Intelligent Infrastructure: Digital Test Fields in Aachen, Munich and Ulm

Summary

The digital twin is connected to the three test fields in Aachen, Munich, and Ulm and continuously receives real-time data from all locations. Each test field is equipped with high-precision sensor technology – including cameras, lidar, and radar – to reliably detect traffic objects. The sensor data is processed on site in real time and transmitted to the digital twin via a central communication unit. This means that all detected objects are available centrally and can be used specifically for the development and optimization of decision-making and motion planning processes for automated driving systems. As part of the demonstration, the real-time data from all three test fields can be visualized together – directly and intuitively via a browser-based interface.

State of the Art

The development of intelligent infrastructures for automated and connected driving in Germany is based on state-of-the-art sensor technology, real-time data processing, and the use of digital twins. The A9 test field in Munich combines simulations with real-world driving tests to optimize AI-supported algorithms. In Aachen and Ulm, 5G campus networks, IoT systems, and sensor fusion enable precise vehicle-infrastructure communication. These intelligent test fields are a central component of the testing of automated driving systems. Their main goal is precise object recognition in order to continuously monitor traffic and be able to respond to various emergency scenarios. However, there is currently neither a common digital twin nor harmonized interfaces connecting the test fields.

Technological Innovations

A modular and scalable digital twin connects the test fields in Aachen, Munich, and Ulm, enabling the cross-location consolidation of sensor data via harmonized, standardized interfaces. This creates a consistent real-time picture of traffic conditions, which provides a reliable basis for the development and optimization of decision-making and movement strategies for automated driving systems.