Constraint-based Modeling of Autonomous Vehicle Trajectories

Yegeta Zeleke and Kennon McKeever published results of their research project on Constraint-Based Modeling of Autonomous Vehicle Trajectories in the 15th Workshop on Domain-Specific Modeling, which is the longest-running workshop in the history of SPLASH/OOPSLA. Their paper, titled "Experience Report: Constraint-based Modeling of Autonomous Vehicle Trajectories" focused on enabling young students (e.g., in elementary school) to safely control a dangerous robot, such as autonomous car, through the application of constraint-based checks during the code generation process. Their experience report discussed the creation of a domain-specific language that allows for faster programming of autonomous vehicles while ensuring valid constraints will be met. The language generates code for multiple controllers that will operate alternatively to allow for fast and effective programming of vehicle trajectories using primitive motions. In addition to improving coding efficiency and reducing the number of programming errors, the language adds a level of abstraction so that autonomous vehicle behaviors may be generated by people with little knowledge of low-level details of the car’s operation. Furthermore, this language ensures safe operation of the vehicle by enforcing a set of user-definable constraints on the output path. A main set of constraints that are applied to every generated path have been specifically chosen to enforce safe switching between controllers and prevent the planning of unsafe actions. A novel application of the language is its ability to permit users to add specific constraints for a particular path; these constraints are checked for validity after the main constraint check is performed.