As we welcome passengers back to the railway, we need to understand the impact of increasing numbers and continued social distance to better manage network performance. Good performance will play a key role in rebuilding passenger confidence in the railway.

Watch our short video about the impact of social distancing on network performance.

RSSB, in collaboration with the University of Sheffield and Risk Solutions, led novel research into modelling the effects of social distancing at stations and on platforms, particularly at the Platform Train Interface (PTI). This work merged two tools: 

  • RateSetter, a pedestrian modelling tool focussed on design-solutions to PTI, platforms and station challenges
  • SaviRPM, a performance model that can quickly test new timetables, identify pinch points and suggest changes to enhance feasibility, robustness and resilience.

Ratesetter showed that, not surprisingly, social distancing increases the boarding and alighting time. But the question is: could this impact dwell times and cause potential delays on individual train services? Also, could this lead to cascading delays across the rail network?

To answer this question, we turned to SaviRPM to identify where and how risks might emerge. 

Our analysis concluded that: 

  1. The impact of social distancing is larger for more heavily loaded doors (those with more than 10 passengers boarding and alighting). Therefore, as passenger number increases and if social distance is followed, the impact is likely to increase. 
  2. Longer boarding and alighting time is likely not to be a widespread risk, but localised at certain ‘hot spots’. These ‘hot spots’ are stations characterised by timetabled dwell times of 1 minute or less.
  3. The impact on overall service performance using the CP6 metric (>1 min late) will vary for different operators, routes and service groups. However, the impact is larger on frequently stopping local or commuter services with shorter timetabled dwells. Based on the modelling these can experience in the range of 2% to 7% fewer on-time service stops averaged across a full 24-hour period.

This preliminary modelling and data analysis show that the overall performance impact at a system level is not large, in the region of 1.5% on average. However, there may be circumstances that cause more significant impact at a local level or for particular service groups. 

Therefore, although timetables do not need to be altered necessarily, operators are advised to continue to gain better intelligence of their network by collecting data and understanding where localised conditions might occur. 

Operators are invited to contact us if they have an interest in a tailored analysis of their network to assess the ‘hot spots’, times of day and periods of the year where social distancing may cause performance issues as passengers return following the lifting of COVID lockdown restrictions.