The application relates to the technical field of automatic
driving test, and discloses a
control algorithm test method based on an intelligent
driving simulator. The method comprises the following steps: collecting multi-source
test data generated by the simulator in real time; performing
wavelet transform denoising and adaptive normalization
processing on the data to generate normalized data flow; constructing a space-time graph structure model, mapping the data into graph nodes and edges, and performing space-
time alignment to generate a synchronous
data set; inputting the synchronous data into a multi-
modal feature fusion network, outputting a fusion feature atlas through cross-
modal attention weighting and feature splicing; calculating the reconstruction probability of the fusion features by using a deep generation model, and identifying abnormal test points according to a probability threshold; iteratively updating parameters by using a group optimization
algorithm, and outputting optimal parameter configurations; and driving a three-dimensional
graphics engine to generate an interactive
test scene based on the configurations, and establishing a dynamic association between the parameters and scene elements. The application realizes the
automation and intelligentization of the test process.