Trains face countless risks across the almost 16,000km of track in Great Britain. From misuse of level crossings to overhanging trees, Network Rail works with partners across the network to protect passengers from a wide array of potential safety issues.
This task increasingly involves use of AI tools, with several trials rolled out recently to assess and counter risks to journeys and passengers. These include Radar (Rail Anomaly Detection And Reaction), one of several rail-focused projects to receive a portion of £32m from UK Research and Innovation (UKRI) earlier this month.
Led by JR Dynamics, Network Rail, First Trenitalia West Coast Rail, Angel Trains and Komodo Digital, the work is focused on safety issues and disruption caused by faults between electric pantographs and the overhead lines they draw power from. AI and machine learning techniques will be used in a ‘self-learning, automated’ anomaly detection system, enhancing the existing Pandas-V pantograph and overhead line monitoring solution, which combines high-definition video footage with accelerometer and GPS data to pinpoint defects.