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The Role of Artificial Intelligence in Revolutionizing Road Safety 

Data-Driven Paths, Safety that Lasts – when we talk about Artificial Intelligence (AI) in traffic, most of us think of autonomous driving vehicles. But this is just one example of where this technology can be adopted. And it shouldn´t be the only area, as a vehicle cannot see around corners or behind obstacles, for example. Imagine this scenario: It is early morning, still dark outside, school is about to begin. A group of kids is walking to school. There is running and laughter. While they play around, everything seems important except the traffic around them. The first group crosses the street. The stragglers follow. Have they checked to see if the light is still green? Have they watched out for cars? Will the cars see the children? Clearly, it is better to be safe than sorry. This is where intelligent infrastructure comes in. 

Smart traffic infrastructure leverages data to manage and optimize traffic flow based on AI algorithms. For example, to extend green phases of traffic lights, when vulnerable groups are detected. Sensors, cameras, GPS, and other IoT devices gather real-time data about traffic conditions, including vehicle counts, speed, congestion, and weather conditions. Not to mention the fact that all road users can be recognized and distinguished, for example pedestrians, cyclists, wheelchair user and elderly people. The collected data is processed and analyzed to identify traffic patterns and potential risk situations. Based on the data, traffic flow can be adjusted, for example, by extending the duration of green lights, or warning messages can be sent to vehicles. 

Detect Vulnerable Road User to Ensure their Safety

One example is our AI-driven detection system Yutraffic awareAI, that is able to analyze the movements of all road users anonymously – including pedestrians or cyclists – in the live image of intersections. By using AI to detect, classify, and track everyone involved, green lights at intersections can be extended for larger groups of pedestrians, school kids, wheelchair users or elderly people. Additionally, this system alerts motorized vehicles about vulnerable road users to increase safety. The insights allow traffic operators to adjust their strategies and improve existing traffic management systems. Furthermore, solutions like this can support autonomous driving vehicles by gathering environmental data from the road infrastructure perspective, providing an extra layer of safety and predictability. 

In Mönchengladbach, this solution is already in place. With 36,000 vehicles passing through the four-lane Fliethstraße in Mönchengladbach, crossing the street is a daily challenge for pedestrians, especially for those with limited mobility or school kids. The awareAI solution now responds to slower pedestrians by extending the green phase of the traffic signal by up to 5 seconds as needed.  

The city of Hamm has installed seven cameras at an intersection to increase road safety. The cameras film diagonally across the streets, capturing both cycling paths and pedestrian walkways. The awareAI system can now detect, for instance, a cyclist 70 meters before the intersection and factor them into its calculations for the duration of green phases.  

In both use cases, all traffic participants are only momentarily captured for control purposes, with no data storage involved, making sure all road users keep their privacy. Through a data interface, recognized objects are transmitted using an encrypted connection including the object’s class, position, classification, and the respective detection zone. Additionally, if needed, it includes speed and direction. 

Prioritizing Emergency Services

AI algorithms can also help to prioritize traffic participants such as emergency vehicles. This scenario has been successfully tested in the city of Linz. The system “Einsatzroutenschaltung” (deployment route switching) for traffic lights enables emergency services to trigger a “green wave” from the control center during emergencies, ensuring swift and safe routes for rescue vehicles, particularly from city entry points or highway exits to hospitals in critical situations. The rapid and secure arrival of emergency vehicles is crucial, especially during acute medical emergencies where every minute counts. This “green wave” during emergencies serves as a complement to sirens and emergency lights on the vehicles. The technology, emphasizing its value in ensuring both faster and safer emergency responses, benefiting everyone. 

A glimpse into the future – From Simulation to Prediction

And these scenarios are just the start. The role of AI in traffic management will extend far from simulate scenarios to predict traffic trends. Using historical data and real-time analysis, AI can predict future traffic trends based on various factors like time of day, events, accidents, or road closures. And that is already possible by today. The predictions can be integrated into adaptive traffic control applications such as our Yutraffic FUSION. The system uses data from multiple sources and with this, new advanced decision-making approaches to control and optimize road networks and transport infrastructure for all road users.  

Furthermore, it is possible to manage the traffic flow focusing on dedicated areas, such as environmental criteria. Our Environmental Traffic Management (ETM) system, for example, serves as a single point of contact, providing customers with all the data and tools they need to manage and optimize their traffic flow for the benefit of the environment by combining real-time traffic and environmental monitoring, traffic anomaly detection, air pollution forecasting, and traffic/air pollution relationships. 

Improved Data Connectivity Fuels New Business Models

By analyzing massive real-time data sets and connecting IoT devices with comprehensive traffic management platforms, the ITS sector will increasingly offer tailored predictive analytics services, and a shift towards subscription-based business models can be expected. The power of data will provide additional monetization opportunities, for example, by offering valuable insights from IoT-generated data to third parties. Faster digital connections, powered by 5G and the IoT, will unleash the full power of this new data economy era. To fully realize this potential, seamless communication between disparate data sources is key. The revised EU ITS Directive (October 2023) is an important milestone in this matter serving as a framework for connecting vehicles, roads, assets, and other devices. The directive advocates for increased data availability and interoperability among various mobility services, including multimodal journey planners and navigation services.  

Cybersecurity becomes a pivotal component of the new data-driven era

As digital and physical infrastructure increasingly converge, cybersecurity will be an elementary success factor to ensure the critical infrastructure is secured. Cyberattacks and vulnerabilities in one area can have a cascading effect on numerous other areas. If they’re not already doing so, cities should embed cybersecurity as an integrated approach throughout the smart city development process, from the planning, design, and transformation stages, considering industry standards, legal and regulatory requirements. 

Ultimately, the interplay of these advancements will redefine business models and reshape the mobility landscape. Collaborative ecosystems in which disparate businesses share data and insights through interconnected platforms will flourish, fostering new opportunities and reshaping traditional industry boundaries.  

Artificial Intelligence and data-based solutions are here to stay in the ITS industry. There’s a lot more to come – and we’ll be there!