Vossloh Integrates LiDAR Technology for Digital Track Inspection

Vossloh AG has formally completed the acquisition of the LiDAR specialist Cordel following court approval and shareholder consent. The transaction, with a volume of around 33 million euros (corresponding to 29 million British pounds), is part of a structured expansion of the company's digital competencies. To provide the capital for expanding these digital offerings, Vossloh had previously placed a hybrid bond worth 250 million euros.

Technical Functionality of the LiDAR Systems
Cordel applies Light Detecting and Ranging (LiDAR) technology for the physical inspection of rail infrastructures. Laser measuring devices installed on trains capture the surroundings and generate three-dimensional scans during operation. This technical mechanism enables the early identification of physical deviations in the track area, including uneven ballast beds, vegetation encroaching on the clearance gauge, or improperly positioned overhead lines. The processing and analysis of the geodata collected over large areas is subsequently carried out by artificial intelligence algorithms.

Operational Applications and Infrastructural Effects
The automated inspection technology is currently being used by major railway operators in the United Kingdom, the Middle East, North America, and Australia to monitor their networks. The continuous recording and evaluation of route data transitions reactive maintenance processes into a data-based model. Regarding the infrastructural effects of this integration, Oliver Schuster, CEO of Vossloh AG, explains that the technology " enables customers to have an even more comprehensive view of their rail network and creates the prerequisites for predictive maintenance and a more reliable operation." Regarding the future scalability of the systems, John Davis, CEO of Cordel Group PLC, adds: "As part of the Vossloh Group, we can further develop our technology and jointly pursue our vision: to transform railway infrastructure through innovation."

Edited by: Maria Brueva, Induportals editor – adapted by AI.

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