In the presence of measurement noises and potential sensor malfunctioning, road condition identification by a single vehicle may not be reliable for motion planning and control of autonomous/intelligent vehicles. In this paper, we propose a distributed cooperative road condition estimation scheme for vehicular networks, involving a dynamic consensus algorithm to increase the reliability and accuracy of estimation. In this scheme, each vehicle individually estimates the road condition parameter using an online recursive least squares estimator, and disseminates it through the network to fuse the individual estimates through a consensus algorithm. It is shown that the proposed scheme well adapts to the variations in the road condition, improves the road condition estimation accuracy even with limited number of vehicles, and reduces the sensitivity to measurement noises. Simulation results demonstrate that estimation of the road condition using the proposed scheme improves the performance of maneuver planning for collision avoidance in slippery road conditions.