In this paper the development of a function for an automated lateral guidance by means of a consistently model-based and verification-oriented methodology of development will be presented. With a virtual test bench being used, the development process starts out with modelling the vehicle dynamics, the sensor system, and the environment. It is followed by a detailed layout of a self-learning driving function for the vehicle to stay in its lane on any single-lane road using artificial neural networks (ANN) and genetic algorithms (GA). The process is completed by a systematic analysis and validation of the thus developed driving function for lateral guidance.

This paper details the concept, realization and application of a mobile Hardware-in-the-Loop (HiL) test bench for Vehicle-to-Everything (V2X) communication. For this purpose, the mechatronic design cycle will be shown first as a basis for ranking the test bench within our methodical procedure and the state of the art of V2X communication. On this basis, demands on the V2X test bench will be defined for a concept to be derived. The concept realization and the proof of function of the test bench will be presented using the example of a navigation algorithm with an interface for V2X messages.