The Research Of Vehicle Active Safety Warning System Based On Driving Behavior

The driver is the leader in the model of "human-vehicle-road environment", whose driving behavior largely determines the safety of road traffic. That the driver's driving behavior has the characteristics of randomness, impulsivity and autonomy brings very great difficulty to study the driver's driving behavior directly. In view of this, the following contents are studied.Firstly, the present situation of research on driver's driving behavior is introduced, and the difficulties and shortcomings of study about driver's driving behavior directly. The analysis of the difficulties and shortcomings in the direct study of driving behavior from the driver's perspective is done. According to the correlation between the driving behavior and vehicle motion state, the method of research on the driver's driving behavior indirectly by analyzing the vehicle motion state, and a monitoring system of vehicle motion state based on MEMS(Micro-Electro-Mechanical System) sensor is constructed.Secondly, in order to solve the problem of random and fuzzy which is encountered in the process to evaluate the state of vehicle motion, the cloud model theory is introduced. In order to judge evaluate the state of vehicle motion intelligently, fuzzy neural network which realizes the mapping between the MEMS output signal and the evaluation results of cloud model.Finally, the attitude data of vehicle motion is calculated by processing the MEMS sensor output signal. And then a methodology to collect the predicting the driving vehicle attitude based on dynamic Elman neural network is presented. Experimental results show that compared with traditional linear model and BP neural network model, this model has higher precision and shows better tracking performance.