Fuente: Sustainability - Revista científica (MDPI) Sustainability, Vol. 18, Pages 2334: Identification of Key Core Technologies and Competitive Landscape Analysis for Intelligent Vehicles Based on Patent Data
Sustainability doi: 10.3390/su18052334
Authors:
Yiping Song
Yan Lin
Chenxi Wang
Siqi Yang

Intelligent vehicles represent a frontier in technological innovation. Effectively identifying their key core technologies and primary competitors is a crucial prerequisite for overcoming industrial technological bottlenecks, playing a pivotal role in promoting sustainable industrial development and enhancing global market competitiveness. This study is based on 46,373 authorized invention patents in the field of intelligent vehicles from 1950 to 2024 and based on four core characteristics of key core technologies: technological centrality, technological value, economic value, and competitive monopoly. Combining the entropy weight method and gray correlation analysis method, it effectively identifies 15 key core technologies in the field of intelligent vehicles, including G05D1, B60W30, G08G1, etc. These technologies cover four core domains: autonomous driving and vehicle control, intelligent transportation and vehicle–road coordination, onboard computing and data processing, and powertrain system integration and optimization. Building on this foundation, the study analyzes the technological competitive landscape from both national and corporate perspectives. The results show that the United States and Japan, with their profound technological accumulation, demonstrate strong competitive strength. China leads globally with 25.56% of worldwide patents, exhibiting rapid growth in R&D scale. However, the technological influence of key core technology patents held by major Chinese enterprises still lags significantly behind that of the United States and Japan, indicating room for improvement in R&D quality. By precisely identifying core R&D directions for intelligent vehicles, this study provides strategic guidance and practical references for optimizing green innovation resource allocation within the industry. It aims to overcome key technological bottlenecks in low-carbon intelligent vehicles, thereby achieving breakthroughs in key core technologies and enabling high-quality, sustainable industrial development.