Automatic Testing of an Autonomous Parking System Using Evolutionary Computation

The method of evolutionary functional testing allows it to automate testing by transforming the test case design into an optimization problem. For this aim it is necessary to define a suitable fitness function. In this paper for an autonomous parking system two different approaches for fitness functions are presented, which evaluate the quality of parking maneuver automatically. A numerical analysis shows, that the proposed area criterion supports a faster convergence of the optimization compared to the proposed distance criterion and that the proposed area criterion describes an efficient method to find functional errors in an automated way.