Prototyping Vehicle Control Applications Using the CAT Vehicle Simulator

TL;DR

This paper presents a methodology for developing and testing vehicle control applications using the CAT Vehicle Simulator and ROS, facilitating the transition from theoretical models to practical autonomous vehicle controllers.

Contribution

It introduces a model-based design approach with Simulink and ROS for creating control systems that can be directly deployed in simulation and real-world autonomous vehicles.

Findings

Successful integration of control algorithms in the CAT Vehicle Simulator

Demonstration of code generation for standalone ROS nodes

Facilitation of transitioning from design to practical deployment

Abstract

This paper demonstrates the integration model-based design approaches or vehicle control, with validation in a freely available open-source simulator. Continued interest in autonomous vehicles and their deployment is driven by the potential benefits of their use. However, it can be challenging to transition new theoretical approaches into unknown simulation environments. Thus, it is critical for experts from other fields, whose insights may be necessary to continue to advance autonomy, to be able to create control applications with the potential to transition to practice. In this article, we will explain how to use the CAT Vehicle simulator and ROS packages to create and test vehicle controllers. The methodology of developing the control system in this article takes the approach of model-based design using Simulink, and the ROS Toolbox, followed by code generation to create a standalone C++ ROS node. Such ROS nodes can be integrated through roslaunch in the CAT Vehicle ROS package.