Trains run on tracks, so intuitively, if we know the location of the rails, we should be able to adjust any measured position to align more closely with reality, right?

Right! But it's not that simple...

Measurement trains play a crucial role in ensuring railway safety and maintenance. They collect vital data on various parameters, including track gauge and catenary height. When these measurements fall outside acceptable limits, technicians are dispatched to address the issues. Over time, certain parameters can degrade, making predictive analysis essential for anticipating maintenance needs and enhancing operational efficiency. However, both timely interventions and accurate predictive analytics hinge on precise positioning of the measurement data.

In this talk, we will delve into the inner workings of an open-source library developed as part of the Openrail initiative. This library leverages rail network topology, train detection data, and GNSS/IMU/ODO information to post-process train positions effectively.

As an added bonus, we’ll explore how open-source hardware, specifically a Raspberry Pi, contributes to the positioning of measurement trains.