Cordel is aiding Southeastern's fleet upgrade program by installing AI-supported Light Detection and Ranging (LiDAR) and Video Imaging sensors on Network Rail's Infrastructure Monitoring (NR-IM) fleet. This 18-month project, initiated by Loram in Derby, aims to provide precise Structure Gauging data to the South East Alliance, a collaboration between Southeastern and Network Rail's Kent Route.
This critical asset information will also be shared with rolling stock suppliers, supporting Southeastern's goal of acquiring new or upgraded trains for Metro routes.
Steve White, MD of Southeastern, said: “To support growing demand, provide better performance and, crucially, improve accessibility, Southeastern are seeking a new (or upgraded) fleet of trains to deliver our Metro services. Cordel will deploy its automated LiDAR capture and AI-processing services to deliver up-to-date, accurate measurements of our Station Platforms which vary in height and curvature. Cordel’s AI makes sense of large volumes of data and quickly, getting insight into the hands of the South East Alliance, rolling stock bidders and Network Rail operations and maintenance teams.”
Network Rail's Infrastructure Monitoring (NR-IM) fleet plays a crucial role in collecting vital asset condition data. This data helps determine the optimal timing for asset interventions, ensuring railway safety and minimising disruption for customers.
For the installation of new technology, Cordel selected Loram, known for their expertise in maintaining the NR-IM fleet in Derby. Loram efficiently scheduled the installations during existing vehicle maintenance downtimes, seamlessly integrating multiple technologies without missing any data-gathering shifts.
Jason Saxon, Network Rail Director Asset Information, said: “This was a great opportunity to use the existing IM Fleet and its existing recording paths, in conjunction with some proven and easy to fit technology from Cordel, selected by our industry partners in South Eastern, to obtain data they needed to procure the next generation of rolling stock in Kent and ultimately improve the passenger experience. At the same time, Network Rail engineers get the same information to help us better manage the rail infrastructure.”
Rebeka Sellick, Business Development Director at Cordel, said: “We are enormously proud to have led and underwritten this deployment of our low maintenance but highly sophisticated AI-supported technology on Network Rail’s Infrastructure Monitoring Fleet. One pass on any fitted train along the railway at up to 100mph enables us to collect raw data across the rail corridor (and several metres beyond) that we can turn into measured outputs. We are delighted that the Network Rail Technical Authority has already approved our measurements for asset engineers to rely on.”
Cordel's autonomous 'Wave 32' hardware was installed by Loram just above the driving cabs on two existing NR-IM vehicles (DBSOs 9702 & 9703). This enhancement allows the specialized fleet to collect more comprehensive data during its regular operations.
As the IM Fleet moves across the rail network, Cordel's AI-supported geo-location systems capture detailed track position measurements, including cant, curvature, and track centrelines. Cordel processes this "Point Cloud" data to meet Network Rail's stringent requirements for structure gauging, track intervals, electrification contact wire positions, and station platform measurements. Additionally, it measures profiles and volumes of trackside vegetation and ballast.
The resulting asset information is timestamped with date, time, and precise location references, then automatically uploaded to the Cordel Cloud via 4G WiFi. From there, it can be quickly shared with Network Rail's asset engineers and their Train Operating Company customers.
Image credits: Cordel
