Mobile Network Data – Rail Station Incident
|Contract||Vauxhall Station, London – Study by Tracsis Partner, Citi Logik|
|Service||Passenger flows and disruption surveys|
|Scale||A 10,000-passenger sample which commute regularly to London by train via Vauxhall station|
|Project Location||6 key London rail interchange points affected by a fire at Vauxhall station|
In 2014, there were 1.65 billion journeys on the National Rail network, making the British network the fifth most used in the world (Great Britain ranks 23rd in world population). With just under 100 million passenger entries and exits between April 2013 and March 2014, Waterloo is Britain’s busiest railway station by passenger usage.
A fire at London’s Vauxhall interchange station caused major disruption for customers travelling into Britain’s busiest railway station. Network planners asked Citi Logik to analyse the effects on passenger flows.
On a normal commuting day, Waterloo and the London rail interchange system is crowded but works reasonably well, however, disruption to any station in this network can have serious knock-on effects. On 5 May 2016, a fire at Vauxhall station caused major disruption to passengers on one of the major routes into Waterloo. In response the team at Tracsis’ partners Citi Logik were challenged with examining the impact of the fire on commuting patterns to assist with planning and responses to similar events in the future.
In partnership with Tracsis, Citi Logik has unique access to anonymised Mobile Network Data from the 3/4G network which allows it to create comprehensive and high value understandings of the urban environment. This capability is genuinely innovative, capturing anonymised and aggregated information from millions of ever-moving SIM cards (mobile phones), facilitating analysis across the city, every minute of every day, for every major road, rail route and pedestrian walkway. Citi Logik complies to the highest global standards of data protection and individual privacy.
By utilising historic anonymised Mobile Network Data, Citi Logik ‘s technology was able to identify an anonymised sample set of 10,000 people that commute regularly to London by train via Vauxhall station. It then used three parameters to analyse this data to assess the disruptive impact on these passengers of the fire on 5 May against days where the rail network was operating normally.
By using anonymised Mobile Network Data, Citi Logik could create a representative view of passenger movements on the day of the Vauxhall fire when compared to a normal working day. We provided this with no need to install any physical infrastructure or having any interaction with passengers, enabling us to deliver disruption-free meaningful results. Our data demonstrated that many people chose not to travel on the day of the Vauxhall fire. For those passengers who did, it was clear that their journeys were disrupted and the impact on key individual London stations was clearly demonstrated.
The graph below of Victoria station passenger traffic shows a large increase in those who normally commute through Vauxhall switching to Victoria station as an alternative on the 5th May when compared to other working days. Additionally, the AM and PM peaks are both offset to the right, demonstrating delays on the inbound journey and people choosing to travel home later in the day to make up time at work, or staying late to avoid the peak period.
Rail network operators now have a good understanding of the ‘knock on effects’ of disruption at the Vauxhall interchange point during rush hour and can take actions to add additional resources and measures to assist with increased passenger flows at alternative interchange points in a timely manner. Following the success of this assignment in analysing historic rail passenger movements, the Citi Logik team are now working with partners Tracsis to investigate the best ways to utilise Mobile Network Data to prepare for future disruptive events, both pre-planned (such as engineering works) and unexpected (such as fire like the one at Vauxhall).