Vehicle Dynamics Model for Simulation Use with Autoware.AI on ROS

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing. These sub-models were converted into Python then uploaded into the simulation framework. Sub-model dynamics were validated independently of each other and within expected operating ranges. System configuration restricts operation to be within the ranges of linear vehicle dynamics. This work provides a potential methodology for model development that can be expanded upon with future simulation work. The existing system configuration can be altered to allow for various combinations of vehicle operating characteristics. Additionally, this work can fast-track model development for other automated vehicle analyses.