10037862NextGen Data-Driven Timetable Performance Optimisation ToolClosedCollaborative R&DInnovate UKDuring the pandemic, the on-time reliability of services significantly increased due to the reduction in the number of services and passengers. However, as passengers have returned to the railway performance has once again deteriorated. This has an even greater impact on the industry post-pandemic as passengers' expectations for services that are reliable and run on-time is even higher. Increased delays and passenger dissatisfaction therefore leads to an even greater decreased revenue from ticket sales. Poor performance is in large part due to a poorly planned timetable that is often operationally unachievable or cannot handle minor perturbations. This is due to the timetable usually being planned with simulations and the method does not in how trains performing in reality at junction or stations. Through years of working closely with performance, planning and operational teams, we've identified that by using granular train movement data and machine learning techniques, the actual performance of the existing timetable could be accurately calculated. This would enable planners with accurate information to make faster and better planning decisions that are based on real-world evidence. Our Timetable Analysis tool will deliver automatically updated insights and recommendations to planners that is highly aligned to the planning process. Utilising both on-track (track circuit) and on-fleet (GPS and OTMR) data, the tool will provide an integrated view to both Network Rail and TOC teams. Fundamentally this tool will result in a step change in the speed and quality of timetable planning, moving away from the use of limited simulations and anecdotal experience to a fully evidenced-based approach.