Integration of Car-2-Car Communication as a Virtual Sensor in Automotive Sensor Fusion for Advanced Driver Assistance Systems

Kurzfassung

Advanced driver assistance systems (ADAS) require a comprehensive and accurate situation model. Often in-vehicle sensors do not provide sufficient quality and quantity of information to fulfill the demanding requirements. Car-2-Car communication can be seen as an adaptive sensor that provides additional information regularly but also on demand. Due to the fact that Car-2-Car communication strongly depends on the penetration rate, we argue for a seamless integration of Car-2-Car communication as an additional sensor in automotive sensor fusion. With increasing penetration rate the sensor fusion will significantly benefit and eventually unfold its full potential. Due to the fundamentally different measuring principles of in-vehicle sensors and information provided by Car-2-Car communication, redundancy and complementarity can be leveraged to a great extent, thus, increasing accuracy, reliability and robustness of the situation assessment. In addition to a detailed description of the fusion algorithm this paper outlines DLR’s system architecture for ADAS and an enhanced ACC as an application example to show the potential of our approach.