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2019 | OriginalPaper | Chapter

Detection of the Patterns in the Daily Route Choices of the Urban Social Transport System Clients Based on the Decoupling of Passengers’ Preferences Between the Levels of Uncertainty

Authors : Elena Krushel, Ilya Stepanchenko, Alexander Panfilov, Tatyana Lyutaya

Published in: Creativity in Intelligent Technologies and Data Science

Publisher: Springer International Publishing

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Abstract

The ideas of data mining techniques were applied for the problem of municipal passengers transport system simulation and its results interpreting and generalization. The purpose of the presented work is to propose and justify the passengers flow model suitable for the detection of hidden patterns in the processes of flow forming with the application of the available sources for model identification. The patterns of the daily route choices detection are based on the decoupling of the general model between the sub-models according to the different levels of uncertainty of passengers intentions in route choice, and on the following joining of the computational results received for the sub-models. The availability of the approach was illustrated by the examples of the typical patterns in the destination stops choice and in hourly passengers’ flow from the departure stops. The model testing shows the high correlation of the simulated passengers’ flow with the results of the real observations.

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Krushel, E.G., Stepanchenko, I.V., Panfilov, A.E., Berisheva, E.D.: An experience of optimization approach application to improve the urban passenger transport structure. In: Kravets, A., Shcherbakov, M., Kultsova, M., Iijima, T. (eds.) JCKBSE 2014. CCIS, vol. 466, pp. 27–39. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11854-3_3CrossRef

Krushel, E.G., Stepanchenko, I.V., Panfilov, A.E., Haritonov, I.M., Berisheva, E.D.: Forecasting model of small city depopulation processes and possibilities of their prevention. In: Kravets, A., Shcherbakov, M., Kultsova, M., Iijima, T. (eds.) JCKBSE 2014. CCIS, vol. 466, pp. 446–456. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11854-3_38CrossRef

Horn, M.: An extended model and procedural framework for planning multi-modal passenger journeys. Transp. Res. Part B Methodol. 37, 641–660 (2003)CrossRef

Krushel, E.G., Stepanchenko, I.V., Panfilov, A.E.: The passengers’ turnout simulation for the urban transport system control decision-making process. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds.) CIT&DS 2017. CCIS, vol. 754, pp. 389–398. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65551-2_28CrossRef

Li, D., Yuan, J., Yan, K., Chen, L.: Monte Carlo simulation on effectiveness of forecast system for passengers up and down buses. In: 3RD International Symposium on Intelligent Information Technology Application, Nanchang, pp. 359–361 (2009)

Schelenz, T., Suescun, A., Wikstrom, L., Karlsson, M.: Passenger-centered design of future buses using agent-based simulation. In: Conference on Transport Research Arena, Athens, vol. 48, pp. 1662–1671 (2012)CrossRef

Bure, V.M., Mazalov, V.V., Plaksina, N.V.: Estimating passenger traffic characteristics in transport systems. Autom. Remote Control 76, 1673–1680 (2015)CrossRef

Li, W., Zhu, W.: A dynamic simulation model of passenger flow distribution on schedule-based rail transit networks with train delays. J. Traffic Transp. Eng. (English Edition) 3(4), 364–373 (2016)MathSciNetCrossRef

Chen, C., Ma, J., Susilo, Y., Liu, Y., Wang, M.: The promises of big data and small data for travel behavior (aka human mobility) analysis. Transp. Res. Part C Emerg. Technol. 68, 285–299 (2016)CrossRef

10.

Dijk, J.: Identifying activity-travel points from GPS-data with multiple moving windows. Comput. Environ. Urban Syst. 70, 84–101 (2018)CrossRef

11.

Bai, Y., Sun, Z., Zeng, B., Deng, J., Li, C.: A multi-pattern deep fusion model for short-term bus passenger flow forecasting. Appl. Soft Comput. 58, 669–680 (2017)CrossRef

12.

Dieleman, F.M., Dijst, M., Burghouwt, G.: Urban form and travel behaviour: micro-level household attributes and residential context. Urban Stud. 39, 507–527 (2002)CrossRef

13.

Kim, J., Corcoran, J., Papamanolis, M.: Route choice stickiness of public transport passengers: measuring habitual bus ridership behaviour using smart card data. Transp. Res. Part C Emerg. Technol. 83, 146–164 (2017)CrossRef

14.

Tao, S., Corcoran, J., Mateo-Babiano, I., Rohde, D.: Exploring bus rapid transit passenger travel behaviour using big data. Appl. Geogr. 53, 90–104 (2014)CrossRef

15.

Gonzalez, M.C., Hidalgo, C.A., Barabasi, A.-L.: Understanding individual human mobility patterns. Nature 453(5), 779–782 (2008)CrossRef

16.

Maghraoui, O.A., Vallet, F., Puchinger, J., Bernard, Y.: Modeling traveler experience for designing urban mobility systems. Des. Sci. 5, E7 (2019)CrossRef

17.

Calabrese, F., Diao, M., Lorenzo, G.D., Ferreira Jr., J., Ratti, C.: Understanding individual mobility patterns from urban sensing data: a mobile phone trace example. Transp. Res. Part C 26, 301–313 (2013)CrossRef

18.

Gärling, T., Axhausen, K.W.: Introduction: habitual travel choice. Transportation 30, 1–11 (2003)CrossRef

19.

Mühlenbein, H., Zinchenko, L., Kureichik, V., Mahnig, T.: Effective mutation rate for probabilistic evolutionary design of analogue electrical circuits. Appl. Soft Comput. 7(3), 1012–1018 (2007)CrossRef

Title: Detection of the Patterns in the Daily Route Choices of the Urban Social Transport System Clients Based on the Decoupling of Passengers’ Preferences Between the Levels of Uncertainty
Authors: Elena Krushel
Ilya Stepanchenko
Alexander Panfilov
Tatyana Lyutaya
Publisher: Springer International Publishing
Book: Creativity in Intelligent Technologies and Data Science
Print ISBN: 978-3-030-29742-8

Electronic ISBN: 978-3-030-29743-5

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-29743-5_14

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