Development of a Driver Lateral Control Model by Integrating Neuromuscular Dynamics Into the Queuing Network-Based Driver Model

This paper describes the development of a novel driver lateral control model by integrating the driver´s neuromuscular dynamics into the queuing network (QN)-based driver lateral control model. Experimental results from 16 participants in a driving simulator show that, compared to the QN-based model, the proposed model performs better, and its performance is closer to that of drivers when a vehicle runs at a relatively high speed. The proposed model not only has the advantages of the models based on a cognitive architecture but also captures the dynamic interaction between the vehicular steering system and the driver´s neuromuscular system. Thus, it can better represent driver lateral control and has greater value in supporting the development of driver assistance systems.