Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Can passenger flow distribution be estimated solely based on network properties in public transport systems?
by
Cats, Oded
, Luo, Ding
, Hans van Lint
in
Case studies
/ Causality
/ Correlation analysis
/ Distribution
/ Flow distribution
/ Indicators
/ Infrastructure
/ Network centrality
/ Networks
/ Passengers
/ Properties (attributes)
/ Property
/ Public transportation
/ Regression analysis
/ Regression models
/ Reverse engineering
/ Street cars
/ Supply & demand
/ Transportation models
/ Transportation networks
/ Transportation systems
2020
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Can passenger flow distribution be estimated solely based on network properties in public transport systems?
by
Cats, Oded
, Luo, Ding
, Hans van Lint
in
Case studies
/ Causality
/ Correlation analysis
/ Distribution
/ Flow distribution
/ Indicators
/ Infrastructure
/ Network centrality
/ Networks
/ Passengers
/ Properties (attributes)
/ Property
/ Public transportation
/ Regression analysis
/ Regression models
/ Reverse engineering
/ Street cars
/ Supply & demand
/ Transportation models
/ Transportation networks
/ Transportation systems
2020
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Can passenger flow distribution be estimated solely based on network properties in public transport systems?
by
Cats, Oded
, Luo, Ding
, Hans van Lint
in
Case studies
/ Causality
/ Correlation analysis
/ Distribution
/ Flow distribution
/ Indicators
/ Infrastructure
/ Network centrality
/ Networks
/ Passengers
/ Properties (attributes)
/ Property
/ Public transportation
/ Regression analysis
/ Regression models
/ Reverse engineering
/ Street cars
/ Supply & demand
/ Transportation models
/ Transportation networks
/ Transportation systems
2020
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Can passenger flow distribution be estimated solely based on network properties in public transport systems?
Journal Article
Can passenger flow distribution be estimated solely based on network properties in public transport systems?
2020
Request Book From Autostore
and Choose the Collection Method
Overview
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.
MBRLCatalogueRelatedBooks
Related Items
Related Items
This website uses cookies to ensure you get the best experience on our website.