
Analyzing data on public transport network structure (case of Volgograd)
Author(s) -
T.P. Ogar,
И. В. Степанченко,
Е. Г. Крушель,
Alexander Eduardovich Panfilov,
И. М. Харитонов
Publication year - 2022
Publication title -
vestnik astrahanskogo gosudarstvennogo tehničeskogo universiteta. seriâ: upravlenie, vyčislitelʹnaâ tehnika i informatika
Language(s) - English
Resource type - Journals
eISSN - 2224-9761
pISSN - 2072-9502
DOI - 10.24143/2073-5529-2022-1-33-41
Subject(s) - public transport , vertex (graph theory) , graph , computer science , transport network , visualization , transport engineering , graph theory , population , data mining , theoretical computer science , engineering , mathematics , demography , combinatorics , sociology
The paper is focused on collecting and analyzing the data on the population density in the districts of
a megapolis was carried out. Each district is further divided into sections to improve the accuracy of the study. The analysis of data on the location of passenger public transport stops in residential areas and areas with socially significant objects was carried out. Visualization of the analysis results was performed by superimposing isochronous accessibility of the main objects of attracting passengers onto the map of the city. Using the algorithm of the minimum cstop of the way there have been found the points of destination in all the routes of the public transport network, which the passenger will be able to reach in 15 or 30 minutes. The route network is presented as a graph, whose vertices are public transport stops. The weights of the graph correspond to the travel time from one stop to another. The shortest paths between all vertices of the graph have been found. The Floyd-Warshell algorithm is selected for calculations. The obtained data are prepared for using them in the transport network model to solve a multi-criteria optimization problem. When adding a new vertex, it becomes possible to calculate a new route with minimal time cstops. Based on the results of the study, the initial data were prepared for constructing a model for generating data on the passenger traffic of urban land transport.