Efficient urban transportation is the lifeblood of any modern city.
Where trams, trains and buses prove faster and easier than car travel, those in metropolitan cities depend on streamlined public transit for their everyday life.
However, in some cases, delays and cancellations are the norm, and inner-city traffic jams have become an accepted part of life.
Transport for Greater Manchester (TfGM), wants to change this. In a city with a worker bee as its icon, the buzzy centre is optimising with AI to ease traffic flow, make public transportation more seamless and communicate it to its users.
Working with AI traffic monitoring firm VivaCity, TfGM has installed over 100 camera sensors at junctions across the region to gain deeper travel data insights into the city.
While existing sensors beneath junctions can detect when an object moves across them, the new cameras leverage AI and machine learning to identify the exact type of object—be it a bike, car, lorry, or pedestrian—and communicate with each other via a 5G small-cell network.
Traffic lights at these ‘smart junctions’ can then reduce congestion and carbon emissions by responding more quickly to real-time traffic conditions.
“As a result,” explains Malcolm Lowe, CIO for TfGM, “a smoother traffic flow means vehicles aren’t idling and emitting carbon dioxide.”
During the COVID pandemic, when bicycle usage surged, these smart junctions proved particularly valuable by recognising and prioritising cyclists and pedestrians when necessary.
Now, TfGM can also collect comprehensive data on the types of traffic moving through the region, whether it’s bikes or cars, and potentially adapt roads to better suit people’s transport choices.
This week Transport for Greater Manchester (TfGM) has taken another step towards its digital transformation by partnering with public transport optimization platform CitySwift to use its AI and data analytic technologies.
As part of an ambitious plan to bring the entire regional bus network under local control by 2025, TfGM is hoping to completely integrate and optimise its ‘Bee Network’.
“This is one of the most significant transformations in public transport in 40 years,” said Lowe, highlighting the changes ahead. “We can start to take control of the bus network and create something called the Bee Network.”
Using AI technology, TfGM will analyse travel patterns and fine-tune timetables to eliminate delays, “so you don’t get that issue of having two or three buses turning up at the same time.”
Additionally, AI and data will ensure bus, tram, and train schedules are coordinated, creating a seamless journey for commuters.
“Our vision is to make the Bee Network an integrated transport system,” said Lowe.
“We aim to get more people using public transport, cut down congestion, and push for sustainability.”
The Bee Network aims to grow bus use by around 30% by 2030 – or about 50 million additional bus journeys annually – which it hopes will be made possible when users can confidently rely on a frequent network.
“It’s all about sustainability, and helping users get from A to B,” says Lowe. “Many people rely on public transport for school runs, work commutes and hospital visits, so it’s helping make their lives easier.”
By using data from monitoring ticket sales, TfGM will also pinpoint busy times and roll out additional services when they’re needed most.
“Customers are at the heart of the Bee Network and by working with CitySwift we will be able to see more clearly than ever how services are performing,” says Catherine Towey, senior lead for bus franchising at TfGM.
“We can then use this information to prioritise improvements and deliver a better service for passengers.”
Moving forward, Lowe imagines opportunities to digitally advance its current transportation application, ‘the Bee Network app’ to include a generative AI chatbot that can answer simple queries.
“People crave information, so if you’re able to tell them a bus or a tram has been disrupted, an AI could measure this and provide an alternative route,” suggests Lowe.
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