Highlights Landscape management in the vicinity of road can prevent the risk of collision. Mitigation measures related to landscape can has similar effectiveness as technical. Long-term and consistent monitoring of UVC is base for the mitigation measures.
Abstract The aim of this study was to identify landscape-related factors which could explain the concentration of traffic crashes with large ungulates in a forest environment. We worked with ungulate-vehicle collisions which took place on the Czech road network in the period 2014–2016 using the application Srazenazver.cz. With the KDE+ method, we chose the most significant hotspots with linkage to forest. For comparison we randomly selected control localities outside the KDE+ hotspots (i.e., with very low level of ungulate-vehicle collisions) but still in the forest area. A set of photos were taken at each hotspot and control locality (2 orthophotos and 4 driver views). Each set of images was then visually analysed by two independent evaluators. They did not know which set of images were for hotspots and which set of images were for control localities. From the point of view of the overall score, it cannot be said that these two groups of locations differ (p-value 0.3575, Kolmogorov-Smirnov test). The only attribute that demonstrated a difference between hotspots and randomly selected locations was “attractiveness (quality food source and cover) of the immediate vicinity of the transport infrastructure for the ungulates” (p-value 0.0016, Kolmogorov-Smirnov test). Results confirm the importance of landscape management in the surroundings of transport infrastructure, especially in its immediate vicinity. However, they did not confirm the possibility that the most dangerous locations from the UVC point of view could be identified on the basis of landscape composition and the overall state of vegetation around transport infrastructure.
Roadside vegetation influences clustering of ungulate vehicle collisions
Transportation Research Part D: Transport and Environment ; 73 ; 381-390
2019-01-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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