Innovative pilot shows how WiFi data can improve journeys across the Tube

WiFi data could be used to improve tube journeys and provide customers with more information as they move around London, new research has shown.

The four-week Transport for London (TfL) pilot, which ran between November and December 2016, studied how depersonalised WiFi connection data from customers’ mobile devices could be used to better understand how people navigate the London Underground network, allowing TfL to improve the experience for customers.

The pilot focused on 54 stations within Zones 1-4 and saw more than 509 million depersonalised ‘probing requests’, or pieces of data, collected from 5.6 million mobile devices making around 42 million journeys.

The data collected was depersonalised, so that no individuals could be identified, and no browsing data was collected from devices. No data collected through the trial was made available to any third parties, and the pilot included clear communication with customers about how to opt out should they wish to do so.

These journeys were analysed by TfL’s in-house analytics team and broken into different aggregated ‘movement types’ to help understand what customers were doing at particular points of their journeys – such as entering or exiting a station, changing between lines or just passing through the station while on a train.

By using this data, TfL was able to get a much more accurate understanding of how people move through stations, interchange between services and how crowding develops.

The data collected through the WiFi pilot could have a number of benefits for TfL and its customers, including:

• Allowing staff to better inform customers of the best way to avoid disruption or unnecessary crowding;
• Helping customers plan the route that best suits them – whether based on travel time, crowding or walking distance;
• Enabling greater sophistication in proving real-time information to customers as they travel across London;
• Helping further prioritise transport investment to improve services and address regular congestion points – ensuring the maximum benefits to customers;
• Providing a better insight on customer flows which could increase commercial revenue from companies which advertise or rent retail units on the transport network.

While the usual ticketing data for major interchange stations such as Oxford Circus can show the levels of people entering and exiting the stations, it cannot show the huge numbers of people interchanging during peak hours, or precise local areas where crowding occurs on platforms or around escalators, whereas WiFi data can.

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 WiFi 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. 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,” commented Val Shawcross, Deputy Mayor for Transport.

Sue Daley, Head of Programme for Cloud, Data, Analytics and AI, techUK, noted:

“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.”

For more information, and to download the full report, please visit tfl.gov.uk/corporate/publications-and-reports/wifi-data-collection