Part B: Steering and control of an autonomous vehicle in emergency lane change maneuvers based on skilled driver's performance

This paper considers the vehicle control process in emergency lane change (ELC). The control method is divided into two parts: before crossing the obstacle and after crossing it. The first part is done by a feed-forward controller inspired by the driver's behavior pattern in the ELC maneuver. This controller is compensated by a neural network system and two proportional-integral (PI) and proportional-derivative (PD) controllers, which correct the output of the feed-forward controller to follow the path more accurately. The second part consists of two PD controllers responsible for controlling and steering the vehicle in the main path after crossing the obstacle. The main novelty of the proposed method is that the computational burden is low because of using a feed-forward controller, which is the main source of the calculation's burden. So as a result, the controller system can cover the ELC maneuver in under 2 seconds in various lateral displacements to bypass the obstacle and prevent collisions. The co-simulations are performed in CarSim software and MATLAB/Simulink, which shows that the control system can appropriately steer the vehicle and follow the desired at different speeds, in the presence of road friction and parameter uncertainty.