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.
Automatic Testing of an Autonomous Parking System Using Evolutionary Computation
Sae Technical Papers
SAE 2004 World Congress & Exhibition ; 2004
2004-03-08
Conference paper
English
Automatic Testing of an Autonomous Parking System Using Evolutionary Computation
British Library Conference Proceedings | 2004
|Automatic testing of an autonomous parking system using evolutionary computation
Automotive engineering | 2004
|Automatic testing of an autonomous parking system using evolutionary computation
Tema Archive | 2004
|Automatic Testing of an Autonomous Parking System Using Evolutionary Computation
British Library Conference Proceedings | 2004
|