Abstract
Introduction. The author's methods for modeling the level of danger of federal highways are considered. A method is proposed for ranking emergency situations caused by accidents in road transport, using color codes to indicate the level of danger. Research objective: to improve the efficiency of response to emergencies caused by accidents in road transport. Development of an algorithm for ranking emergencies caused by road transport accidents in order to develop an information and analytical decision support system responsible for predicting and responding to road transport accidents. Methods. To solve the decision-making problem in predicting emergencies caused by accidents in road transport, a method was used to determine criteria that can be used to accurately determine whether the presented object belongs to the corresponding class. To achieve the goal of reducing the trend of increasing accidents in road transport and timely response to these threats, it is proposed to rank the criteria, depending on the vulnerability of the road section and the presence of factors affecting traffic safety, according to hazard levels, indicating specific preventive measures for the authorities. Results and discussion. A method is presented for determining criteria that can be used to accurately determine whether the presented object belongs to the corresponding class. This method allows you to rank sections of federal highways according to hazard levels. Findings. The developed algorithm for predicting the level of danger on sections of federal highways will reduce the growth of emergencies caused by accidents on vehicles, thanks to the timely implementation of preventive measures to prevent traffic accidents on dangerous sections of roads. Based on this algorithm, it is possible to develop an information and analytical decision support system for the senior operational duty control center in crisis situations and other officials responsible for predicting and responding to accidents in road transport. Keywords: emergency forecasting, road transport accidents, traffic accident, decision support system, federal highways.
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