A Trajectory-Based Method for Scenario Analysis and Test Effort Reduction for Highly Automated Vehicle 2019-01-0139

Unlike the test of passive safety of traditional vehicles, highly automated vehicles (HAV) need more capabilities to be tested. Besides, there are more parameter combinations for the scenarios that need to be tested for each capability, resulting in a high time-consuming and costs for the autonomous vehicle tests. This paper proposes a method for scenario analysis and test effort reduction. Firstly, the trajectories of the vehicle under test (VUT) in the scenario are analyzed, and the trajectories which lead to the test mission failure are obtained. Based on the above trajectories, the threshold that lead to the test mission failure, or a combination of thresholds are analyzed. The above thresholds or a combination of thresholds values are defined as Scenario Character Parameter (SCP). The process of the analysis of the SCPs are related to the abilities of the HAV, but does not depend on the specific algorithm of the HAV. Therefore, through the above analysis of trajectories and SCPs, the ability of the scenario to measure the performance of HAVs can be quantized. After completing the analysis of scenarios that are used in HAVs evaluation, the SCPs corresponding to each scenario are obtained. The SCPs have the relationships such as overlapping or inclusive. Then, a set of scenarios with minimum number but still cover all SCPs can be searched. Use this set of scenarios to replace the original combination of test scenarios, the number of scenarios that need to be tested can be reduced. The method proposed in this paper reduces the amount of tests and costs for HAVs, which will be a promote to the development of the HAV technology.