One of the most notable impacts that global lockdowns have had on society is a restriction on travel: both modes of travel and frequency of travel. Companies like Google and Citymapper, a public transit app and mapping service, have created tools to better understand the changes in mobility that have occurred, since Covid-19 started. These tools allow us to understand the depth with which people’s lives have been forced to change and are likely to provide deeper insights into how mobility within cities will be different once the pandemic passes.
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Google’s Community Mobility Reports were created to inform us about the movement trends that have emerged in the past few weeks and how these trends have impacted retailers, workplaces, residential areas and recreational activities. The report for the UK can be found here. As expected, movement through transport stations, such as trains and buses, has declined by an average of 75% in the UK1. The Citymapper mobility index dashboard, found here, shows the slowdown in travel in cities across the world. In the UK, only 9% of people in London and 9% of people in Manchester are currently moving2. If you compare this to 3 weeks ago, where 83% of Londoners and 89% of Mancunians were moving, the contrast is stark.
The true power in this data, however, lies in its ability to be integrated with other data sources that track mobility and movement. We know that Citymapper is sharing this transit data with the government to help them track transport use. The government have also met with telecom providers to discuss a collaboration to give them access to mobile device locations of tens of millions of citizens, which could help them to track the movement of crowds and identify trends in the spread of Covid-193.
Whilst the government’s sole intended use of this location data is to stop the spread of Covid-19, it would be remiss to ignore the potential of this data for other use cases, such as transportation within cities. Data of this quality and magnitude has the potential to inform policy decisions regarding the future of transportation – a key topic in the smart cities space. Just last month the Department for Transport launched the ‘Future of transport regulatory review’, which aims to make mobility easier, smarter, and greener in the future through the introduction of new technology. The review will focus on three key areas: micromobility vehicles (recently legalised e-scooters for use on public roads), flexible on-demand bus services (think ordering a bus like you would an Uber) and mobility as a service (MaaS).
Although government and local authorities will have scores of data on how their citizens currently move about their community, imagine the impact that mobile location-based data could have on targeting the most relevant parts of a city that would see the greatest benefit from deploying some, or all, of the above initiatives. Derby and Nottingham, for example, have received a grant of £15 million to invest in ‘mobility hubs’ to promote the uptake of alternative travel methods such as car club hire, bike-sharing and vehicle charging points. If they could combine their existing data with mobile phone location-based data, they would be able to create an incredibly accurate picture of how, and where, people move around a city on a daily basis. This in turn could influence the locations of these mobility hubs as well as inform future transport-related decisions.
Ultimately, in order to be able to holistically understand the true benefits and costs of each new transport product or service, authorities need to have access to varied and robust data that accurately depicts the movement trends of the population. Location-based data, such as the data stored by telecoms companies, is invaluable due to its accuracy of depicting social movement.
Whilst all data privacy implications cannot be ignored, access to relevant, location-based data to inform operational models should play a key role in the future of transport regulatory review.
- As of 29 March 2020
- As of 5 April 2020
- Government Telecom location data