A Driver Lateral and Longitudinal Control Model Based on Queuing Network Cognitive Architecture

In this paper, we propose a new computational model of driver car-following control with lateral control based on the Queuing Network (QN) cognitive architecture. A driver car-following model within the framework of the QN cognitive architecture is first developed based on the time headway and then integrated with a QN-based driver lateral control model previously validated. The comparison between human driver data and the integrated model simulation data suggests that this computational model can perform car-following control with lateral control well, and its performance is in agreement with that of drivers under straight and curved roads. This proposed model can compute and simulate car-following behavior and thus has the potential to help develop driver assistance systems for the car-following scenario.