A framework is proposed to improve car navigation through cooperative data fusion. We consider incorporating information from GPS-enabled neighboring cars and Received Signal Strength Indication (RSSI) out of IEEE 802.11p messages. The solution includes prediction-based data resynchronization, links selection mechanisms using RSSI measurements pre-validation or a Cramér-Rao Lower Bound (CLRB) indicator eliminating
non-informative data, and finally a Bayesian tracking filter. First simulations show benefits from selective cooperation in terms of navigation continuity under harsh GPS conditions.