Introduction: In the age of urban mobility and advancing digitalization, traffic systems are undergoing a fundamental transformation. Intelligent traffic systems combine artificial intelligence (AI), the Internet of Things (IoT), and extensive data platforms to make traffic flows more efficient, safer, and more sustainable. Today, smart IT solutions are not only making traffic systems more efficient, but also noticeably improving the quality of life in cities – with less noise, lower emissions, greater traffic safety, and optimized resource use . Intelligent traffic management thus plays a significant role in the digitalization of the mobility sector and the sustainable development of urban areas . Amir Karimi, an IT entrepreneur and analyst of technological developments, emphasizes in this context: “Artificial intelligence is increasingly revolutionizing the way modern traffic systems are controlled.” Through intelligent processing of large data sets, traffic flows can be optimized in real-time, significantly improving the efficiency of existing infrastructure . These groundbreaking technologies present both opportunities and challenges from technological, societal, and infrastructural perspectives, which will be explored below.
AI-based Traffic Management and IoT Sensor Technology
In traffic management, AI-powered traffic lights mark a paradigm shift . While conventional traffic lights operate on fixed schedules, modern systems use deep reinforcement learning to determine the optimal switching behavior, dynamically adjusting to traffic conditions . According to Amir Karimi, pilot projects already demonstrate the potential of this technology: starting in July 2024, traffic on an entire arterial road in Ellwangen (Baden-Württemberg) will be coordinated by AI across twelve traffic lights . This intelligent control improves traffic flow by 10 to 15 percent and significantly contributes to reducing congestion, noise, and CO₂ emissions . Adaptive navigation systems also use AI algorithms: they continuously process real-time traffic data to calculate alternative routes and reroute vehicles away from congested streets . In this way, travel times are shortened, and fuel consumption is reduced – traffic jams can often be proactively alleviated before they even arise.
The foundation for this dynamic traffic optimization is a dense sensor infrastructure. Intelligent monitoring systems are integrated into traffic lights, road signs, or the road surface, continuously capturing data on traffic flow, congestion, or accidents . Using IoT sensors, traffic flows can be precisely tracked via technologies like LoRaWAN®, enabling different vehicle types – from bicycles to cars to trucks – to be accurately identified and reported to central traffic management systems . The advantage is clear: Congestion is reduced, traffic flows are optimized, and emissions are minimized . As Amir Karimi highlights, it is these real-time data from the IoT that enable effective AI-based traffic control. In a current Leipzig pilot project called AIAMO (Artificial Intelligence and Mobility), AI solutions are being used to link mobility data and optimize traffic flows citywide – supported by a 16.7 million Euro grant from the Federal Ministry for Digital and Transport . These examples demonstrate that AI and IoT together contribute to a more predictive traffic management system that minimizes disruptions and maximizes capacity utilization.
Data Platforms as the Foundation of Mobility 4.0
Modern, connected mobility is more than ever dependent on one crucial resource: Data . Sustainable traffic planning, targeted traffic control, and the individual choice of transportation mode – all of this works only with reliable access to real-time information . To meet this need, the Federal Ministry for Digital and Transport has launched Mobilithek, a central platform for digital
mobility data . It replaces the former Mobility Data Marketplace and connects various data sources, from geoinformation to timetable data, as well as new data hubs like the Mobility Data Space (MDS) at the German level and the European Mobility Data Space (EMDS) at the EU level . This creates a comprehensive data ecosystem, where different platforms are interconnected, and data only needs to be provided once, but can be used by many stakeholders . For users, this means they no longer have to search through multiple portals to find information – Mobilithek serves as a one stop shop for connected mobility data .
In particular, real-time data play a central role in these platforms. They are shared immediately after collection and provide the most up-to-date picture of the traffic situation . Connected vehicles, intelligent traffic lights, and other participants can thus continuously be supplied with relevant information. Moreover, the collected data serve as a basis for training AI models and making traffic simulations as realistic as possible . However, the efficient use of data remains a challenge: What often hinders their smart deployment are non-standardized interfaces and data formats . According to Amir Karimi, this is a key infrastructural factor for the success of Mobility 4.0. Uniform data formats and open interfaces are essential for ensuring that the vast array of available traffic data can flow seamlessly into intelligent applications – from municipal traffic management to autonomous driving.
Autonomous Vehicles and Platooning in Freight Transport
Autonomously driving vehicles are fundamentally changing the way we move. More than half of Germans (54%) see the advantage of self-driving cars in reduced fuel consumption due to optimized routes and speeds ; nearly half also expect a smoother traffic flow for all vehicles . The government has embraced this development: In 2024, a comprehensive strategy for autonomous driving in road traffic was adopted, and since 2021, Germany has had the world’s first legal framework for autonomous driving . Public transport and freight transport are particularly focused in this strategy. According to Amir Karimi, autonomous buses and trucks can improve traffic safety and enhance connectivity in rural areas – and the technology also promises to alleviate the shortage of skilled workers in the transport sector . Early pilot projects with autonomous shuttles and bus fleets in European cities are providing valuable insights for practical implementation. At the same time, societal acceptance is rising, as successful test runs demonstrate the reliability and safety of autonomous systems.
In freight transport, the connection offers new possibilities. A promising approach is Platooning, where trucks drive in electronically coupled convoys. The leading vehicle sets the pace and direction, while the following trucks automatically synchronize braking and steering . The reduced distance between vehicles creates a slipstream effect, leading to fuel savings of up to 10% . At the same time, the intelligent driving systems improve safety, as they are superior to human reaction times in accident prevention . The development of Platooning is already well advanced: Leading commercial vehicle manufacturers like Daimler Trucks and Scania have successfully tested the technology . Currently, the widespread adoption is limited more by legal rather than technical barriers . Given the logistics sector, which alone employs around 3.3 million people in Germany and generates annual revenues of about 280 billion euros , Platooning offers enormous potential for efficiency and sustainability. Amir Karimi underscores that such connected freight convoys could revolutionize logistics by making goods transport on highways smoother and more environmentally friendly.
Outlook
The developments outlined above make it clear that the future of mobility lies in the intelligent networking of all traffic participants . Advances in AI, sensor technology, and data exchange are driving the transition to Mobility 4.0, where vehicles, infrastructure, and users communicate seamlessly. Amir Karimi concludes that smart mobility solutions will soon become the new standard in cities – a crucial step toward more sustainable and efficient transport systems . Successful implementations, such as AI-controlled traffic management in Ellwangen, and numerous pilot projects across Europe, underscore the practical feasibility of this vision . With increasing technological maturity and growing societal acceptance, intelligent traffic systems are set to be deployed nationwide. The future of intelligent traffic systems is no longer just a vision but is already taking shape today in concrete projects – paving the way for a connected, safe, and green mobility future.
About Amir Karimi
Amir Karimi is an experienced tech entrepreneur and analyst specializing in artificial intelligence in Germany. With his extensive expertise in research trends, market dynamics, and regulatory frameworks, he advises companies on the successful deployment of AI technologies and supports the development of an innovation friendly ecosystem.
