Path Tracking for an Autonomous Vehicle During Emergency Condition

Abstract

An autonomous vehicle's primary function is detecting and tracking the road course precisely and correctly without a driver's assistance. As a result, implementing appropriate controllers is critical for improving the vehicle's stability and movement responsiveness. The performance of adaptive Stanley controlled is evaluated in this paper using numerical simulations. The Stanley controller's most common geometric controller for vehicle path tracking algorithms is compared based on their trajectory tracking analyses on various vehicle speed maneuvers. Stanley calculates steering based on the difference between the vehicle's lateral position and heading angle. The difference between desired coordinates and present coordinates of the vehicle along the path is used to calculate lateral, longitudinal, and vehicle heading orientation angle using the future prediction control technique. The results demonstrate that the Stanley controller outperforms the emergency trajectory with more consistent trajectory tracking and steady-state error.