causes can increase the probability of traffic accident occurrences anywhere within road network, the local factors are tightly bound to a specific place. We studied patterns of traffic accidents which occurred in the Czech Republic during the period 2009 ? 2013. We used the novel KDE+ method which determines and classifies the significant clusters according to their strength. The results enabled us to effectively localize the most dangerous places within the road network. The overall length of clusters covers only a short part (approximately 2.8 %) of the entire road network. We also developed the KDE+ software, which is a programmed version of the KDE+ method, for the effective hotspots of traffic accidents identificat

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/ED2.1.00%2F03.0064" target="_blank" >ED2.1.00/03.0064: Dopravní VaV centrum</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Safety and Reliability of Complex Engineered Systems

ISBN

978-1-138-02879-1

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

3-6

Název nakladatele

Taylor & Francis Group

Místo vydání

London

Místo konání akce

Zurich

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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