Use of fuzzy sets in calculating the passenger capacity utilisation rate in conditions where it is impossible to collect objective data

The tasks of planning the organisation of passenger transportation by urban transport in modern Ukrainian conditions face new challenges, in particular, with the complexity or even impossibility of obtaining accurate input data for calculations. The research focused on solving the problem of unavailability of accurate and up-to-date data for calculating the organisation of passenger transportation by urban transport by using fuzzy logic methods. It is assumed that in conditions of limited time for conducting field research or the impact of military operations that cause dynamic changes in passenger traffic through migration processes and allow obtaining data by traditional methods, the proposed approach will allow performing calculations with minimal error. On the example of the coefficient of passenger capacity utilisation on the stage of a transport route, which directly depends on the indicator of passenger occupancy, the possibility of expanding the mathematical model of passenger transportation in urban transport using fuzzy logic approaches is considered. In particular, this refers to replacing input values with a subjective assessment of an outsider in the form of using fuzzy sets. The theoretical study showed the possibility and expediency of using fuzzy sets to solve the problem of the lack of objective input data in calculating the passenger capacity utilisation rate. The general principles of forming universes of fuzzy sets when they are used in mathematical models of the organisation of passenger transportation in urban transport to level the subjectivity of input data are determined. The requirements for the degree of overlap of the accumulated functions of belonging of fuzzy sets of the permissible level of subdivision are described, which can be used to reduce the error of calculations and, accordingly, the dimension of universes of fuzzy sets. The dependence of the tensor bit depth of the initial results on the quantitative indicator of stages on the public transport route, which can be used as a basis for analysing the complexity of calculations, is determined. The general principles of working with fuzzy sets in this mathematical model are shown using the example of calculating the passenger capacity utilisation rate. The study can be useful for city administrations, transport companies, software developers, transport logistics experts, and scientists to optimise public transport operations in the face of a lack of objective data and dynamic changes