Integrating Small-scale Autonomous Vehicles in CS Education: An Experience Report

Teaching software systems engineering is neither effective, nor inspiring if students cannot practice the conveyed theory. We report on a hands-on approach that closes the gap by means of off-the-shelf and in-house realistic miniature models of autonomous vehicles. It is innovative that the infrastructure extends beyond the widely-used solutions, to digitally controlled cars and trains, with open hardware and extendable sensory/actuating capabilities (cameras, opto-sensors, proximity sensors, LEDs, displays) operating in realistic mini-environments, including line-marked roads, railways, traffic-lights and -signs, tunnels and railroad switches. For many years already, we have been using these vehicles to structurally teach physical computing (300 undergraduates yearly) and systems testing (12 graduates yearly), and for incidental individual research projects. Recently, we started two initiatives that stimulate a more dynamic know-how transfer across generations. The first is a better scalable undergraduate capstone project, where groups of students work on a 'hot' research topic in autonomous driving. The second motivates student teams to go the extra mile in an international intelligent car race competition. Evaluations showed that although unusual for a non-engineering curriculum, 'playing' with autonomous vehicles is an excellent strategy to discover the interaction of software with hardware and environment, to better consolidate existing knowledge on programming and testing, and to explore new fields, such as AI-based computer vision, navigation and safety, adding in all cases more fun and motivation. We share the design of the scaffolding and teaching initiatives, together with lessons learned which will hopefully inspire other educators in shaping engaging and future-proof CS curricula.