The collaborative strategy of vehicle-road-environment based on intelligent and connected vehicles (ICVs) to assist in driving vehicles safely and relieve traffic congestion has become an effective solution. This paper proposed a strategy for vehicle lane change and roundabouts traffic based on vehicle profile (VP) in combination with the driving characteristics of roundabouts. Initially, in order to solve the confusion problem of multisource heterogeneous data of ICVs in roundabouts, this paper defines VP to describe and characterize the multidimensional data of ICVs, so the data in ICVs can be further applied. Furthermore, the weights of relevant parameters in the VP are updated based on the random forest algorithm. In addition, the payoff function is designed for the lane change decision at the exit of roundabouts based on the VP and dynamic weights. Finally, the performance of the proposed algorithm is compared with other algorithms through the SUMO platform and three scenarios are used in the simulation verification, including traffic congestion, normal, and sparse. The experimental results verify the optimization effect of vehicle profile on roundabout traffic strategy and also show that this algorithm can effectively improve the efficiency of vehicle traffic in roundabouts. In particular, the efficiency and comfort of vehicles in roundabouts are effectively improved in normal traffic scenarios.