Model Based Design and Verification of Automated Driving Features Using XIL Simulation Platforms

The latest edition of the US Department of Energy's (DOE) Advanced Vehicle Technology Competition (AVTC) series is the EcoCAR Mobility Challenge (EMC). In the third year of the EMC, the Mississippi State University (MSU) team developed and tested a perception system and a longitudinal controller to achieve SAE level 2 autonomy. Our team leveraged the model-based design approach to iterate between developing software components and executing tests in multiple environments in the loop (XIL) to verify that design requirements are met. This workflow allowed us to detect and resolve issues early in the development process. The perception system is composed of a sensor fusion and tracking algorithm. It relies on detections from a front facing camera and radar to generate tracks for a leading vehicle. The tracks from the perception system are used by a model predictive controller (MPC) to maintain a safe distance to the leading vehicle. A comparison study between test results from different testing environments was conducted to improve our models' fidelity and gain better insight into the software's behavior. The end result is a robust development process that allows for seamless transition between development and testing, improved performance of the perception system, a functional longitudinal control system, and a framework that can be adapted for future autonomous features.