A Simulation Testing Framework for Intelligent Power Platform under Complex and Diverse Weather Conditions
The problem of autonomous vehicle testing and evaluating under complex and adverse weather conditions is addressed,and a method based on knowledge graph is proposed to represent and quantify the typical weather-traffic elements,as well as a simulation framework to model and reproduce the complex weather scenarios.The current situation and challenges of autonomous vehicle testing and evaluation are analyzed,the existing simulation platforms and their limitations are introduced.The structural and seman-tic features of knowledge graph are used to systematically divide and describe the complex weather condi-tions and traffic scenarios,providing data support for the simulation tests.Finally,a"same-picture"method is adopted to effectively fuse and present different weather conditions and traffic scenarios,provid-ing a platform for the performance evaluation of autonomous vehicles under various complex situations.
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