The rapid change of the topology for the intelligent connected vehicles results in the instability of communication links, which reduces the efficiency of data forwarding. To address these challenges, the paper proposes a road section scoring-based data forwarding model for intelligent connected vehicles (RSSM) for urban scenario. Firstly, the road segment is divided into two parts by the vehicle density, and the connectivity for the two parts of the road is modeled, separately. Then, the connectivity between the nodes in the whole road segment is obtained as the scoring of the road segment. Then, the connectivity for all road segments in the whole road network is calculated and regarded as the scoring of the corresponding road segments. Next, the dynamic path calculation from the source node to the destination node is realized by the scoring of the whole road network, which ensures that the planned routing is optimal. Finally, RSSM is implemented on the NS3 and SUMO experimental platform. Experimental results show that the proposed RSSM is superior to the similar data forwarding methods in terms of the successful rate of data delivery and average end-to-end delay.