Aiming at the shortcomings of the existing methods of vehicle instability determination, the research of pattern recognition in vehicle driving stability is carried out, and a new method of judging vehicle lateral stability based on K-means clustering algorithm is proposed. The vehicle dynamics model was established by CarSim, and the offline clustering centers were obtained by offline clustering analysis of vehicle driving state data through K - means clustering algorithm. Then build the CarSim and Simulink co-simulation platform. Calculate Euclidean distance between data points and cluster centroids. Design vehicle driving stability criterion in Simulink and identify the vehicle driving stability online. The method is of data mining, which makes full use of the comparison of offline data and real-time data. The simulation results show that the method can accurately and real-timely quantify the vehicle’s lateral driving stability considering various parameters, which can provide the criterion for intervention timing and degree of control system.