Sample Survey of Passenger Traffic by Analysing Wi-Fi Data in Moscow Transport Hub. Part 1

Author:

Alekseev N. Yu.1

Affiliation:

1. Sitronics Group

Abstract

In modern, rapidly developing cities of the world, building an urban transport model requires traffic data. The lack of those data does not allow making timely management decisions on distribution of passenger flows, namely within transport flows. Currently, there are various methods and systems for counting passenger flows, such as the manual staff counts, survey and counted ticketed entries methods, and various automated technology-based systems. However, those well-known methods have their drawbacks.For this reason, the task to search for alternative methods and data sources for the study of passenger flows remains relevant.This article is based on the updated results of the study recently conducted by the author during preparation of his master’s thesis. During the study and developing previous author’s papers, data on connections of passengers to Wi-Fi routers were chosen as a data source. Since this phase of the study was conducted on the territory of Moscow transport hub, in metro and on Moscow Central Diameters (MCD), where the cars are equipped with great number of Wi-Fi routers, with free connection and Internet access, it has increased the sample Wi-Fi data array significantly.The objective of the study was to study the possibility of processing Wi-Fi data obtained from Wi-Fi scanners as a passenger flow analysis tool.The study has revealed that, on average, up to 40% of passengers in metro and MCD cars on the studied lines use the WI-FI module turned on in their mobile devices.The results of the study have confirmed that Wi-Fi data can be used as a tool for passenger traffic analysis, but at the same time revealed the necessity to integrate them with other data sources, as well as the strong dependence of the result of Wi-Fi data processing on the technical features of the Wi-Fi scanner and its location in the vehicle during experiments. You can find the first part of the article in the issue.

Publisher

FSBEO HPE Moscow State University of Railway Engineering (MIIT)

Subject

General Medicine

Reference22 articles.

1. Pashina, A. S., Kravchuk, I. S. Innovations in the infrastructure of Moscow metro [Innovatsii v infrastructure Moskovskogo metropolitena. Sovremennoe sostoyanie, problemy i perspektivy razvitiya otraslevoi nauki]. In: Proceedings of the conference «Current state, problems and prospects for development of branch science». Moscow, Pero publ., 2019, pp. 330−335. [Electronic resource]: https://www.elibrary.ru/item.asp?id=39227779. Last accessed 10.04.2022.

2. Dolmatenya, Yu. V., Trandina, E. V. Features of the Metro as Area for the Organization and Development of Tourist Events. In: Topical problems of development of service sector [Aktualnie problem razvitiya sphery uslug]. Collection of scientific works, Vol. XIII. St. Petersburg State University of Economics, 2019, pp. 135–139. [Electronic resource]: https://www.elibrary.ru/item.asp?id=42476132. Last accessed 10.04.2022.

3. Podkhalyuzina, V. A. Analysis of passenger traffic in the Moscow ground public transport. Challenges of the global world. Vestnik IMTP, 2015, Iss. 2 (6), pp. 31−34. [Electronic resource]: https://www.elibrary.ru/item.asp?id=24245177. Last accessed 10.04.2022.

4. Alekseev, N. Yu., Zyuzin, P. V. Assessment of Applicability of Wi-Fi Analytics in Studies of Urban Public Transport Passenger Flow (Moscow Case Study). World of Transport and Transportation, 2021, Vol. 19, Iss. 3, pp. 196–208. DOI: https://doi.org/10.30932/1992-3252-2021-19-3-6.

5. Petrova, D. V. Modern approaches to the organisation of public transport passenger traffic monitoring in urban agglomerations. International Journal of Open Information Technologies, 2020, Vol. 8, Iss. 1, pp. 47−57. [Electronic resource]: https://www.elibrary.ru/item.asp?id=42340332. Last accessed 10.04.2022.

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