Demand Impacts of Recovery Time in Railway Timetables

Demand Impacts of Recovery Time in Railway Timetables


F Teklu, J Segal, M Dix, MVA Consultancy; M Wardman, ITS, University of Leeds; B Condry, ATOC, UK


This paper presents the results of a study into passengers' awareness and valuation of recovery time in railway timetables.


Recovery time is the time included in timetables to compensate for unplanned delays. This provides passengers with a more reliable service relative to advertised times, with a related improvement in train operators' Public Performance Measure (PPM) scores.

Recovery time extends the scheduled journey time beyond what is needed in undelayed circumstances: trains either stop at intermediate stations for longer than they should, stop between stations or run slowly between stations due to recovery time. Whilst the increased reliability may increase rail demand, the increased journey times may have the opposite effect. Recovery time may be valued differently from other times in trains and its valuation may be dependent on how it is implemented. This paper aims to understand passengers'awareness of recovery time and its impacts on demand.

A three-staged approach was used for this study. In Stage 1, a nationally representative sample of 1000 rail customers in Great Britain was surveyed online to understand their awareness of recovery time. These surveys identified differences between their scheduled and perceived actual travel times for a recently made journey, passengers? perceived benefits of earlier than scheduled arrivals, and broad preferences between recovery time and journey time reliability. Stage 2 of this study used focus groups to gather additional insight into passengers? awareness of recovery time. Finally, a stated-preference analysis was carried out to understand passengers' valuation of recovery time and its comparison with other factors (including reliability) that drive rail demand, and are commonly aggregated in a composite generalised journey time measure.

The paper briefly reviews the Passenger Demand Forecasting Handbook (PDFH) methodology for forecasting rail demand, highlighting the different factors that comprise generalised journey time and their relative valuation. It then discusses the three-staged methodology in detail and presents the results.


Association for European Transport