Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 7, Issue 1, 2023

Passenger Flow Distribution Model in Urban Rail Transit Hub Platform

Download as PDF

DOI: 10.23977/acss.2023.070115 | Downloads: 15 | Views: 461

Author(s)

Gao Long 1,2, Xie Binglei 1, Zong Chuanling 2, Zhang Ning 2

Affiliation(s)

1 Harbin Institute of Technology, Shenzhen, Shenzhen, 518055, China
2 State High-Tech Industrial Innovation Center, Shenzhen, Shenzhen, 518057, China

Corresponding Author

Xie Binglei

ABSTRACT

Urban rail transit hub platform is the most important area for passenger flow distribution. In order to calculate passenger flow volume in platform and evaluate platform service level during rush hours, this paper presents a method for modeling and simulation of passenger flow distribution in platform. Passenger flow distribution model (PFDM) is proposed based on the basic analysis and the superposition principle of passenger flow. Simulation design for PFDM is proposed by Anylogic, which contains simulation process and simulation model. Experiment results show that PFDM and simulation design are effective and accordant with the reality scenario, and the simulation precision is comparatively ideal. This research could provide a beneficial reference for train scheduling and operation management under the viewpoint of traffic safety and service level.

KEYWORDS

Passenger flow distribution model, Simulation design, Performance evaluation, Passenger flow volume, Service level, Urban rail transit hub platform

CITE THIS PAPER

Gao Long, Xie Binglei, Zong Chuanling, Zhang Ning. Passenger Flow Distribution Model in Urban Rail Transit Hub Platform. Advances in Computer, Signals and Systems (2023) Vol. 7: 115-127. DOI: http://dx.doi.org/10.23977/acss.2023.070115.

REFERENCES

[1] Fruin. J. J. Designing for pedestrians: a level of service concept. Washington DC: Highway Research Board. vol. 355, no. 12, pp. 1-15, 1971.
[2] Transportation Research Board. Highway Capacity Manual. Washington DC: National Research Council Press. pp. 635-670, 2000.
[3] Muramatsu. M, Irie. T, and Nagatani. T. Jamming transition in pedestrian counter flow. Physica A. vol. 267, no. 3, pp. 487-498, 1999.
[4] Okazaki. S. A study of pedestrian movement in architectural space, part 1: pedestrian movement by the application on of magnetic models. Transactions of the Architectural Institute of Japan. vol. 283, no. 3, pp. 111-119, 1979.
[5] Gipps. P. G., and Marksjo. B. A micro-simulation model for pedestrian flows. Mathematics and Computers in Simulation. vol. 27, no. 2, pp. 95-105, 1985.
[6] Lovas. G. G. Modeling and simulation of pedestrian traffic flow. Transportation Research Part B. vol. 28, no. 3, pp. 429-443, 1994.
[7] Helbing. D, and Molnar. P. Social force model for pedestrian dynamics. Physical Review E. vol. 51, pp. 4282-4286, 1995.
[8] Blue. V. J, and Adler. J. L. Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transportation Research Part B. vol. 35, pp. 293-312, 2001.
[9] Li. X. M, Yan. X. D, and Li. X. G. Using cellular automata to investigate pedestrian conflicts with vehicles in crosswalk at signalized intersection. Discrete Dynamics in Nature and Society. vol. 3, pp. 1555-1565, 2012.
[10] Helbing. D. Collective Phenomena and States in Traffic and Self-driven Many-particle Systems. Computational Materials Science. vol. 30, pp. 180-187, 2004.
[11] Xiong. H. W, Yao. L. Y, and Wang. W. H. Pedestrian walking behavior revealed through a random walk model. Discrete Dynamics in Nature and Society. vol. 12, pp. 1951-1965, 2012.
[12] Lu. L. L, Ren. G, and Wang. W. Exploring the effects of different walking strategies on bi-directional pedestrian flow. Discrete Dynamics in Nature and Society. vol. 2, pp. 1-9, 2013.
[13] Daamen. W, Bovy. P. H. L, and Hoogendoorn. S. P. Influence of changes in level on passenger route choice in railway stations. 84th Annual Meeting of the Transportation Research Board, Washington DC: National Research Council Press. pp. 12-20, 2005.
[14] Daamen. W, Bovy. P. H. L, and Hoogendoorn. S. P. Choices between stairs, escalators and ramps in stations. 10th International Conference on Computer System Design and Operation in the Railway and Other Transit Systems. pp. 3-12, 2006.
[15] Duive. D. C, Daamen. W, and Hoogendoorn. S. P. State-of-the-art crowd motion simulation models. Transportation Research Part C. vol. 37, no. 3, pp. 193-209, 2013.
[16] Guillermo H. G. A mathematical model of the formation of lanes in crowds of pedestrians moving in opposite directions. Discrete Dynamics in Nature and Society. vol. 2, pp. 56-63, 2015.
[17] Bandini. S, Mondini. M, and Vizzari. G. Modelling negative interaction among pedestrians in high density situations. Transportation Research Part C. vol. 40, no. 1, pp. 251-270, 2014.
[18] Seriani. S, and Fernandez. R. Pedestrian traffic management of boarding and alighting in metro stations. Transportation Research Part C. vol. 53, pp. 76-92, 2015.
[19] Zhang. Q., Han. B. M., and Li. D. W. Modeling and simulation of passenger alighting and boarding movement in Beijing metro stations. Transportation Research Part C. vol. 16, no. 5, pp. 635-649, 2008.
[20] Zhang. Q., Han. B. M. Modeling and simulation of transfer performance in Beijing metro stations. 8th IEEE International Conference on Control and Automation. vol. 17, no. 1, pp. 1888-1891, 2010.
[21] Yang. Y. D., Li. J., and Zhao. J. X. Study on Passenger Flow Simulation in Urban Subway Station Based on Anylogic. Journal of Software. vol. 9, no. 1, 2014.
[22] Wang. G. Research on the model of assembling in the urban rail transit platform [Master dissertation]. Beijing Jiaotong University, China, 2012.
[23] Gao. S. S. Analysis and calculation of assembling passengers at urban rail transit platform [Master dissertation]. Beijing Jiaotong University, China, 2015.
[24] Wang S. W, and Rong. J. Transit station congestion index research based on pedestrian simulation and gray clustering evaluation. Discrete Dynamics in Nature and Society. vol. 12, pp. 1-8, 2013.
[25] Zhao. H. Study on the service level of pedestrian facility in urban rail transit hub [Master dissertation]. Beijing University of Civil Engineering and Architecture, China, 2011.
[26] Schelenz. T, Suescun. A, and Wikstrom. L. Passenger-centered design of future buses using agent-based simulation. Procedia-Social and Behavioral Sciences. vol. 48, pp. 1662-1671, 2012.
[27] Schelenz. T, Suescun. A, and Karlsson. M. Decision making algorithm for bus passenger simulation during the vehicle design process. Transport Policy. vol. 25, no. 1, pp. 178-185, 2013.
[28] Schelenz. T, Suescun. A, and Wikstrom. L. Application of agent based simulation for evaluating a bus layout design from passengers' perspective. Transportation Research Part C. vol. 43, no. 2, pp. 222-229, 2014.
[29] Zhao. N, and An. S. Collaborative management of complex major construction projects: anylogic-based simulation modeling. Discrete Dynamics in Nature and Society. vol. 10, pp. 1-8, 2016.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 12501
Visits: 251266

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.