Science and Transport Progress
Published February 15, 2021 | Version v1
Journal article Open

Improvement of Technology of Passenger Intermodal Transportation with Involvement of Railway Transport in the Conditions of Tourism Development

Creators

  • 1. Ukrainian State University of Railway Transport, Ukraine

Description

Purpose. The main purpose of the authors is to define and methodically substantiate the ways to increase the efficiency of intermodal passenger transportations with the involvement of high-speed trains as an auxiliary mode of transport in terms of sea and river tourism. Methodology. In the process of research the following was used: the method of factor analysis – to determine the factors influencing the attractiveness of tourist travel using high-speed trains as ancillary transport; method of skipping stops – to increase the efficiency of using high-speed trains as an auxiliary mode of transport when making tourist trips; methods of construction and training of generative-adversarial networks for the formation of model of passenger flows forecasting, on the basis of historical data of multivariate time series; method of genetic algorithms – to optimize the model of mixed-integer programming, which allows obtaining the optimal scheme of high-speed trains on the line. Findings. In order to preserve the attractiveness of tourist travels and increase the route speed of trains, it is proposed to improve the technology of planning their work based on the method of skipping stops. A mathematical model of mixed-integer programming has been formed, which simultaneously provides the attractiveness of tourist travel and profitability for railway operators. To prepare the initial data, a method for forecasting passenger flows based on multivariate time series has been developed. The optimization procedure of the generated model was implemented in the form of software in the Matlab language. Originality. The method of skipping stops, which was first used to improve the technology of intermodal passenger traffic, was further developed in the work. An original method for predicting passenger flows based on multivariate time series using a modern model of generative-competitive neural networks is proposed. Practical value. The obtained results are aimed at improving the methodological approaches to the formation of modern technologies of intermodal passenger transportation and the realization of the potential of high-speed rail transportations as a basis for the comprehensive development of tourism.

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