The KDE+ software: a tool for effective identification and ranking of animal-vehicle collision hotspots along networks
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44994575%3A_____%2F16%3AN0000076" target="_blank" >RIV/44994575:_____/16:N0000076 - isvavai.cz</a>
Výsledek na webu
<a href="http://link.springer.com/article/10.1007/s10980-015-0265-6" target="_blank" >http://link.springer.com/article/10.1007/s10980-015-0265-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10980-015-0265-6" target="_blank" >10.1007/s10980-015-0265-6</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
The KDE+ software: a tool for effective identification and ranking of animal-vehicle collision hotspots along networks
Popis výsledku v původním jazyce
Objective identification of locations on transportation networks, where animal-vehicle collisions (AVC) occur more frequently than expected (hotspots), is an important step for the effective application of mitigation measures.We introduce the KDE+ software which is a programmed version of the KDE+ method for effective identification of traffic accident hotspots. The software can be used in order to analyze animal-vehicle collision data. The KDE+ method is based on principles of Kernel Density Estimation (KDE). The symbol ‘+’ indicates that the method allows for the objective selection of significant clusters and for the ranking of the hotspots. It is also simultaneously applicable to an unlimited number of road segments. We applied the KDE+ method to the entire Czech road network. The hotspots were ranked according to their significance. The resulting hotspots represent a short overall road length which should require a more detailed assessment in the field. The 100 most important clusters of AVC represent, for example, only 19.7 km of the entire road network (37,469 km). We present an objective method for hotspots identification which can be used for AVC data. This method is unique because it determines the significance level of hotspots in an objective way. The prioritization of hotspots allows a transportation manager to effectively allocate resources to a feasible number of identified hotspots. We describe the software, data preparation and present the KDE+ application to AVC data.
Název v anglickém jazyce
The KDE+ software: a tool for effective identification and ranking of animal-vehicle collision hotspots along networks
Popis výsledku anglicky
Objective identification of locations on transportation networks, where animal-vehicle collisions (AVC) occur more frequently than expected (hotspots), is an important step for the effective application of mitigation measures.We introduce the KDE+ software which is a programmed version of the KDE+ method for effective identification of traffic accident hotspots. The software can be used in order to analyze animal-vehicle collision data. The KDE+ method is based on principles of Kernel Density Estimation (KDE). The symbol ‘+’ indicates that the method allows for the objective selection of significant clusters and for the ranking of the hotspots. It is also simultaneously applicable to an unlimited number of road segments. We applied the KDE+ method to the entire Czech road network. The hotspots were ranked according to their significance. The resulting hotspots represent a short overall road length which should require a more detailed assessment in the field. The 100 most important clusters of AVC represent, for example, only 19.7 km of the entire road network (37,469 km). We present an objective method for hotspots identification which can be used for AVC data. This method is unique because it determines the significance level of hotspots in an objective way. The prioritization of hotspots allows a transportation manager to effectively allocate resources to a feasible number of identified hotspots. We describe the software, data preparation and present the KDE+ application to AVC data.
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
JO - Pozemní dopravní systémy a zařízení
OECD FORD obor
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Návaznosti výsledku
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
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Landscape Ecology
ISSN
0921-2973
e-ISSN
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Svazek periodika
31
Číslo periodika v rámci svazku
2
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
7
Strana od-do
231–237
Kód UT WoS článku
000372318900003
EID výsledku v databázi Scopus
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