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Evaluation of Different Fitness Functions for the Evolutionary Testing of an Autonomous Parking System

Joachim Wegener1 and Oliver Bühler2

1DaimlerChrysler AG, Research and Technology, Alt-Moabit 96 a, D-10559 Berlin, Germany
Joachim.Wegener@DaimlerChrysler.com

2STZ Softwaretechnik, Im Gaugenmaier 20, D-73730 Esslingen-Zell, Germany
Oliver.Buehler@stz-softwaretechnik.de

Abstract. The method of evolutionary functional testing allows for the automation of testing by transforming test case design into an optimization problem. To this end it is necessary to define a suitable fitness function. In this paper two different fitness functions are compared for the testing of an autonomous parking system. The autonomous parking system is executed with the test scenarios generated, the fitness for each test scenario is calculated on the basis of an evaluation of the quality of the parking maneuver calculated by the autonomous parking system. 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 for finding functional errors in the system in an automated way.

LNCS 3103, p. 1400 ff.

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