- New data has allowed TfL to update Journey Planner to reflect more accurately the time it takes to travel through stations during busy periods
- More than 2.7 billion depersonalised pieces of data analysed already, allowing TfL to understand in greater detail how customers move across the network
- Work underway to improve data around crowding at platform level to help customers consider alternatives before they travel
- Changes are part of TfL’s wider improvements to customer information which will be delivered within the next 12 months
Transport for London (TfL) has implemented the first improvements for customers following the start of collection of Wi-Fi connection data earlier this year.
The 2.7 billion pieces of depersonalised data that have been analysed so far have allowed TfL to update Journey Planner to more accurately reflect the time it takes to travel through stations. Through collecting data TfL has gained a greater understanding of the routes people take across the network, where they interchange and how long people may have to wait at certain points along their journey due to crowding or maintenance work.
TfL’s in-house data scientists worked through the data and identified a number of instances where the length of time to travel through a station was greater than the time previously allocated on TfL’s Journey Planner. TfL has now adjusted Journey Planner timings for journeys involving 55 stations. The changes, which will also be reflected in the Journey Planner open data in TfL’s free Unified API, include:
- At major interchange stations like Baker Street, Canada Water, Earl’s Court and Notting Hill Gate, the time to interchange between lines has been adjusted to better reflect busy times at the stations. Historically, TfL has relied on customer surveys to understand the flow of movement through a station. Using depersonalised Wi-Fi data provides a more accurate understanding of how people interchange throughout the day.
- At high tourist areas like Bond Street, Covent Garden, Leicester Square and Piccadilly Circus, times have been adjusted to take account of higher usage outside of peak periods due to theatres, museums and other leisure activities nearby.
- At stations towards the end of Underground lines in outer London, times have been adjusted to take account of increased passenger numbers.
The improvements to TfL’s Journey Planner will benefit all customers, including people with accessibility needs, as it will help provide clearer journey times and identify the quickest or most convenient option, especially for those who require a step-free route. Following these changes, TfL will continue to analyse the depersonalised Wi-Fi data and make additional changes to Journey Planner should they be required in the future. Work is also underway to see what further information can be sourced from the depersonalised Wi-Fi data to help provide further benefits to customers. These include understanding where customers interchange on certain key routes in London, such as King’s Cross St Pancras to Waterloo and Liverpool Street to Victoria, to see whether better alternatives could be suggested at certain times to help customers find their best route.
The aggregated data is also being prepared for use by TfL’s planning teams, who will use the better understanding of customer flows throughout stations to help identify improvement opportunities and target investment in the transport network. The aggregated data is also being used by TfL’s advertising partner, Global, to improve where it positions advertising to help raise revenue for reinvestment in the transport network. The aggregated data will also be used in the future to help highlight the effectiveness and accountability of the advertising estate, based on measured footfall, which should also improve commercial revenue.
The data collection, which began on 8 July 2019, is harnessing existing Wi-Fi connection data from more than 260 Wi-Fi enabled London Underground stations. All data collected by TfL is automatically depersonalised to ensure that it is not possible to identify any individual, and no browsing or historical data is collected from any devices.
Lauren Sager Weinstein, Chief Data Officer at Transport for London, said: “Our lives are now more data-rich than they have ever been and therefore we are working to use this data to allow our customers to better plan their journeys and find the best routes across our network. These changes to our online Journey Planner using depersonalised Wi-Fi data collection is just the start of wider improvements we are hoping to introduce which will provide better information to our customers and help us plan and operate our transport network more effectively for all. As we do this, we take our customers’ privacy extremely seriously. It is fundamental to our data approach and we do not identify any individuals from the Wi-Fi data collected.”
The changes to Journey Planner are part of a wider set of improvements to how live travel information is shared with customers planned by TfL in the coming 12 months. TfL has a number of ways which customers can find up to date travel information, including the TfL website, social media channels, or via hundreds of apps powered by TfL’s free open data feeds. TfL has recently begun improving the way data is shown on the status boards within stations to help make it easier for customers to see whether lines which serve their specific station are affected by any delays or planned closures.
Customers can also set up ‘Favourites’ to easily access live travel information on the TfL website, as well as use online Travel Tools such as Status Updates and Live Arrivals for stations, stops and piers. Further improvements to TfL’s website and free open data Unified API are also expected to be made in the coming months, including providing better live accessibility data to customers as well as incorporating real-time information for journeys on TfL-operated rail services within Journey Planner.
For more information about TfL’s Wi-Fi data collection programme, please visit https://tfl.gov.uk/corporate/privacy-and-cookies/wi-fi-data-collection