Dedicated Short Range Communication (DSRC) systems will become ubiquitous among vehicles in the near future. Because this technology enables communication between any set of DSRC-equipped vehicles, precise knowledge of these other vehicles is available to the host car. In addition to the DSRC system, onboard radars are able to provide high fidelity dynamics measurements of other objects within the sensing range. Given these two methods of measurement, environmental perception for driver assistance systems can be greatly improved, especially if the measurements are fused together. However, this is not a trivial task because of an inherent data association problem: Given the objects detected by the radar sensor, which one is truly the DSRC message sender? In this paper, we propose a system architecture to fuse DSRC and radar data. This architecture uses a reliable statistical track-to-track association algorithm in a novel way to solve this data matching problem. We present experimental results of this architecture on a system running in real traffic situations in the U. S.