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At the Institute of Automotive Engineering (FZD) at TU Darmstadt, we develop modeling and validation strategies for Automated Driving Systems (ADS) within the framework of the DFG MiRoVA research project. To simulate the operational and tactical driving behavior of varying automation levels and system designs, this thesis investigates the application of stochastic state machines.
Supervisor: Can Kemmler, M.Sc.
An accurate collection an interpretation of the data plays a central role for the development of driving assistance systems. HD-Maps provide detailed information about the road infrastructure, traffic rules and geometric properties. In order to evaluate and train driving functions, a ground truth is necessary to verify the algorithms.
Supervisor: Cristian Martinez, M.Sc.
At the Institute of Automotive Engineering of TU Darmstadt (FZD), we research validation strategies for Advanced Driving Assistance (ADAS) and Automated Driving Systems (ADS), incorporating field tests in collaboration with industry. Modern ADAS and ADS promise enhanced safety but require extensive validation. In this thesis, a virtual comparison of test strategies should be implemented using Monte Carlo Simulations.
Supervisors: Daniel Betschinske, M.Sc., Malte Schrimpf, M.Sc.
To extend modular system architectures of automated vehicles with new technologies, the upgradeability of the hardware is crucial. The goal of this thesis is to analyze what is required to perform a hardware upgrade on a modular hardware architecture and how the upgradeability can be tested.
Supervisor: Lorenz Bayerlein, M.Sc.
Research on the topic of perception sensor simulation in ADAS/automated driving is being conducted at the Institute for Automotive Engineering Darmstadt (FZD) in collaboration with Porsche. To this end, approaches for simulating degradation effects in lidar sensors will be investigated and developed.
Supervisor: Kristof Hofrichter, M.Sc.