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Can passenger flow distribution be estimated solely based on network properties in public transport systems? / Luo, Ding; Cats, Oded; van Lint, Hans.

In: Transportation, 01.01.2019.

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@article{26640156674241c09cb8f51d5a1d3da0,
title = "Can passenger flow distribution be estimated solely based on network properties in public transport systems?",
abstract = "We present a pioneering investigation into the relation between passenger flow distribution and network properties in public transport systems. The methodology is designed in a reverse engineering fashion by utilizing passively measured passenger flow dynamics over the entire network. We quantify the properties of public transport networks using a range of centrality indicators in the topological representations of public transport networks with both infrastructure and service layers considered. All the employed indicators, which originate from complex network science, are interpreted in the context of public transport systems. Regression models are further developed to capture the correlative relation between passenger flow distribution and several centrality indicators that are selected based on the correlation analysis. The primary finding from the case study on the tram networks of The Hague and Amsterdam is that the selected network properties can indeed be used to approximate passenger flow distribution in public transport systems to a reasonable extent. Notwithstanding, no causality is implied, as the correlation may also reflect how well the supply allocation caters for the underlying demand distribution. The significance and relevance of this study stems from two aspects: (1) the unraveled relation provides a parsimonious alternative to existing passenger assignment models that require many assumptions on the basis of limited data; (2) the resulting model offers efficient quick-scan decision support capabilities that can help transport planners in tactical planning decisions.",
keywords = "Centrality, Complex network science, Network properties, Passenger flow distribution, Public transport systems, Topology",
author = "Ding Luo and Oded Cats and {van Lint}, Hans",
year = "2019",
month = "1",
day = "1",
doi = "10.1007/s11116-019-09990-w",
language = "English",
journal = "Transportation",
issn = "0049-4488",
publisher = "Springer Netherlands",

}

RIS

TY - JOUR

T1 - Can passenger flow distribution be estimated solely based on network properties in public transport systems?

AU - Luo, Ding

AU - Cats, Oded

AU - van Lint, Hans

PY - 2019/1/1

Y1 - 2019/1/1

N2 - We present a pioneering investigation into the relation between passenger flow distribution and network properties in public transport systems. The methodology is designed in a reverse engineering fashion by utilizing passively measured passenger flow dynamics over the entire network. We quantify the properties of public transport networks using a range of centrality indicators in the topological representations of public transport networks with both infrastructure and service layers considered. All the employed indicators, which originate from complex network science, are interpreted in the context of public transport systems. Regression models are further developed to capture the correlative relation between passenger flow distribution and several centrality indicators that are selected based on the correlation analysis. The primary finding from the case study on the tram networks of The Hague and Amsterdam is that the selected network properties can indeed be used to approximate passenger flow distribution in public transport systems to a reasonable extent. Notwithstanding, no causality is implied, as the correlation may also reflect how well the supply allocation caters for the underlying demand distribution. The significance and relevance of this study stems from two aspects: (1) the unraveled relation provides a parsimonious alternative to existing passenger assignment models that require many assumptions on the basis of limited data; (2) the resulting model offers efficient quick-scan decision support capabilities that can help transport planners in tactical planning decisions.

AB - We present a pioneering investigation into the relation between passenger flow distribution and network properties in public transport systems. The methodology is designed in a reverse engineering fashion by utilizing passively measured passenger flow dynamics over the entire network. We quantify the properties of public transport networks using a range of centrality indicators in the topological representations of public transport networks with both infrastructure and service layers considered. All the employed indicators, which originate from complex network science, are interpreted in the context of public transport systems. Regression models are further developed to capture the correlative relation between passenger flow distribution and several centrality indicators that are selected based on the correlation analysis. The primary finding from the case study on the tram networks of The Hague and Amsterdam is that the selected network properties can indeed be used to approximate passenger flow distribution in public transport systems to a reasonable extent. Notwithstanding, no causality is implied, as the correlation may also reflect how well the supply allocation caters for the underlying demand distribution. The significance and relevance of this study stems from two aspects: (1) the unraveled relation provides a parsimonious alternative to existing passenger assignment models that require many assumptions on the basis of limited data; (2) the resulting model offers efficient quick-scan decision support capabilities that can help transport planners in tactical planning decisions.

KW - Centrality

KW - Complex network science

KW - Network properties

KW - Passenger flow distribution

KW - Public transport systems

KW - Topology

UR - http://www.scopus.com/inward/record.url?scp=85062771722&partnerID=8YFLogxK

U2 - 10.1007/s11116-019-09990-w

DO - 10.1007/s11116-019-09990-w

M3 - Article

JO - Transportation

T2 - Transportation

JF - Transportation

SN - 0049-4488

ER -

ID: 52554296