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提出了结合“PSO-SVM”和“五要素”车辆防碰撞预警模型对车辆的行驶状态是否安全进行监测和预警.利用Matlab仿真软件,结合SVM技术与“驾驶员、车、路、环境、车辆行驶状态”五要素车辆行驶安全评价模型,进行了车辆行驶状态监测与安全报警的仿真实验.较详细的论述了影响因素的选取和确定,以及预警模型的建立和测试过程,仿真实验的测试结果误差较小,表明该方法有一定的有效性.“,”In order to reduce the traffic accidents and ensure driving safety, the paper combines PSO-SVM and the five elements of the safety evaluation model (“driver, vehicle, road, environment, and vehicle running state”), and puts forward a vehicle anti-collision warning model which can conduct analysis and early warning by monitoring the vehicle traffic status. Firstly, the paper discusses the influencing factors of the driving security, and analyzes the correlation between the influencing factors and collision. Then the vehicle anti-collision warning model based on PSO-SVM is built up. Finally, the paper carries out the simulation experiment of the model by MATLAB simulation software, and tests the procedure of the warning model in detail. Simulation results demonstrate the high accuracy and effectiveness of the algorithm.