Innovate UK is to lead a research project that could result in faster and higher-precision mapping of Britain’s railway infrastructure through the use of AI.
The project is being funded by Network Rail under its R&D portfolio and delivered by Innovate UK through the SBRI competition, Innovation in Automated Survey Processing for Railway Structure Gauging, Phase One.
Hexagon, a sensor, software and autonomous solutions provider headquartered in Stockholm, Sweden, will conduct the project through its Geospatial business division.
If successful, the project will enable Network Rail to automatically identify and measure railway structures from lidar data, saving time and resources, while also improving planning and operations across the rail network.
According to Network Rail, the current manual process can take analysts months or years to complete due to the size of data and labour-intensive tasks involved.
“The combination of cross-sectional area, shape, length and speed all place a space requirement on today’s railway,” said James Sweeney, senior engineer at Network Rail.
“We anticipate this project will offer us a more efficient way to capture, analyse and measure railway features along 20,000 miles of track, which is important to railway safety and the growth and capacity of our network.”
Network Rail currently collects detailed information about its track and the surrounding features, such as bridges and tunnels. The data is then analysed to assess clearances between trains and the infrastructure around them.
The new project aims to automate the extraction and calculation of railway features from sensor data, leveraging AI to automatically analyse point cloud data, identify different structure types and perform measurements on the structures.
The data will be collected from reality capture solutions from Hexagon Geosystems.
“Network Rail, supported by Innovate UK, is leading the way in the use of AI to automate rail structure identification and measurement,” said Mladen Stojic, president of Hexagon’s Geospatial division. “We are excited to be part of a project that can help transform the gauging process for UK railways.”
