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Weather conditions have both direct and indirect effects on road traffic. On the one hand, precipitation heavily influences road traction as well as vehicle visibility, and on the other hand, medical meteorology phenomena – for example weather fronts – have a great effect on the driving ability and accuracy of drivers. Weather fronts – through their physiological effects – may cause the deterioration of human reaction times, and therefore increase the risk of accidents’ occurrence in unexpected and hazardous traffic situations that would require quick intervention of drivers. In this article, our research regarding the relation between weather fronts and traffic accidents as well as between local meteorological parameters and weather fronts is presented. In this article, a crowdsourcing-based methodology is presented, that is supported by a database, which is assembled using data that is far more heterogeneous with regard to acquisition frequency and quality, than those available previously. Using such a database, a driver aiding system can be created for use in cars currently supporting lower levels of autonomy. Such driver assistance systems would be capable of informing or, in a given situation, indirectly decrease the likelihood of the development of an emergency by warning the driver. Key-words: weather fronts, traffic accidents, accident statistics, local weather and weather fronts, crowdsourcing, road safety, Hungary

Towards an intelligent traffic control system using crowdsourcing, based on combined evaluation of weather information and accident statistics