Optimization method and system, server and medium of automatic driving failure scene library

Abstract

The optimization method and system, server and storage medium of the automatic driving failure scene library provided by the present invention determine the failure weight ratio of each factor by analyzing the failure event data recorded in the automatic driving road test process, and use the analytic hierarchy process to comprehensively obtain The complexity of the test scenario, and then determine the importance of different scenarios to the test function, the priority of different test scenario use cases, and realize the optimization of the test scenario library, which is important for the design of test scenario use cases, test implementation, and post-test evaluation. significance; and the present invention makes the failure weight ratio calculation of each factor more accurate by classifying each factor hierarchically.

Description

Technical field [0001] The present invention relates to the field of failure testing techniques in automatic driving, in particular, to an optimization method and system, server, and storage medium of automatic driving failure field boots. Background technique [0002] Driving scene data is an important resource for the development and testing of intelligent Net. It is a key data basis for redefining the intelligent automotive level. The scene library is used as a set of intelligent network cars, and the test scenario use example is also unlimited due to the continuity of the scene parameter distribution and the diversity of scene factors. Therefore, the test scene is evaluated, and the complexity of each scene is calibrated, and the priority of the test is particularly important. Inventive content [0003] In view of this, embodiments of the present invention provide an optimization method and system, server, and storage medium of automatic driving failure field boots to solve ...

AI Technical Summary

Problems solved by technology

[0003] In view of this, an embodiment of the present invention provides an optimization method, system, server, and storage medium for an automatic driving failure scene library, so as to solve the problem of using different arrangements and combinations of scene elements in the construction of existing automatic driving test scene use cases. The number of scenario use cases is increasing proportionally, and there is no corresponding system method and standard for the complexity evaluation of each scenario use case, and technical issues such as the priority and importance of the scenario use cases cannot be clarified during the test

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