  The connectivity between vehicles, infrastructure, and other traffic
participants brings a new dimension to automotive safety applications. Soon all
the newly produced cars will have Vehicle to Everything (V2X) communication
modems alongside the existing Advanced Driver Assistant Systems (ADAS). It is
essential to identify the different sensor measurements for the same targets
(Data Association) to use connectivity reliably as a safety feature alongside
the standard ADAS functionality. Considering the camera is the most common
sensor available for ADAS systems, in this paper, we present an experimental
implementation of a Mahalanobis distance-based data association algorithm
between the camera and the Vehicle to Vehicle (V2V) communication sensors. The
implemented algorithm has low computational complexity and the capability of
running in real-time. One can use the presented algorithm for sensor fusion
algorithms or higher-level decision-making applications in ADAS modules.
