Chris Harrison
Principal Futures Systems Engineer, RSSB
It's the sort of bad dream that would make a rail manager wake up in a cold sweat: a late running passenger service overspeeds through a temporary speed restriction and passes a signal at danger.
In the light of day, it's unlikely all three of these would happen at once—but separated out, they are very real issues on our railways. They also carry with them substantial financial, safety, and reputational liabilities.
The rail industry is already committed to combat these challenges, but we have an opportunity to further build on existing approaches with a more informed, system-wide, data-driven future. At the heart of this evolution is Train Movement Insights (TMI).
A new data landscape
This new analytical tool builds on the foundation of the Red Aspect Approaches to Signals (RAATS) system. While RAATS focused on signal approaches, TMI will widen the lens of RAATS to look at other operational features. By using additional data, the TMI tool will operate across three core areas designed to provide insights on the network. They are SPAD prevention, service reliability, and overspeed.
The first module provides estimates of how often trains encounter red signals. Users can benchmark SPAD rates and target interventions where they are needed most.
The second module looks at the journey from the train’s perspective. By overlaying performance data with signal sequences, it will help put train performance in the context of the signal aspects approached. This will help identify specific patterns of delay. This makes it possible to find and fix hidden pinch points.
The third module reinforces safety through network-wide speed insights. The overspeeding tool will give an indicator of where speeding may be an issue. It provides the intelligence required for targeted risk reduction.
Forging a resilient future
Using TMI we'll unlock better timetable planning. Decision-makers will be able to perform retrospective analyses on previous changes. This ensures that future schedules are built on proven performance rather than projections.
Furthermore, the data transforms driver training. Operators can now brief drivers on specific 'high-risk' signals based on real-time train movement profiles, enhancing preparedness and safety.
This change represents a strategic shift toward a more resilient railway. The TMI tool provides operational analysts and senior leaders with practical, evidence-based insights that can be acted upon immediately.
Looking forward, the goal is further industry collaboration. As new operational data becomes available, the scope for TMI will grow.
The focus remains clear: reducing delays, mitigating risk, and protecting the bottom line.
Data modelling has turned the complexity of train movements into a manageable strategic asset.