# Revealing the Spatial Pattern of Weather-Related Road Traffic Crashes in Slovenia
###### Abstract  
Despite an improvement in worldwide numbers, road traffic crashes still cause social, psychological, and financial damage and cost most countries 3% of their gross domestic product. However, none of the current commercial or open-source navigation systems contain spatial information about road traffic crash hot spots. By developing an algorithm that can adequately predict such spatial patterns, we can bridge these still existing gaps in road traffic safety. To that end, geographically weighted regression and regression tree models were fitted with five uncorrelated (environmental and socioeconomic) road traffic crash predictor variables. Significant regional differences in adverse weather conditions were identified; Slovenia lies at the conjunction of different climatic zones characterized by differences in weather phenomena, which further modify traffic safety. Thus, more attention to speed limits, safety distance, and other vehicles entering and leaving the system could be expected. In order to further improve road safety and better implement globally sustainable development goals, studies with applicative solutions are urgently needed. Modern vehicle-to-vehicle communication technologies could soon support drivers with real-time traffic data and thus potentially prevent road network crashes. GIS; hot spot analysis; traffic safety; spatial modelling; weather patterns +
Footnote †: journal: Medical  
opposite pattern was observed in Athens (Greece), where the number of road traffic crashes was inversely proportional to precipitation [11]. A similar situation was found in Belgium as well, where more traffic crashes occurred in clear and sunny weather, while there were fewer in adverse weather conditions [12]. However, more attention should be paid to road traffic crashes in adverse weather conditions because these usually have a higher death toll [13; 14; 15]. At the EU level, in 2016, most crashes occurred in dry weather conditions (70.8%) followed by rain (9.4%), fog (1.4%), snow and hail (0.9%), and strong wind (0.4%) [9]. It has also been found that in rainy, cloudy, and snowy weather, more traffic crashes are caused by women, while in clear weather more crashes are caused by men [16]. Road traffic crashes should receive more attention, especially in Slovenia, since the share of people traveling by car is 86.3% [17], which ranks Slovenia second in the EU. In addition, the number of registered cars in Slovenia is constantly growing (1,165,000 in 2019, which is 2% more than in the previous year) [18]. With more frequent use of cars, the possibility of traffic crashes increases. In fact, the total number of traffic crashes in Slovenia in 2019 increased by 3% compared to 2018, and the number of fatalities increased by 12% [19]. Road safety is one of the fundamental characteristics of transport system quality. The latter is the responsibility of government institutions since they have an overview of transport activities and the means to plan measures. Collection and analysis of data on road traffic crashes in Slovenia is performed within the Sector for the Development and Coordination of Road Safety in the Slovenian Traffic Safety Agency, which operates within the Ministry of Infrastructure. Collecting data is the basis for planning and introducing preventive measures to increase traffic safety. In this context, geographic information system technology enables the implementation of various methods for studying spatial traffic patterns, such as the Bayesian method considering different distribution functions (Poisson, Poisson-gamma, Poisson-lognormal) [20]; hierarchical models [21]; and methods of spatial statistics, such as kernel density estimation [22], local Moran index [23], and the Getis-Ord G* statistics [24]. Moreover, combining machine-learning algorithms and geospatial models can provide applicable solutions to change complex patterns caused by human activity [25; 26].