FRAZER-NASH CONSULTANCY

Predicting delays on the UK rail network

Understanding how delays will propagate and recover on the UK rail network is a complex challenge: the network has a complicated infrastructure and is used heavily by both passengers and freight. With information recorded by every train as it passes through the thousands of timing points on the network, there is an abundance of data that is too detailed to give operators the holistic view required to make informed decisions but, if aggregated and presented suitably, has the potential to provide valuable insight.

Funded under a grant from Network Rail and RSSB, as part of its Data Sandbox+ competition, Frazer-Nash Consultancy have combined their advanced Machine Learning experience from the defence sector with Lampada Digital Solution’s comprehensive and detailed rail network database (NR+) to develop REPAIR: Rapid Evaluation and Planning Analysis

Infrastructure for Railways. REPAIR applies a model trained on five years of historical data to live data feeds from Network Rail, allowing predictions to be made on how delays might improve or worsen in the following hours. The visualisation tools also provide an overview of these delays on the rail network, allowing users to quickly identify locations that have delays which may impact their operations.

Extensions to the predictive model were also developed, utilising NR+’s route-finding methodology, to offer alternative routing solutions, and allow the user to run ‘what if’ scenarios to test the impact of different incidents on the system as a whole. This will empower controllers to make faster and better decisions. These extensions were designed as a result of engagement with an advisory board, made up of major players in the rail freight operating sector.

CONTACT:

Gwen Palmer g.palmer@fnc.co.uk

01752 507641