A new artificial intelligence-powered monitoring system designed to track passenger numbers in real time could help reduce overcrowding on UK trains and improve the passenger experience.
Developed through a collaboration between Loughborough University and rail technology company TrainFX, the system uses depth-sensing cameras and onboard AI to estimate how crowded each train carriage is, even during busy peak periods and in low-light conditions.
Unlike conventional CCTV, the technology captures depth information only, allowing passenger movement and occupancy levels to be monitored without identifying individuals. The live data is processed onboard through TrainFX’s Smart Passenger Information System, enabling operators and station staff to monitor crowding more effectively.
Researchers say the system could help train operators improve scheduling, crowd management and long-term capacity planning. In future, passengers may also be able to access live occupancy information before boarding, helping them identify quieter carriages.
The prototype has already been tested successfully within TrainFX’s simulated rail environment and is now preparing for live trials with train operators.
The project was funded through a UK Research and Innovation-backed Knowledge Transfer Partnership and recently won the AI Tech Innovation of the Year award at the Made in the UK Midlands Awards 2026.
TrainFX said the technology aims to provide operators with better insight into passenger demand while making better use of available train capacity.