  Sensor calibration usually is a time consuming yet important task. While
classical approaches are sensor-specific and often need calibration targets as
well as a widely overlapping field of view (FOV), within this work, a
cooperative intelligent vehicle is used as callibration target. The vehicleis
detected in the sensor frame and then matched with the information received
from the cooperative awareness messagessend by the coperative intelligent
vehicle. The presented algorithm is fully automated as well as
sensor-independent, relying only on a very common set of assumptions. Due to
the direct registration on the world frame, no overlapping FOV is necessary.
The algorithm is evaluated through experiment for four laserscanners as well as
one pair of stereo cameras showing a repetition error within the measurement
uncertainty of the sensors. A plausibility check rules out systematic errors
that might not have been covered by evaluating the repetition error.
