Despite increasing digitalization and networking, current traffic systems are largely characterized by incomplete information about all road users. Pedestrians and cyclists in particular often cannot be adequately considered in traffic control and traffic safety functions.
The project “Artificial Intelligence in Ingolstadt’s Traffic System” (KIVI) addresses this issue and aims to achieve increased efficiency in the areas of traffic control and traffic safety by leveraging the previously largely inaccessible data treasure across all road users.
To this end, a high-definition test field is being established across multiple intersections, equipped with local sensors for detecting all road users. This stationary view is supplemented (and fused using AI) with additional mobile sensors (cars, buses, bicycles, and pedestrians equipped with 5G smartphones) to generate the most comprehensive current digital representation of the local and network-wide traffic situation.
Through data fusion and the use of AI methods, it is being examined how traffic signals can be optimized through more comprehensive, current information about all road users and how traffic safety can be increased.
Current Status
The high-definition test field continues to exist as a real-world laboratory and is currently being used in the SiRaMiS project, among others.
The overarching vision remains unchanged. Traffic safety and traffic flow for connected and non-connected road users are to be improved, particularly in urban areas and at critical points. The focus of the test field is on urban traffic and the interaction of motorized vehicles with vulnerable road users (pedestrians, cyclists, e-scooter and e-bike riders, etc.).
