The rise of artificial intelligence and machine learning means public transport is achieving new levels of efficiency and safety, encouraging people out of their cars.
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By Johnny Sharp
If you could sum up public transport systems in two words, ‘organised chaos’ might be as apt as any. Managing the flow of millions of people and vehicles, all heading in different directions at different speeds, has always been a major challenge – but modern technology is here to help.
Among many innovators working on artificial intelligence (AI) projects across the country, engineers at Imperial College London are currently partnering with Cubic Transportation Systems to develop AI techniques analysing ‘irregular domains’ such as the London Underground network where multiple ‘nodes’ (stations) stand in inconsistent relationships with one another, attracting different passenger flow and connectivity features.
Image: Willesden Green station, London, Credit: Shutterstock.
A new centre is set to open in September at Cubic’s Surrey HQ, creating an immersive ‘tube station of the future’ in which to trial new technologies. “This collaboration is an opportunity for us to develop the transportation experts of the future,” said project leader, Professor Danilo Mandic. “Our students and researchers will be working closely with Cubic to harness the latest innovations in technology to solve transportation’s most significant challenges.”
AI is already all around us on our travels. We often benefit from machine learning (ML) in our private vehicles, from sensor systems and road positioning alerts to predictive features flagging imminent upgrades our cars require. The latter feature is increasingly being introduced to buses and trains to plan the best opportunities for running repairs and thereby reduce downtime.
In February last year, AI-enabled cameras were employed by Transport for London on the Tube network to create a ‘smart station’ at Willesden Green in North London, identifying various activities and issues, from discarded items on platforms to passengers standing too close to the platform edge. Information was then relayed via tablets and smartphones to station staff, enabling them to react more quickly.
Other details that may seem trivial also proved significant, as cameras were primed to spot raised arms, suggesting distress or potential violence. The cameras could even detect weapons from live video footage. On a more positive front, ‘intelligent’ cameras could alert staff to wheelchair and pushchair users that may need assistance.
A similar trial at Blackhorse Road station on the Victoria Line monitored ticket barriers, adjusting them according to passenger flow. The trial concluded that if all barriers were automated, queue times could be reduced by up to 90 percent. All of which helps public transport to become a more attractive prospect for commuters, promoting modal switch to help decarbonisation.
Potential commercial benefits have also been targeted. The Irregular Travel Analysis Platform (ITAP) has been employed by TfL to analyse journey and ticketing data to identify common fare evasion tricks and potentially identify and prosecute repeat offenders. While privacy issues remain a concern, if crime can be combatted with the use of AI camera data, everyone benefits.
The potential for other forms of public transport is also considerable. With AI-enhanced traffic management already in place in our towns and cities, schedules can be updated more accurately in real time and fewer stops made by buses, for instance.
Significant safety improvements can also be achieved through ML algorithms, fine-tuned to pinpoint potential accidents based on driver behavioural analysis, weather and road conditions, among other factors.
Whether passengers will notice these innovations as they travel around remains to be seen, and it may be no bad thing if they don’t. AI at its best has the potential to quietly and unobtrusively improve our public transport experience without placing any unwanted obstructions in our path. Unless you want to dodge your fare – then you’ve got your work cut out.
Download CIHT’s report on AI, ‘The role of data and artificial intelligence in achieving transport decarbonisation’.
Image: Willesden Green station, London, Credit: Shutterstock.
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