Case study: Network Rail on the data-driven decisions keeping our railways safe | Computer Weekly
Summary
The project was presented as a case study at the recent Big Data and AI World conference in London, in early March 2024. “These are the two types of assets that are most at risk of failure during heavy rainfall,” said Mike Briggs, director of data insights at the Rail Safety and Standards Board. We have to remember that we’re making the decisions on the speed of passenger trains based on the outcomes of these models.” This, said Briggs, meant working closely with Network Rail’s own experts. And how many times did we see failures?” This statistical model then formed the basis of a new tool, PRIMA – Proportionate Risk Response to Implementing Mitigating Speeds to Assets. PRIMA helps Network Rail’s operations teams identify parts of the track that are at risk following heavy rain.