Context . Wildlife–vehicle collisions (WVC) are one of the major risk factors for the safety of drivers, as well as a great danger to wildlife that moves through the territory. In recent decades, given the growth of these accidents, some researches emerged to understand what are the main causes of this phenomenon and find the best solutions for implementation and try to solve this problem.
Aims . The aim of the present study was to analyse the road and traffic characteristics of road segments with a high occurrence of WVC in north-western Spain, specifically, the collisions with wild ungulates (roe deer and wild boar).
Methods . A nearest-neighbour analysis was used to analyse the spatial distribution of the WVC spots, and so as to identify these hotspots of accidents, we performed a hotspot analysis using the routine nearest-neighbour hierarchical cluster. Then, we calculated the WVC density of each road segment (KP). The existence of differences in the values of variables between high and low accident densities was analysed using a Mann–Whitney U-test for the continuous variables, and a χ2-test for the categorical ones. Then, multiple logistic regression analysis was used to identify which variables could predict the existence of KPs with a high density of WVC.
Key results . Our results showed that the daily traffic volume, the width of the road, the number of lanes and speed limit affect whether a particular road marker has a high or low density of WVC.
Conclusions . We conclude that high WVC is frequently characterised by wider lanes and shoulders, as well as gentler slopes, whereas in the sections with narrower roads and a shorter curvature radius, there are some conditions (low visibility and speed reduction) that reduce the probability of having an accident with ungulates. However, the speed at which it is possible to drive on a given road section is closely related to the occurrence of WVC.
Implications . These findings emphasise the importance of including mitigation measures in the decision-making when planning and designing infrastructure.
