A method for testing an autonomous driving system, comprising: obtaining scenario description information of a testing scenario; characterized in that, the method further comprises: analyzing the scenario description information by natural language understanding or by a pre-trained machine learning model to determine a scenario risk, a scenario probability and a scenario complexity corresponding to the testing scenario; obtaining a scenario weight of the testing scenario according to the scenario risk, the scenario probability and the scenario complexity; and determining the number of testing times corresponding to the scenario weight, wherein the autonomous driving system is to be tested in the testing scenario for the number of testing times, and wherein the number of testing times increases as the scenario weight increases, wherein obtaining the scenario weight of the testing scenario according to the scenario risk, the scenario probability and the scenario complexity comprises: determining a risk level according to the scenario risk, determining a probability level according to the scenario probability, and determining a complexity level according to the scenario complexity; and obtaining the scenario weight of the testing scenario, according to a summing result of weight values corresponding respectively to the risk level, the probability level and the complexity level. obtaining scenario description information of a testing scenario; characterized in that, the method further comprises: analyzing the scenario description information by natural language understanding or by a pre-trained machine learning model to determine a scenario risk, a scenario probability and a scenario complexity corresponding to the testing scenario; obtaining a scenario weight of the testing scenario according to the scenario risk, the scenario probability and the scenario complexity; and determining the number of testing times corresponding to the scenario weight, wherein the autonomous driving system is to be tested in the testing scenario for the number of testing times, and wherein the number of testing times increases as the scenario weight increases, analyzing the scenario description information by natural language understanding or by a pre-trained machine learning model to determine a scenario risk, a scenario probability and a scenario complexity corresponding to the testing scenario; obtaining a scenario weight of the testing scenario according to the scenario risk, the scenario probability and the scenario complexity; and determining the number of testing times corresponding to the scenario weight, wherein the autonomous driving system is to be tested in the testing scenario for the number of testing times, and wherein the number of testing times increases as the scenario weight increases, wherein obtaining the scenario weight of the testing scenario according to the scenario risk, the scenario probability and the scenario complexity comprises: determining a risk level according to the scenario risk, determining a probability level according to the scenario probability, and determining a complexity level according to the scenario complexity; and obtaining the scenario weight of the testing scenario, according to a summing result of weight values corresponding respectively to the risk level, the probability level and the complexity level. determining a risk level according to the scenario risk, determining a probability level according to the scenario probability, and determining a complexity level according to the scenario complexity; and obtaining the scenario weight of the testing scenario, according to a summing result of weight values corresponding respectively to the risk level, the probability level and the complexity level.