有级转向履带车辆的驾驶员操控行为模型

For the representation of driving skills at the control level of tracked vehicle with stepped steering mechanism, a driver control behavior model based on control primitive sequence is proposed by utilizing a large amount of collected real driving data. The control primitives are characterized by Gaussian mixture models, and the digraph is applied to complete the extraction and category identification of the driver control primitives sequence. According to the recognition results of different types of control primitive sequence, the driving data is regrouped, and the hidden Markov model-Gaussian mixture model is used to train the driver control behavior model for each type of sequence. The results show that the extracted control primitive sequence can not only represent the driver's steering control primitives switching behavior, but also realize the reasonable division of the trajectory primitive types. Within the predicted time domain corresponding to a given desired trajectory, the proposed model can predict driver control behavior with an average deviation of 4.2% under certain conditions.