ATLAS (Automated Track & Lineside Asset Survey)

Gauging is a vital part of Network Rail’s maintenance and operating of the railway. Gauging is the process through which Network Rail ensures adequate clearance between passing trains and lineside objects and structures. Currently, this process requires specialist gauging machines or via manual reviews of point cloud data captured from trains, drones or personnel operated laser scanners. The consortium of MobiBiz (Lead), BAE Systems and Jacobs Engineering Group will enhance the interpretation of point-cloud data. MobiBiz’s cloud based ATLAS (Automated Track & Lineside Asset Survey) platform will be used to create an end-to-end automated pipeline of the following steps: 1. Automatically classify, detect and segment and locate trackside structures within a point cloud using deep learning. These structures include crossings, overbridges, platforms, underbridges, tunnels, viaducts, wall, signals, OLE supports, telecommunications structures and other line side furniture. 2. Automatically detect vegetation around trackside structures from point cloud data. 3. Use Artificial Intelligence techniques to interpret and analyse point clouds automatically and assist in gauging processing, cant, curvature and clearance. 4. Provide a Web based portal to visualise geo-references route overplayed with point cloud data and automated analysis to assist gauging engineers for visualisation, validation and cross-checking. 5. Integrate with existing Network Rail systems by outputting SC0 files and exposing an open API (Application interface) to facilitate integration with existing reporting systems, events and asset databases. Trainborne capture methods are now extremely efficient and accurate in capturing vast amounts of information in the form of point clouds. However the problem now lies in processing. Capturing terabytes of data makes the processing and subsequent analysing extremely slow, with much of the process taken up splitting the data into manageable chunks, cleaning up the chunks and classifying the data. ATLAS can automate this part, leaving more time for specialist Network Rail staff to actually review the outputted files and make informed maintenance decisions. These inspections can be carried out more frequently, spotting trends and issues as they arise. The processed data output from these inspections will be used to inform maintenance and assist with predictive maintenance planning and intervention. ATLAS also provides a visualisation platform, allowing Network Rail staff to compare point clouds of structures across multiple routes for current and historical data.