With the development of artificial intelligence, autonomous vehicles have become a typical application in the field of artificial intelligence. In recent 10 years, autonomous vehicles have already made considerable processes. As an uncertain system, their quality and safety have attracted much attention. Autonomous vehicletesting, especially testing the intellectual systems in autonomous vehicles (such as perception module, decision module, synthetical functional module, and the whole vehicle) gain extensive attention from both industry and academia. This survey offers a systematical review on 56 papers related to autonomous vehicle testing. Besides, this survey analyzes the testing techniques with respect to perception model, decision model, synthetical functional module, and the whole vehicle, including test case generation approaches, testing coverage metrics, as well as datasets and tools widely used in autonomous vehicle testing. Finally, this survey highlights future perspectiveson autonomous vehicle testing and provides reference for researchers in this field.