GWR 2019 timetable recast
Assessing the performance impact of the biggest timetable change since 1976
Great Western Railway operates one of the key corridors in the UK, connecting London Paddington to the Cotswolds, West of England, South West England and South Wales. Following the electrification of the busiest part of the corridor and the replacement of the iconic but aging HST trainsets with state-of-the-art bimodal units provided by Hitachi, in December 2019 GWR introduced the biggest timetable change on the network since 1976, bringing faster, more frequent services with thousands more seats across the region. Around three-quarters of journey times changed.
Beyond the complexity of the study area - including several peculiar locations such as Paddigton and Reading stations and the coexistence of different operating companies - the main challenge was the need to simulate major changes in infrastructure, timetable and rolling stock at the same time, while being aware of the impact of each of these factors.
trenolab used its powerful trenissimo simulation tool to test the timetable drafts supplied by GWR, assessing performances under the current and other expectable conditions, with particular regard to input delays and performances of the new trainsets. trenolab supported to GWR highlighting critical issues and other weakness of the timetable and estimating the impact on PPM and other performance metrics compared to the current operations.Unexpectedly, the study showed that despite the new timetabled included more and faster services, PPM would have slightly increased. The timetable went into service as planned in December 2019 and real data confirmed this trend, demonstrating once again the strength of stochastic simulation in estimating the performance impact of new timetables.
Our tasks:
- Operations analysis
- Microscopic simulation model development
- Microscopic simulation model calibration
- Microscopic stochastic simulation
- 2019/06 - 2019/11
- UK
- Great Western Railway
- Timetable Planning
- TRENOplus, TRENOanalysis, trenissimo