Metamorphic Testing of Driverless Cars. - ZHI QUAN ZHOU; LIQUN SUN (Communications of the ACM, 2019)
The article discusses the use of metamorphic testing to test driverless cars, specifically their untestable software, detecting fatal errors in autonomous vehicles' onboard computer systems. Topics include metamorphic testing's cost-effective ability to address the oracle problem and the automated test-case-generation problem, and the use of both LiDAR obstacle perception to determine an object's shape and position and radar to estimate the velocity of moving obstacles in autonomous vehicles.