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BBA 2020 Winner Profile: UK–Japan Partnership – The Alan Turing Institute/Toyota Mobility Foundation
Written by Sterling Content
December 11, 2020
British Business Awards
A collaboration between The Alan Turing Institute (the Turing), the UK’s national institute for data science and artificial intelligence, and the Toyota Mobility Foundation (TMF), a Japanese non-profit advancing mobility for all, has been recognised by the British Chamber of Commerce in Japan (BCCJ).
Representatives of the organisations accepted the British Business Award 2020 (BBA) in the category of UK–Japan partnership at the BCCJ’s virtual gala on November 5. The partnership was recognised for providing innovative and equitable solutions to some of the world’s most pressing mobility needs.
The Turing and TMF are united by a common vision, to solve real problems for social good. The partnership says that “no matter the challenge—environmental, economic or social—mobility is at the heart of living better, which is why we are working together to uncover efficient and small solutions to keep us all moving forward.” International by design, the collaboration has produced outcomes that can be localised to meet the needs of cities worldwide.
Will Taylor, research project manager for urban analytics at the Turing, and William Chernicoff, head of research and innovation at TMF, say that receiving a BBA is sure to help the partnership achieve its mission. In addition to motivating the team, it has validated and raised awareness of the partnership’s work.
“Greater visibility [as a result of the BBA] could lead us to other connections, cities and partners that might want to get involved in some way,” says Taylor. “It could even spark ideas in other people, creating other meaningful partnerships that can solve societal problems.”
Chernicoff agrees, noting that the collaboration operates under the approach that “a rising ocean lifts all boats.” Receiving a BBA for efforts to improve mobility can help the pursuit of improved mobility for all, globally.
“Awareness helps us achieve our objectives. We don’t want [our work] to be a tree falling in a forest that no-one hears,” he says. “Innovation doesn’t come from the creation of technology. It comes from the use and adaption of that technology to help society.”
Building on a pilot project
The collaboration between the Turing and TMF was established in April 2018 following the realisation that both parties shared a synergy and mission while offering complementary skillsets. Shortly after, an 18-month pilot project was launched “to transition complex traffic management from static systems with limited human intervention to a dynamic, system-wide, real time-managed and optimised system across multiple travel modes.”
Under the premise that a city that moves more efficiently can do more for the people in it, the team worked on three streams: the creation of a mobility data toolkit, the application of artificial intelligence (AI) to optimise traffic light timings in real-time across the entire system, and the development of models of human behaviour to better understand how and why people change how they travel.
The mobility data toolkit is essentially a dashboard powered by AI that allows traffic managers to easily visualise their data and respond in real-time. It also predicts ever-changing needs and behaviours due to factors that impact personal choices like weather, events, emergencies, infrastructure and evolving mobility options.
Data is collected via many sources and, through repetition, the AI learns how to respond to different traffic demands. At the same time, user-choice modelling accounts for the decisions people make based on their needs and circumstances, for example how the availability of cheaper rideshare services might affect the use of public transit.
The combination of reinforcement learning and modelling helps traffic managers make better decisions during times of high demand and heavy congestion such as the end of a match or the onset of inclement weather. Traffic managers can even utilise “intelligent” intersection lights that display the most appropriate signal for a particular time and place and coordinate with all traffic signals in the area.
In short, the toolkit provides visibility of current and upcoming situations as well as how new factors could impact the way people move.
At the Turing, says Taylor, mobility is classified as “a big, small problem” due to its complexity. It is “big” because it is “cross-cutting and deals with societal issues, not just narrowly defined problems” and “small” because it extends to a granular level requiring local know-how, such as how to address “one pensioner waiting at a bus stop in a suburb.”
Few organisations can tackle such a problem. According to Chernicoff, the toolkit has filled a gap in research on mobility. To date, studies have created outcomes that optimise what happens at a single intersection but not what happens on the roads that feed into, or are parallel and perpendicular to, that intersection.
The toolkit, however, can address the thousands of linked intersections and mobility modes, offering hope that some of the world’s toughest mobility challenges can be solved. Moreover, it is accessible even to cities with limited resources.
“Before, only big cities could employ a team of data scientists to do this sort of analysis. The toolkit should level the playing field,” says Taylor.
With the completion of the pilot project at the end of 2019, the partnership embarked on a second project focused on refining the mobility data toolkit. In the past 12 months, the work has reached important milestones, including demonstration of the toolkit.
“We’ve turned abstract ideas into something that allows us to talk to cities and municipalities and have meaningful impact,” says Chernicoff.
Taylor looks forward to welcoming more implementation partners. Working with all kinds of cities allows the toolkit to “handle many different types of problems,” which is important for its development.
Long-term, the Turing and TMF hope to continue to build on their partnership and learn from one another. The Turing is bringing its strength in collaboration, convening and interdisciplinarity to the project.
For example, lessons from an unrelated project run by the Turing to understand how autistic people experience various public spaces have been applied to the partnership to “make sure that the tools we make are inclusive from the outset, rather than an afterthought,” according to Taylor.
As for the toolkit, the partnership is passion about its further development, so it can help people move around better, improving the quality of their lives.