An Autonomous Driving Simulation Platform as a Virtual HSAVC Competition Environment

At ISEC 2018, Professor Marc E. Herniter presented the High School Autonomous Vehicle Competition (HSAVC), which introduces autonomous driving to high school students. The competition promotes STEM education by challenging participants to use MATLAB to create a vision-based track detection algorithm and Simulink to build a motor controller model. Following the COVID-19 global pandemic, many in-person STEM competitions were canceled, including HSAVC. The goal of the Autonomous Driving Simulation Platform is to replicate the physical conditions of HSAVC using simulation to allow students to continue the activity virtually. Using MATLAB, the Simulation Platform creates a real-time virtual environment for students to test their HSAVC track detection algorithms and motor controller models. The Simulation Platform consists of two MATLAB apps: a Track Generator and a Driving Simulator. The Track Generator application can create fixed tracks based on user inputs or randomized tracks based on user-defined lengths. The Track Generator utilizes a growth and mutation algorithm to create a track with three distinct track sections: straight, left curve, and right curve. The Track Generator’s randomized track replicates the HSAVC’s physical track, and the Driving Simulator replicates the HSAVC’s 1:18 scale autonomous vehicle equipped with a linescan camera, two drive motors, and a servo motor with a vehicle model and a camera model. The Track Generator and Driving Simulator have been successfully designed and implemented with MATLAB App Designer. Users can create a track and test their algorithms and models through an intuitive interface, making it an effective tool for STEM education in any classroom. The Autonomous Driving Simulation Platform holds potential as a solution to continue the HSAVC during the pandemic and can increase student engagement in the HSAVC from high schools around the world like Amazon Web Services DeepRacer. Another benefit of the Simulation Platform is convenient and controlled virtual algorithm testing, which allows for repetitive experimentation to be simulated without risk of damaged materials. The simulation platform has broad potential as an educational tool, such as complementing high school robotics curriculums to teach motor control algorithms and training reinforced learning racing models. The successful virtual adaptation of HSAVC demonstrates how simulation can provide many educational benefits when borrowing the framework of STEM competition.