Abstract
Organizing the effective operation of urban public transport and planning the development of transport infrastructure requires predicting the volume of passenger traffic. In particular, it needs to predict the volume of passenger departures from stopping points, which depends on a large number of different factors, such as the population density near the stopping point, the types of transport departing from it, the number of routes passing through it, etc. In this article, we propose modeling outgoing passenger traffic based on a regression approach. To test the approach and determine the most appropriate specifications for regression equations, data on passenger boarding volumes at bus stops in Ekaterinburg, as well as open data from the database of apartment buildings, were used.
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