创新科技2024，Vol.24Issue(12)：78-89,12.DOI:10.19345/j.cxkj.1671-0037.2024.12.7
基于专利挖掘的智能网联汽车领域关键共性技术识别研究
Research on Identification of Key Generic Technologies in Intelli-gent Connected Vehicle Field Based on Patent Mining
摘要
Abstract
Intelligent connected vehicles,which result from the deep integration of new-generation communication technologies,artificial intelligence,and the Internet,have become a focal point for global industrial innovation and a significant direction for future development.To further promote intelligent transportation and enhance national competitiveness,it is essential to identify and advance key generic technologies.These technologies can be widely applied across multiple industries or fields and profoundly impact various sectors.Breakthroughs in these areas are crucial for collaboration across the industrial chain and enhancing innovation capacity.This study,therefore,focuses on the domain of intelligent connected vehicles,systematically explor-ing and identifying key generic technologies to provide theoretical and practical guidance for technological research and development as well as strategic planning.This study employs a pat-ent text mining approach to identify key generic technologies,constructing an identification framework based on the LDA(Latent Dirichlet Allocation)model.The process begins with data collection and preprocessing,followed by extracting hidden technological themes from patent texts using the LDA model.These themes are then quantitatively analyzed from three dimen-sions:①Universality analysis.This involves using indicators such as technical theme intensity and co-occurrence rates to evaluate the broad applicability of technologies across various fields.②Profitability analysis.This measures the importance and economic benefits of technologies through the volume of patent applications and their trends.③Relevance analysis.This assesses the interrelation and mutual influence among technological themes based on their co-occurrence strengths.Through these analyses,key generic technologies in the domain of intelligent con-nected vehicles are gradually screened and ultimately identified. This study uses the incoPat patent database as its data source,selecting 19 928 valid patent texts related to intelligent connected vehicles from 2015 to the present.By applying the afore-mentioned key generic technology identification framework,nine key generic technologies are ul-timately identified:data storage,high-precision maps,path planning,image acquisition,in-vehicle terminals,environmental perception,alarm systems,intelligent operating systems,and wireless communication.These technologies demonstrate extensive application potential and eco-nomic value while also exhibiting strong interconnections and mutual reinforcement during their development.This study systematically identifies key generic technologies in the domain of intel-ligent connected vehicles by constructing an identification framework based on the LDA model and leveraging patent mining techniques.Theoretically,the study enriches the methodologies for identifying key generic technologies and deepens the exploration of technological innovation paths in this field.Practically,the results provide clear directions for technological break-throughs to both governments and enterprises,assisting governments in formulating technology development policies and enabling enterprises to optimize resource allocation and conduct their research and development more effectively.Notably,the nine key generic technologies identified in this study encompass the core technological areas essential for the development of the intelli-gent connected vehicle industry,offering robust support for technological planning and industrial collaboration.关键词
专利挖掘/智能网联汽车/关键共性技术/技术识别/技术主题Key words
patent mining/intelligent connected vehicle/key generic technology/technology identification/technical topic分类
社会科学引用本文复制引用
苏平,李莹..基于专利挖掘的智能网联汽车领域关键共性技术识别研究[J].创新科技,2024,24(12):78-89,12.基金项目
重庆市教委人文社科基地重点项目"军民一体化下国防专利技术转移转化应用政策制度体系与实现机制研究"(24SKJD131). （24SKJD131）
