Comparative Analysis of Various Control Techniques for a ROS-based Platooning Architecture

Andrew Youssef, Gasser Elazab, Seif El-Bouhy, Mohamed Owis, Youssef Salem, Dalia M. Mahfouz

Abstract: Over the past few decades, cooperative autonomous vehicles have gained considerable research attention for transportation development. One of the most important cooperative applications is vehicle platooning. Control strategies for platoon vehicles' trajectory tracking has recently attracted extensive interests. This study investigates two different control algorithms for the platoon leader to manage its speed and trajectory. In addition, a robust control approach is adopted for the followers to manage their inter-vehicular distances. These controllers are applied on a platoon of three vehicles, each vehicle is modeled using the Ackermann steering model. A comparative study is analysed between the controllers implemented, which are Go- to-Goal (G2G) control and Nonlinear Model Predictive Control (NMPC). The followers are controlled using Sliding Mode Surface (SMC) controller. Two experiments are conducted to evaluate the controllers' performance. The first is tracking a predefined velocity profile in longitudinal motion. The second is tracking a maneuver generated using Artificial Potential Field (APF) path planning algorithm. The overall system's architecture is implemented through Robot Operating System (ROS). It is evaluated using Gazebo environment to assess the system's performance. Results show satisfactory performance in terms of velocity, trajectory and spacing distance convergence that are further discussed through out the study.