Depersonalised Wi-Fi connection data from London Underground customers’ mobile devices could be used to better understand how people navigate the Tube network, supporting efforts to reduce crowding and prioritise investment.
This was the key finding of a four week pilot study run by Transport for London at the end of last year, results from which have now been released.
The trial ran between November and December and focused on 54 stations within Zones 1-4. It saw more than 509 million depersonalised pieces of data collected from 5.6 million mobile devices making around 42 million journeys.
These journeys were analysed by TfL and broken into different aggregated ‘movement types’ to help understand what people were doing at particular points of their journeys – be its entering or exiting a station, changing between lines or just passing through the station while on a train.
In doing so TfL was able to get a much more accurate understanding of how people move through stations, interchange between services and how crowding develops.
The pilot revealed a number of insights that could not have been detected from ticketing data or paper based surveys. For example it showed that customers travelling between King’s Cross St Pancras and Waterloo take at least 18 different routes, with around 40% of customers observed not taking one of the two most popular routes.
It is thought that the data collected through the pilot could bring a number of benefits for TfL and its customers. These include helping customers to plan a route that best suits them – whether based on travel time, crowding or walking distance – and enabling greater sophistication in providing real time information.
It could also help to further prioritise transport investment to improve services and address regular congestion points, ensuring focus is placed on where the maximum benefits to customers can be realised.
TfL has now begun discussions with key stakeholders including the Information Commissioner’s Office, privacy campaigners and consumer groups about how this data collection could be undertaken on a permanent basis, possibly across the full Tube network.
“The analysis of secure, depersonalised Wi-Fi data could enable us to map the journey patterns of millions of passengers and understand in much greater detail how people move around our transport network,” said Deputy Mayor for Transport Val Shawcross.
“It will provide real benefits helping TfL tackle overcrowding, provide more information for passengers about their best journey route, and help us prioritise new investment where it’s most needed.”
Trade association techUK’s head of programme for cloud, data, analytics and AI Sue Daley added: “The transparency and openness shown by TfL is to be applauded. The steps taken to make customers aware of the data collection and its purpose should be seen as a blueprint for others.
“If UK organisations are to realise the full potential of real time data driven decisions, it is vital that we bring the public on this journey by building a culture of data trust and confidence.”
TfL ensured that all the data collected was depersonalised so that no individuals could be identified, and no browsing data was collected from devices. No data was made available to any third parties and the pilot also included clear communication with customers about how to opt out.