Siemens Mobility Turns a Berlin S-Bahn Train into a Moving Track Surveyor
LiDAR and cameras on a passenger train keep a live digital twin of the railway up to date
Siemens Mobility has fitted a Berlin S-Bahn passenger train with LiDAR scanners and high-definition cameras that record the condition of the railway while the train runs its normal timetable. The data feeds a continuously updated 3D digital twin of the infrastructure, which Siemens sees as an essential building block for automatic train operation. The work was reported by Railway Gazette International in September 2026.
How the self-surveying train works
As the train runs in passenger service, its LiDAR and camera systems generate terabytes of data per shift. Machine learning algorithms then process that data to automatically recognise and locate 145 different types of railway asset, including track geometry, overhead line equipment, loading gauge clearances, retaining walls, signals, trackside landmarks and encroaching vegetation.
According to the report, Siemens’ algorithms have already processed more than 4,500 track-kilometres of infrastructure data, and the digital twin can be updated in near real time.
Why automated trains need live maps
Higher grades of automation, known as GoA3 and GoA4, allow trains to run without a driver in the cab. To do that safely, a train needs a precise, up-to-date map of its surroundings. As Railway Gazette’s report puts it, an autonomous train cannot rely on a map that was last updated six months ago.
Continuous surveying from in-service trains means changes such as new vegetation growth, shifted overhead wires or reduced clearances can be spotted quickly, both for automation and for everyday maintenance planning.
Surveying without extra track access
Traditionally, railway surveys rely on dedicated measurement trains or teams working on the track during closures. Here, the survey is a by-product of normal service, so no extra track access is needed and the data is refreshed every time the train runs.
Siemens is taking the technology forward in three phases: a rapid proof of concept, system hardening, and then expansion into a wider platform.
Digital rail skills in demand
Projects like this sit where rail engineering meets data science. They need LiDAR and survey specialists, software and machine learning engineers, signalling and systems engineers, and asset managers who can turn data into maintenance decisions. The same skills are increasingly in demand on UK rail as digital signalling and predictive maintenance grow.
Bernoullis recruits for computer and software engineering and electrical engineering roles. Get in touch to find out more.
Sources: Railway Gazette International · Bricks & Bytes
Images are illustrative. Credits: Michael.F.H.Barth, CC BY-SA 4.0 via Wikimedia Commons; Geoprofi Lars, CC BY-SA 4.0 via Wikimedia Commons; nzsteam, CC BY 2.0 via Wikimedia Commons.
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