A Study on the Construction of Automobile Working Scenario Library Using GooSeeker Crawlers Software and Element Matrices

In the context of upward branding of automobiles and upgrading of marketing strategies, this paper combines the advantages of user-driven architecture and multilevel architecture, and puts forward an optimization method for the construction of automobile working condition scenario library that integrates user needs and is oriented to technical marketing. Starting from the perspective of causes of vehicular traffic accidents, incorporating user concerns, we use cause analysis, cluster analysis and correlation analysis and other methods to establish a perfect hierarchical relationship of elements based on the theory of scenario definition, process the data information types obtained by web crawlers, and complete the element matrix to generate the automotive working condition scenario library by using the exhaustive enumeration method. And based on the construction process, we explore the application of automotive working condition scenario library system, providing support and reference for technological innovation and product development using scenario data.