Data-driven modeling of a scenario space
- Type:Master's thesis
- Person in Charge:Open
Context: Verification and validation of driver assistance systems / automated driving functions by means of scenario-based testing; use of real data to populate models for a scenario space; selection of scenarios from the scenario space that are as realistic as possible.
Challenge: Interpretation of real data in the scenario generation use case; identification of characteristics in the real data; transfer of characteristics of the real data into a feature model; simulation of scenarios to evaluate the feature model
Goal: Generation of scenarios for scenario-based testing that are as realistic as possible; automated population of the scenario space
Prerequisite: Basic knowledge of: software testing; analysis, interpretation and processing of data; driver assistance systems; Python and C++