An Innovate UK funded Knowledge Transfer Partnership (KTP) was initiated to provide Eurostar International Limited with new knowledge in advanced simulation modelling to support year on year growth in passenger numbers and revenue.
The study, led by Professor Jesse O’ Hanley identified new ways to reduce passenger queuing and minimise the impact of train delays and network disruptions.
Key milestones include a detailed accounting of data sources and gaps, creation of multiple digital twins of individual stations and a large fleet-level model of Eurostar’s entire operation, including train movements from station to station, maintenance depots and the main control centre.
Modelling and analysis used in the study supported greater use of evidence-based decision making at Eurostar, helping it to increase passenger throughput through better understanding of the key triggers that create queues and evaluation of proposed interventions to reduce congestion, as well as improve the robustness of train timetables by pre-emptively identifying which trains are most at risk of delay, thereby allowing managers to take preventative steps.
Two concrete examples include analysis that was critical to informing the new layout of border controls at Eurostar’s Paris Gare du Nord station and implementation of a new departure area at London St Pancras. Simulation helped to identify how best to position new border control stations and reorganise queue lanes at Paris in order to smooth passenger flows through the station and increase passenger throughput.
In London, virtual testing showed that repurposing arrival space for a new departure lounge could increase passenger throughput at peak times without adversely affecting arrivals. Following its construction, Eurostar witnessed its highest ever passenger processing rates and customer satisfaction scores over the peak summer travel period.