Improved Energy Efficiency of Railway Transport using AI

The effectivnes and efficiency of the Swedish railway transport need to be improved, to fulfil the ever growing demands on sustaible transport.

It is believed that shifting from road to rail transport will have major contribution to global sustainability goals, though improved energy inefficiency.

However, rail track conditions influence capacity and punctuality, which are important factors for railway trustworthiness.

Hence, the objective of this project is to improve the track condition. one of the main challenges in track condition monitoring is to distinguish between regular designed elements (like turnouts, and joints) from track defects. A key innovation of this project is on AI to identify and dectect the existence of defects.

Additionally, the project will investigate fusion of other data sources, e.g. LIDAR and satellite data.

Furthermore, a demonstrator will be developed as proof-of-concept using the existing “AI Factory for Railway” framework developed by LTU.