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

TL;DR

This paper introduces Zoomable Level-of-Detail ChartTables, a visualization tool that helps interpret complex probabilistic model outputs of reactionary train delays, aiding understanding and robustness testing.

Contribution

It presents a novel visualization method combining tables and mini-charts with zoom interaction to interpret distributions of reactionary delay models.

Findings

Effective visualization of delay distributions

Enhanced understanding of delay causality

Potential for broader application in probabilistic analysis

Abstract

"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.