无级转向履带车辆驾驶员转向操控行为建模与预测

Reforming the current manned tracked vehicles into the unmanned tracked vehicles is one effective way to develop the unmanned tracked vehicle. To this end,a data acquisition system is designed to collect the vehicle state and driver’s operation data. Based on the collected data,the driver’s steering behaviors during the tracked vehicle’s operation are clustered and analyzed based on the Gaussian mixture model(GMM),and a steering control behavior model is established. Based on different steering categories from GMM,a prediction model for the driver’s steering operation is trained by taking the running speed and steering angle deviation of vehicle as model inputs and the turning angle of hydraulic motor swinging arm as the predictive truth value of steering control. The proposed predsiction model is used for the statistical modeling and prediction of driver steering behavior in the in real cross-country environment. Experimental results show that the proposed steering control model can predict the driver’s steering behavior accurately.