Data Analytics to predict and reduce passenger delays

Russell Martin1 and Antony McCabe2 1Department of Computer Science; 2Institute of Integrative Biology University of Liverpool Contact: a.mccabe@liv.ac.uk

Delays • When a delay occurs, later services may also be

affected. • A rail network has operational dependencies. • Some are known, e.g.; track, trains, people • Others are possibly unknown. • Delays can propagate through the network. • By mining pas t running data, we can find the

dependencies and model how delays propagate

Dependencies • Even the known dependencies are not always

used to currently inform passengers. • These dependencies may not be obvious, or may

need to be manually entered. • Computational discovery of delay propagation

can help to give passengers better and faster information regarding delays.

Data • The ‘Data’ would include historical, and

current, Train movement data. • Data from other relevant sources, e.g., Twitter

could also be included. • This dataset is of manageable size by

BioInformatic standards. • Past data could be used to generate full

network simulations.

Objectives • To better inform passengers of likely delays and

how to avoid them. • To discover how delays propagate and, by

simulating the rail network, search for changes that may help reduce future delays.

The University of Liverpool provides: • A Multi-disciplinary Software Lab dedicated to

Network Technologies (NeST)

Expertise and experience with : • Data Mining1

• Analysing Large Datasets2 • Producing Analytical Software3 • Temporal Networks4 • Graph Routing Algorithms5 • Network Congestion Games6

Sample References A Scalable Algorithm for Banded Pattern Mining In Multi-Dimensional Zero-One Data MLDM 2014 1

Bioinformatics challenges and solutions in proteomics as quantitative methods mature. OMICS, (In Press) 2 Software for analysing ion mobility mass spectrometry data to improve peptide identification. PROTEOMICS 2012 3

Designing and Testing Temporally Connected Graphs CORR 2015 4 Shortest Paths with Bundles and Non-Additive Weights is Hard CIAC 2013 5

Weighted Congestion Games: The Price of Anarchy, Universal Worst-Case Examples, and Tightness. ACM TEC 2015 6

Example Deliverables • An API for retailers that can report ‘at risk’

connections and suggest smart alternatives. • A website (or app) that shows how current delays

may affect the passenger in the near future. • A simulation model of the rail network.

Proportion of services with total delay of 10 minutes or more (up to 15%)

Data source: Network Rail Movement Data Feed Oct ‘12 – Sep ‘13

Proportion of services with additional delay of 5 minutes or more (up to 10%)