In addition to simulations, real driving tests are indispensable for testing systems that cause autonomous intervention in the longitudinal or lateral dynamics of a vehicle. Due to the high costs of real tests, it is necessary to identify a small number of "relevant" function-specific test scenarios, to implement them in the vehicle in a reproducible manner, and then to evaluate them. Simulations can be used to identify and analyze the "relevant" test scenarios, but also data from traffic scenarios recorded during journeys on public roads. In the intensification phase, bridges between the simulation and the real world in the safeguarding process are to be created with the help of AI methods. The advantages of AI methods are to be used in a targeted manner.

In subproject I, research is being conducted on high-precision state estimation in the absence of GPS signals or other external sensors under real conditions. The extent to which on-board sensors of the vehicles are suitable for sensor fusion with the inertial gyro system of the project partner is being investigated. In subprojects II and III, real-world data will be used to research adaptive driver modeling and the generation of urban traffic scenarios using AI methods. Further details can be found on the pages of the subprojects:

  • SP I: High-accuracy state estimation and data generation.
  • SP II: Driver modeling for function development and validation
  • SP III: Test systematics for automated driving

Contact

Scientific director AImotion Bavaria; Programme director and Academic Advisor "Automated Driving and Vehicle Safety" (Master)
Prof. Dr.-Ing. Michael Botsch
Phone: +49 841 9348-2721
Room: K209
E-Mail:
Peter Riegl, M.Eng.
Phone: +49 841 9348-3353
Room: P108
E-Mail:

Funding reference number

13FH7I08IA

Funding agency