FORECASTING PASSENGER TRAFFIC BASED ON STRUCTURE IDENTIFICATION OF NON-STATIONARY TIME SERIES

Authors

  • V. Vdovychenko Kharkiv National Automobile and Highway University
  • I. Ivanov Kharkiv National Automobile and Highway University
  • M. Vasyliev Kharkiv National Automobile and Highway University

DOI:

https://doi.org/10.33042/2522-1809-2022-3-170-307-313

Keywords:

volume of passenger traffic, time series, connections, transport service.

Abstract

The article proposes to consider the change in the volume of passenger traffic as non-stationary time series which is characterized by the presence of transients moments that lead to a significant change in the overall trend over time. Studies of changes in demand for passenger traffic in suburban service on bus routes of Cherkasy region in 2019–2021 showed that in the period up to 2020, the daily amount of presented demand on weekdays ranged from 4.1 thousand to 6.4 thousand passengers, and on the second half of 2020, the volume of demand decreased due to applying quarantine restrictions in 1.9–2.1 times (up to 2.1 thousand to 4.1 thousand passengers). Based on the analysis of fluctuations in the actual volume of traffic, the structural and logical inter-component relationship of the formation of demand for transportation was identified, which consists of the allocation of the main groups of transport classes forming the volume of passengers. By adapting the methodological provisions of singular spectral analysis, the main stages of the procedure for identifying the elemental structure of the non-stationary time series of changes in the volume of transportation have been formalized. Based on the analysis of the preconditions for the emergence of transients information on demand for passenger traffic allocated structure elements of the time series of the actual volume of passenger traffic that is based on the features and factors of its occurrence. Implementation of the procedure of using the singular spectral method analysis in the study of changes in the volume of passenger traffic is proposed to do by converting a one-dimensional time series into a matrix of elements that determine the trend, harmonic and random components demand. Based on the analysis of the materials of the passenger survey, it was established that the trend component of the change in demand in the Cherkasy – Smila connection contains two types of labor movements: permanent nature of formation and temporary. For the studied combination during 2019–2021, the share of worker transfers with a permanent character increased from 46.5% to 53.1%, with temporary character – decreased by 30.2% to 20.3%, and the harmonic component - increased from 11.5% to 15.3%, and the random component - remained stable within 11.9% to 11.2%. Based on the synthesis of predicted values of time components series for the connection Cherkasy – Smila found that in terms of implementation positive development scenario, there is a tendency to gradual short-term growth in traffic by 3.5%.

Author Biographies

V. Vdovychenko, Kharkiv National Automobile and Highway University

Doctor of Engineering, Professor

I. Ivanov, Kharkiv National Automobile and Highway University

PhD, Doctoral Student

M. Vasyliev, Kharkiv National Automobile and Highway University

PhD Student

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Published

2022-06-24

How to Cite

Vdovychenko В., Ivanov І., & Vasyliev М. (2022). FORECASTING PASSENGER TRAFFIC BASED ON STRUCTURE IDENTIFICATION OF NON-STATIONARY TIME SERIES. Municipal Economy of Cities, 3(170), 307–313. https://doi.org/10.33042/2522-1809-2022-3-170-307-313