Evaluation Model of Intelligent Vehicle Test Conditions Based on Risk Degree and Complexity Degree

Abstract

In order to study the quantitative evaluation of the effectiveness of intelligent vehicles under test conditions, the risk model based on driving risk field was improved and the complexity degree of each element of driving environment was defined. Considering risk degree and complexity degree coverage and the maximum and distribution of user and test conditions, an evaluation model of user and test conditions based on risk degree and complexity degree was constructed. The validity of three tests was analyzed and evaluated using examples. The results showed that the effectiveness index could be used to evaluate the effectiveness of the test conditions quantitatively.