The rate of urbanisation and congestion continues to rise. Yet as we look to develop our cities and shape our roads to accommodate this rise, traditional methods of collecting data on travel and building new infrastructure are at odds with sustainable goals, which instead seek to fulfil a ‘refurb over rebuild’ approach to meet this demand.
Not only do we need to facilitate more active travel modes and improve public transport reliability and uptake (while also reducing emissions), but also enhance connectivity and data between travel modes and understand its connection with other factors such as air quality and road safety.
But the technology that can address these issues is already at play. Real-world trials of AI and smart junctions have demonstrated a 23% reduction in journey times across a single junction. It signals a major step forward in creating the ability to optimise traffic flow without having to build more infrastructure or lay more tarmac. It’s ‘reimagining over rebuilding’ – and it’s making the future a reality.
Reducing congestion and emissions
Tackling congestion requires a collaborative effort. One that joins technological advancements such as smart junctions with schemes and campaigns that simultaneously encourage behaviour changes and introduce physical changes – driven by data – to enable such change.
Park and ride schemes have long been a method for encouraging public transport use in cities. For example, in Bristol, parking sites are located at four corners on the outskirts of the city. Parking is free, and you only pay the bus fare into the city. This concept has been joined by newer initiatives that look to tackle the problem within cities themselves with a more targeted approach. London has recently expanded its ULEZ and continued its roll-out of ‘Low Traffic Neighbourhoods’ and the School Streets scheme, with the intention of prioritising active travel modes and limiting private vehicle use.
However, such schemes can only have an effect up to a certain point. Rather than just implementing physical changes, such as widening roads and building cycle lanes, we need to find new sustainable ways of reusing existing infrastructure. To unlock the true environmental, economic and societal value from reducing congestion and emissions, advanced techniques, sensors and intelligent transport systems are needed to gain a detailed insight into travel trends and optimise traffic flow.
The rise of smart junctions and AI: how its role is becoming integral for the transport sector
SCOOT and MOVA have dominated traffic signal control in the UK for the past few decades. While both have scenarios in which they work effectively, reducing congestion through coordination of multiple junctions (SCOOT) or optimising individual junctions (MOVA), they have both experienced limitations when optimising signal timings to improve air quality or to help other modes of transport. And this has become increasingly significant.
What’s needed is a system that is able to prioritise key modes like cycling, pedestrians and buses and is inherently designed to improve air quality (or has the capability to do so). The ability to create such a multi-modal system has accelerated the introduction of AI into the transport sector, a technology that has been long established in sectors such as retail, marketing and fast finance.
Next-generation intelligent traffic control systems, such as smart junctions, are using AI-powered sensors to anonymously visualise, classify and respond in real time to all types of road users, from cars and buses to pedestrians and cyclists (and everything in between). This data includes counts, speed, pathways and travel patterns. For context, data is sent to an AI-based deep learning algorithm that optimises the signal timings and sends the commands and requests to the traffic signal controller, resulting in a system that can optimise signals and traffic flow accordingly for all road users.
Real-world applications of smart junctions
How has this technology panned out on the roads? Real-world trials have demonstrated a 23% improvement in journey times, and shown that AI can be used to improve existing systems. This improvement in journey times equates to 13 seconds. But how does 13 seconds play out on our roads? What does it look like? And what does that mean for travel?
Thirteen seconds is a long time at a junction. If a user crosses ten junctions, they are saving 130 seconds in journey time – over two minutes. And that’s just at the junctions. Journey times between each junction are subsequently further quickened. The domino effect of speeding up every journey means systems will adapt, improve and further quicken journey times.
Less stopping, stalling and braking at lights mean lower emissions. Faster public transport and active travel prioritisation increase its use and, likewise, reduce emissions. This is only a brief overview, but it highlights the vast potential of change that can be delivered if adopted successfully.
The road ahead
Integrating this technology and connectivity infrastructure opens up an array of benefits. A key asset of this is the power to connect with other innovative players and technology. The Breathe London network, for example, offers affordable and easy-to-install and maintain air quality sensors to anyone in London. These could be combined with other, more advanced sensors, such as Vaisala’s weather and environmental measurement products, to generate a hub of air quality data.
The sensors can then be set up with intelligent traffic systems to understand the correlation between air quality and congestion in specific areas and junctions, for example. This enables a wealth of accurate, detailed, real-time, 24/7 data that can then be fed back into AI systems, helping to plan everything from signal timings and prioritisation to air quality.
This only scratches the surface of the possibilities for what different types of connected technology could offer. The increasing availability of such data will allow new players into the field, ushering in GovTech start-ups who will leverage the latest in technology to do things we can’t yet imagine. Who knows where this could lead. For now, the key to realising this ambition is delivering a vastly improved traffic signal system and network through the power of smart junctions and AI.
