Version 1
: Received: 23 September 2016 / Approved: 26 September 2016 / Online: 26 September 2016 (08:11:45 CEST)
Version 2
: Received: 2 December 2016 / Approved: 2 December 2016 / Online: 2 December 2016 (07:52:00 CET)
How to cite:
Gao, L.; Jia, L. Modeling and Simulation of Passenger Flow Distribution in Urban Rail Transit Hub Platform. Preprints2016, 2016090085. https://doi.org/10.20944/preprints201609.0085.v2.
Gao, L.; Jia, L. Modeling and Simulation of Passenger Flow Distribution in Urban Rail Transit Hub Platform. Preprints 2016, 2016090085. https://doi.org/10.20944/preprints201609.0085.v2.
Cite as:
Gao, L.; Jia, L. Modeling and Simulation of Passenger Flow Distribution in Urban Rail Transit Hub Platform. Preprints2016, 2016090085. https://doi.org/10.20944/preprints201609.0085.v2.
Gao, L.; Jia, L. Modeling and Simulation of Passenger Flow Distribution in Urban Rail Transit Hub Platform. Preprints 2016, 2016090085. https://doi.org/10.20944/preprints201609.0085.v2.
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
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
