Metamorphic Testing Harness for the Baidu Apollo Perception-Camera Module

As the complexity of autonomous driving systems (ADSs) increases, the question of how to organize testing in an efficient manner has become a serious issue. This study investigates the potential for metamorphic testing (MT) to evaluate the perception-camera module of an open-source autonomous driving system (ADS), namely Baidu's Apollo ADS. The experiments revealed inconsistent obstacle identification results when increasing the brightness of a specific region of the driving scenarios, both in individual and sequential frames, demonstrating the ability of MT to address the oracle problem when testing the perception module of ADSs. Furthermore, this paper presents an MT harness to facilitate ADS testing, which would increase efficiency and help testers to better organize the testing procedure. We also present an industry case study to demonstrate its use in actual production phases.