Resumen
The study considers the process of response of emergency rescue units to emergencies and hazardous events occurring on the territory of a city with a population of more than one million people. It has been determined that the flow of calls to the departments of emergency rescue units has a certain structure, and their number correlates with the size of the total area of the housing stock of a settlement. This dependence was described by a polynomial trendline, for which an appropriate equation was composed to determine the number of calls that could be made to the emergency rescue units in the future. These data can also be used to determine the number of emergency vehicles that emergency response units must provide to carry out their intended operations effectively. A method of completing the departments of emergency rescue units with emergency vehicles is proposed taking into account the operational situation in the areas of their on-site visits, and it consists in performing four consecutive stages. The first stage involves the selection of the necessary factors on the basis of analysing statistical data that characterize the process of response of departments of emergency rescue units to various destructive events and the construction of a predictive model. The second stage involves the calculation of the indicator of the specific number of emergency vehicles per call, taking into account the different groups of call flows. The third stage involves determining the total number of emergency vehicles at the emergency rescue units of a settlement. As the mathematical models applied at this stage are based on the Poisson distribution law, there is a limitation in using the proposed method, entailing that the flow of calls must be Poisson. The fourth stage of the calculations involves the redistribution of the previously determined total number of emergency vehicles between the departments of the emergency rescue units, taking into account the peculiarities of the operational situation in the areas of their on-site visits.