A Mini-Living Lab Project as a Pedagogical Approach to AI-driven Autonomous Systems in Undergraduate Engineering and CS+[X] Education

Abstract

We present the living lab methodology as a pedagogical approach to artificial intelligence (AI) based autonomous systems under the framework of place-based learning. Due to time, location, weather, traffic safety, and other issues, performing road testing on autonomous cars is challenging. Autonomous driving testing has been made easier by the virtual test platform, which can partly replace road testing. To improve the system-designed skills of the students and to validate autonomous driving ideas in real life settings to further refine solutions proposed, we proposed Mini-Living Lab system. The platform may also give a significant number of test scenarios for the driver during early verification of the autonomous driving control approach. We provide the detailed system design and implement an artificial intelligence based autonomous driving model on our proposed system. For the neural network model, we adopt PointNet++ and improve its design to process the lidar point cloud data, then further to perform the autonomous steering control tasks. The proposed project provides an opportunity for students to actively participate in co-creation of knowledge and innovation in real-life contexts, thus leading to an enhanced understanding of complex engineering problems and development of required skills for their innovative solutions.