Smart Intersection

Inner-city intersections are repeatedly the focus of political and traffic discussions due to their complexity on the one hand and as accident blackspots on the other. The situation becomes even more complicated if autonomous vehicles are facing up to these challenges either among themselves or in mixed traffic.

The cooperation of vehicles with the infrastructure offers a solution for increasing the safety of automated driving functions in the context of complex urban intersections. The so-called Smart Intersection opens up the potential of stationary environment perception, capturing complex traffic situations within the local dynamic object map. It compensates the visual shadows and restricted sensor horizons of the vehicle's own sensors by exchanging information between infrastructure and vehicle.

Great advantages are seen in the recording and transmission of the current locations of non-networked road users, e.g. within cooperative transition scenarios from conventional traffic to networked-automated traffic. Furthermore, the detection and position transmission of vulnerable road users (VRU) such as cyclists or pedestrians promise major benefits in terms of traffic safety.

There is also a need for a protocol of data traffic usable in court due to the shared responsibility between vehicle manufacturers, infrastructure operators, communication service providers and possibly other parties involved. Manipulation risks are compensated by the integrity of data transmission and by mechanisms for the security of cooperative systems.

Smart intersection requires key technologies that have been developed in the Fraunhofer Cluster of Cognitive Internet Technologies (CCIT) together with the AISEC, HHI, IIS and IVI institutes. The Fraunhofer IVI as the leading institute for transportation and infrastructure systems implemented the different technologies into demonstrators at their site. These demonstrators illustrate the innovative, networked and universal solutions for automated driving within complex urban intersections.


  • Stationary monitoring of the surroundings from the side of the road using a 360° model
  • Exchange of detected dynamic objects between infrastructure and vehicles
  • Detection of dangerous situations in public traffic areas


  • Central sensor data processing
  • Low-latency and broadband communication through mmWave technology
  • Standardized object list transmission
  • Tamper-proof, authenticated data transmission


  • Synchronization of highly automated traffic flows
  • Increasing safety in mixed inner-city traffic