A safe autonomous vehicle trajectory domain specific modeling language for non-expert development

Abstract

Managing complexity while ensuring safely designed behaviors is important for cyber-physical systems as they are continually introduced to consumers, such as autonomous vehicles. Safety considerations are important as programming interfaces become open to experts and non experts of varying degrees. Autonomous vehicles are an example system where many domain experts must collaborate together to ensure safe operation. Through the use of higher level abstraction, domain experts may provide verification tools to check dynamic behavioral constraints. Similarly, higher level modeling tools may generate lower level artifacts for a working system. With modeling and verification tools, smaller teams and potentially non-experts may program custom behaviors while ensuring a correctly behaved system. A high level domain specific modeling language was created with a focus on non-domain experts. The domain consists of driving a vehicle through a set of known waypoints by connecting together multiple primitive motions in a sequence. Though constrained to simple motions, it is still possible to create a sequence to drive the vehicle unsafely. Model verification was implemented to check that the expected start and stop waypoints were correctly reached without driving the vehicle into unsafe regions. The language was then provided to a set of 4th year elementary school students to create unique paths. The models created by the students were then used to generate controller artifacts to operate a real autonomous vehicle on a soccer field.