Zoomable Level-of-Detail ChartTables for Interpreting Probabilistic Model Outputs for Reactionary Train Delays

Fuente: arXiv
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Autores principales: Slingsby, Aidan, Hyde, Jonathan
Formato: Preprint
Publicado: 2024
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author Slingsby, Aidan
Hyde, Jonathan
author_facet Slingsby, Aidan
Hyde, Jonathan
contents "Reactionary delay" is a result of the accumulated cascading effects of knock-on train delays which is increasing on UK railways due to increasing utilisation of the railway infrastructure. The chaotic nature of its effects on train lateness is notoriously hard to predict. We use a stochastic Monte-Carto-style simulation of reactionary delay that produces whole distributions of likely reactionary delay and delays this causes. We demonstrate how Zoomable Level-of-Detail ChartTables - case-by-variable tables where cases are rows, variables are columns, variables are complex composite metrics that incorporate distributions, and cells contain mini-charts that depict these as different levels of detail through zoom interaction - help interpret whole distributions of model outputs to help understand the causes and effects of reactionary delay, how they inform timetable robustness testing, and how they could be used in other contexts.
format Preprint
id arxiv_https___arxiv_org_abs_2408_01203
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Zoomable Level-of-Detail ChartTables for Interpreting Probabilistic Model Outputs for Reactionary Train Delays
Slingsby, Aidan
Hyde, Jonathan
Human-Computer Interaction
"Reactionary delay" is a result of the accumulated cascading effects of knock-on train delays which is increasing on UK railways due to increasing utilisation of the railway infrastructure. The chaotic nature of its effects on train lateness is notoriously hard to predict. We use a stochastic Monte-Carto-style simulation of reactionary delay that produces whole distributions of likely reactionary delay and delays this causes. We demonstrate how Zoomable Level-of-Detail ChartTables - case-by-variable tables where cases are rows, variables are columns, variables are complex composite metrics that incorporate distributions, and cells contain mini-charts that depict these as different levels of detail through zoom interaction - help interpret whole distributions of model outputs to help understand the causes and effects of reactionary delay, how they inform timetable robustness testing, and how they could be used in other contexts.
title Zoomable Level-of-Detail ChartTables for Interpreting Probabilistic Model Outputs for Reactionary Train Delays
topic Human-Computer Interaction
url https://arxiv.org/abs/2408.01203