NextGen Data-Driven Timetable Performance Optimisation Tool

于疫情期间，由于服务及乘客数量减少，服务的准时可靠性显著提高，但随着乘客返回铁路，表现再次转差。这对疫情后的行业影响更大，因为乘客对可靠及准时服务的期望更高。因此，延误和乘客不满的增加导致售票收入进一步减少。业绩不佳在很大程度上是由于计划不周的时间表，这往往是无法实现的，或无法处理小的扰动。这是因为列车时刻表通常是通过模拟来规划的，而这种方法并不了解列车在枢纽或车站的实际运行情况。通过多年与性能、规划和运营团队的密切合作，我们发现，通过使用精细的列车运行数据和机器学习技术，可以准确计算出现有时刻表的实际运行情况。这将使规划者能够获得准确的信息，根据真实世界的证据做出更快、更好的规划决策。我们的时间表分析工具将自动更新与规划流程高度一致的见解和建议。该工具将利用轨道上（轨道电路）和车队上（GPS和OTMR）数据，为网络铁路和TOC团队提供综合视图。从根本上讲，该工具将使时间表规划的速度和质量发生根本性变化，从使用有限的模拟和轶事经验转向完全基于证据的方法。

During 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.