The article describes first results of the research project PRORETA 3 that aims at the development of an integral driver assistance system for collision avoidance and automated vehicle guidance based on a modular system architecture. For this purpose, relevant information is extracted from a dense environment model and fed into a potential field-based trajectory planner that calculates reference signals for underlying vehicle controllers. In addition, the driver is supported by a human-machine interface.

In this proceeding a lateral planning approach for advanced driver assistance systems is presented. Therefore, an optimal future trajectory is planned, based on a combination of potential field theory and optimal control theory, which leads to a formulation of a model predictive control problem. To handle complex environment structures, for example in urban scenarios, the potential fields of the road and of the dynamic obstacles are extended by a potential field of the so-called free space. The trajectory planning is embedded in a framework, which gives the possibility to use the optimal trajectory for an emergency intervention system as well as for automated driving.

The article describes first results of the research project PRORETA 3 that aims at the development of an integral driver assistance system for collision avoidance and automated vehicle guidance based on a modular system architecture. For this purpose, relevant information is extracted from a dense environment model and fed into a potential field-based trajectory planner that calculates reference signals for underlying vehicle controllers. In addition, the driver is supported by a human-machine interface.