Many of us share a similar experience in our daily commute, the annoyance of driving on a busy route.

Our roads overflow with vehicles, motorists weaving through traffic and pedestrians switching pavements. It’s the typical urban chaos that often leads to frustrating traffic jams.

But what if this scenario could be transformed into a smoother, more efficient experience, thanks to artificial intelligence (AI)?

This is not science fiction and can be achieved using the Digital Traffic Brain. Let’s start with the most visible element on our roads – the traffic lights.

Traditionally, traffic lights follow a set pattern, often leading to unnecessary waiting even when the roads are clear. Enter AI-powered traffic lights, a technology revolutionising how we navigate our city streets. These intelligent lights use a combination of cameras and predictive algorithms to adapt in real time to traffic conditions.

A study by Carnegie Mellon University in the United States highlighted the effect of this technology, indicating a 40 per cent reduction in idling time, a 20 per cent reduction in vehicle emissions and a 26 per cent decrease in overall travel times across the city. However, the scope of AI in traffic management extends beyond just controlling individual intersections.

The more expansive concept of road network optimisation leverages AI to scrutinise and understand traffic patterns. This ensures a smoother traffic flow, particularly for public transport and emergency vehicles, enhancing their appeal to commuters.

AI achieves this by integrating data from various sources, including cameras, sensors and GPS devices, to provide a comprehensive approach to traffic management. This not only optimises traffic flow but also significantly reduces congestion.

Moreover, an efficient and reliable public transport system facilitated by AI will reduce the number of private cars on the road. As public transport becomes more efficient and reliable, it becomes a more attractive option for commuters.

This shift from private car use to public transport can significantly reduce traffic volumes, further alleviating congestion while contributing to a more sustainable and environmentally friendly transport system.

The utility of AI in traffic management extends far beyond just controlling the flow of vehicles. It can revolutionise how we respond to incidents on the road, significantly reducing response times and minimising traffic disruptions, an issue that the prime minister highlighted in a recent interview. Consider a minor accident, for instance. Even in such cases, much time is spent in the aftermath. The involved parties often get out of their vehicles to dispute the incident, further blocking the traffic. Then, they must call local authorities and wait for them to arrive.

Implementing AI to guide drivers towards vacant spots saves valuable time and reduces traffic congestion

During this time, traffic continues to accumulate, leading to significant delays. Moreover, people often find themselves trapped on accident-affected roads without alternate escape routes.

Now, imagine a system where AI processes data from cameras, quickly detecting and responding to such incidents. As soon as an accident occurs, the AI system will immediately alert local authorities, even before any of the involved parties have a chance to make a call. This could significantly reduce the waiting time for the authorities to arrive at the scene.

Furthermore, the AI system will analyse the traffic situation in real time and suggest alternate routes to drivers approaching the accident site. This could prevent them from getting trapped in the traffic caused by the accident.

Such a system can save thousands of hours wasted in traffic and significantly improve the overall efficiency of our transportation systems.

Predictive analytics plays a pivotal role in anticipating traffic patterns. By scrutinising historical data, AI can accurately forecast peak traffic periods, empowering city planners to make strategic changes. This forward-thinking approach also benefits individual drivers, particularly those who rely on popular navigation apps such as Waze or Google Maps.

Incorporating real-time traffic data into these apps can significantly streamline commuting. According to a study conducted by McKinsey, integrating such data can reduce commuting time by up to 15 per cent.

This substantial reduction is achieved by assisting drivers in avoiding traffic congestion, making their journeys quicker and more efficient.

Once you reach your destination, AI plays a pivotal role, not just in traffic flow but also in parking management. AI’s real-time analysis of parking spots significantly reduces the time spent cruising for parking. In fact, studies suggest that in busy urban areas, drivers spend an average of 17 minutes searching for a parking spot.

Implementing AI to guide drivers towards vacant spots saves valuable time and reduces traffic congestion, making urban commuting more efficient and less stressful. This innovative use of AI in parking management is a critical component in the broader vision of creating intelligent and more accessible cities.

The Digital Traffic Brain presents a transformative solution to the age-old problem of urban congestion, harnessing the power of AI to streamline our daily commutes. By intelligently predicting traffic patterns and managing traffic, this system not only enhances the efficiency of our roads but also contributes significantly to environmental sustainability by reducing emissions.

This approach represents a paradigm shift towards a more interconnected and responsive urban transport infrastructure. As we embrace the future, the Digital Traffic Brain stands as a beacon of innovation, paving the way for smarter cities where congestion is a challenge of the past and efficient, eco-friendly travel becomes the norm.

Alexiei Dingli is professor of artificial intelligence.