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# MODELLING PASSENGER DISTRIBUTION ON METRO STATION PLATFORM

DOI: 10.7708/ijtte.2014.4(4).08

4 / 4 / 456-465 Pages

Author(s)

Nikola Krstanoski - Faculty for Technical Sciences, Department for Transport and Traffic Engineering, University â€œSt. Kliment Ohridskiâ€, Bitola, Macedonia -

Abstract

The problems such as design of a metro station, an analysis of the station or line performance characteristics, simulation of passenger alighting and boarding process, simulation of metro line operation, etc. involve the need to get much better knowledge about the behavior of the passengers on the station platform in terms of their distribution among train doors in relation with the station design elements. Despite this, there have been only very limited number of researchers that tackled this problem. In this article, a model of passenger distribution among metro train doors has been developed. The model has been based on the data collected from the Bloor metro station in Toronto, Canada. Metro trains were video-taped during two-hour study period and data were obtained for the number of alighting and boarding passengers per each door and per each train. The results of the statistical analysis have shown that multinomial probability distribution appears to be a good model to describe passenger boarding and alighting process. It also has been shown that there has been clear dependence of the passenger distribution among train doors on the position of the platform entrance and exit points.

Acknowledgements:

The data used in this research were made available to me courtesy of Prof. Gerald N. Stuart from University of Toronto and were collected as part of the study done by Bruce Mori at the same University (Mori, 1988). The author of this paper would like to express special thanks to Prof. Gerald N. Stuart from University of Toronto, for the great help by making to me available the data from video recordings on Bloor station in Toronto.

References:

Cox, C. 1984. An Elementary Introduction to Maximum Likelihood Estimation for Multinomial Models: Birch’s Theorem and the Delta Method, The American Statistician. DOI: http://dx.doi.org/10.1080/00031305.1984.10483226, 38(4): 283-287.

Krstanoski, N. 1996. Rapid Transit Line Performance Analysis: A Stochastic Approach. A Dissertation in Systems Engineering, University of Pennsylvania, USA.

Mori, B. 1988. A Study of the Dwell Time at Urban Rail Transit Stations. Master Thesis. Department of Civil Engineering, University of Toronto.

Szplett, D.; Wirasinghe, S.C. 1984a. An Investigation of Passenger Interchange and Train Standing Time at LRT Stations: (i) Alighting, Boarding and Platform Distribution of Passengers, Journal of Advanced Transportation. DOI: http://dx.doi.org/10.1002/atr.5670180102, 18(1): 1-12.

Szplett, D.; Wirasinghe, S.C. 1984b. An Investigation of Passenger Interchange and Train Standing Time at LRT Stations: (ii) Estimation of standing Time, Journal of Advanced Transportation. DOI: http://dx.doi.org/10.1002/atr.5670180103, 18(1): 13-24.

Thomson, S.K. 1987. Sample Size for Estimating Multinomial Proportions, The American Statistician. DOI: http://dx.doi.org/10.1080/00031305.1987.10475440, 41(1): 42-46.

Wu, Y.; Rong, J.; Wei, Z.; Liu, X. 2012. Modeling Passenger Distribution on Subway Station Platform prior to the Arrival of Trains, Transportation Research Board Annual Meeting 2012, Paper #12. 15 p.

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