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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. Zusammenfassung Der Beitrag beschreibt erste Ergebnisse des Forschungsprojektes PRORETA 3, das die Entwicklung eines integralen Fahrerassistenzsystems zur Kollisionsvermeidung und automatisierten Fahrzeugführung auf Basis einer modularen Systemarchitektur anstrebt. Hierzu werden relevante Informationen aus einem dichten Umfeldmodell extrahiert und in einem potentialfeldbasierten Trajektorienplaner verarbeitet, der Führungsgrößen für unterlagerte Fahrzeugregler generiert. Zusätzlich unterstützt eine Mensch-Maschine-Schnittstelle den Fahrer zielgerichtet bei der Fahrzeugführung.

The occurrence of accidents caused by deficiencies in risk recognition by the driver can be prevented by presenting relevant information in real time to the driver. In this paper it is proposed to draw the driver's attention towards relevant traffic objects, which might be a safety hazard, by a LED strip which is affixed 360° around the interior of the car's cabin. With this approach a higher number of use cases can be covered than with existing HMIs. The effectiveness of this system is evaluated in a driving simulator study with 13 subjects in four critical traffic situations. The gaze attention times are ascertained with eye tracking technology; mental effort and acceptance are determined by questionnaires and the comprehensibility by semi-structured interviews. There are indications of shortened gaze attention times using the LED strip compared to the baseline without driver support. The subjects understand the information submitted mostly intuitively. The acceptance ratings overall are in a positive range, but differ between scenarios.

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