Cargando…
A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability
The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some litera...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9394422/ https://www.ncbi.nlm.nih.gov/pubmed/35893006 http://dx.doi.org/10.3390/e24081026 |
_version_ | 1784771486726225920 |
---|---|
author | Su, Guanghui Si, Bingfeng Zhi, Kun Li, He |
author_facet | Su, Guanghui Si, Bingfeng Zhi, Kun Li, He |
author_sort | Su, Guanghui |
collection | PubMed |
description | The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of passenger flow distribution. Specifically, the existing methods have not been applied to practical large-scale subway networks due to the computational complexity. To fill this research gap, this paper analyzes the relationship between passenger travel behavior and train operation in the space and time dimension and formulates the passenger–train matching probability by using multi-source data including AFC, train timetables, and network topology. Then, a reverse derivation method, which can reduce the scale of possible train combinations for passengers, is proposed to improve the computational efficiency. Simultaneously, an estimation method of passenger flow distribution is presented based on the passenger–train matching probability. Finally, two sets of experiments, including an accuracy verification experiment based on synthetic data and a comparison experiment based on real data from the Beijing subway, are conducted to verify the effectiveness of the proposed method. The calculation results show that the proposed method has a good accuracy and computational efficiency for a large-scale subway network. |
format | Online Article Text |
id | pubmed-9394422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93944222022-08-23 A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability Su, Guanghui Si, Bingfeng Zhi, Kun Li, He Entropy (Basel) Article The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of passenger flow distribution. Specifically, the existing methods have not been applied to practical large-scale subway networks due to the computational complexity. To fill this research gap, this paper analyzes the relationship between passenger travel behavior and train operation in the space and time dimension and formulates the passenger–train matching probability by using multi-source data including AFC, train timetables, and network topology. Then, a reverse derivation method, which can reduce the scale of possible train combinations for passengers, is proposed to improve the computational efficiency. Simultaneously, an estimation method of passenger flow distribution is presented based on the passenger–train matching probability. Finally, two sets of experiments, including an accuracy verification experiment based on synthetic data and a comparison experiment based on real data from the Beijing subway, are conducted to verify the effectiveness of the proposed method. The calculation results show that the proposed method has a good accuracy and computational efficiency for a large-scale subway network. MDPI 2022-07-26 /pmc/articles/PMC9394422/ /pubmed/35893006 http://dx.doi.org/10.3390/e24081026 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Su, Guanghui Si, Bingfeng Zhi, Kun Li, He A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title | A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title_full | A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title_fullStr | A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title_full_unstemmed | A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title_short | A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability |
title_sort | calculation method of passenger flow distribution in large-scale subway network based on passenger–train matching probability |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9394422/ https://www.ncbi.nlm.nih.gov/pubmed/35893006 http://dx.doi.org/10.3390/e24081026 |
work_keys_str_mv | AT suguanghui acalculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT sibingfeng acalculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT zhikun acalculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT lihe acalculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT suguanghui calculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT sibingfeng calculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT zhikun calculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability AT lihe calculationmethodofpassengerflowdistributioninlargescalesubwaynetworkbasedonpassengertrainmatchingprobability |