Research On Vehicle Anti-collision Control Algorithm Based On Road Adhesion Coefficient

It is an active safety technology for vehicle anti-collision system by a series of sensor to monitor dangerous of driving environment and remind the driver or active intervene to avoid collision,which requires that anti-collision control algorithm cans reduce false alarm rate and missing alarm rate so as to ensure effective and accuracy.The different motion state of vehicle、road condition and braking strength will have a great influence on vehicle anti-collision control algorithm.If those parameters are obtained by means of sensors and other measures,which increase cost and less practical.The paper presents the estimation to motion state parameters of vehicle and road adhesion coefficient based on double unscented kalman filter algorithm,then those estimated valve are used for safety distance model,while introducing the barking strength coefficient into safety distance model to get new vehicle anti-collision control algorithm.The paper analyzes the relationship between road adhesion coefficient and motion state parameter of vehicle based on the establishment of Dugoff tire model and seven degree of freedom vehicle dynamics model,and to design the double unscented kalman filter algorithm to estimate.One filter to estimate the motion state parameters of vehicle,other is to estimate the road adhesion coefficient,and both of them form a close loop interaction to improve the accuracy of estimation.The results of MATLAB and CarSim joint simulation show that the double unscented kalman filter algorithm cans real-time accurately estimate motion state parameters of vehicle and road adhesion coefficient.According to different motion state between vehicle and front vehicle,and there is a braking strength coefficient to be introduced into safety distance model,meanwhile design an algorithm of braking strength coefficient based on fuzzy theory,and combined the safety distance model to establish vehicle anti-collision classified warning strategy,finally set up MATLAB and CarSim joint simulation experiment.The results show that vehicle anti-collision classified warning strategy cans effectively warning based on estimation of road adhesion coefficient and braking strength coefficient,and reduce false alarm rate and missing alarm rate.