Abstract:This article takes the post-epidemic demand for the Intelligent & Connected Vehicles(ICV) industry as a starting point, selects 20474 patents in the Derwent database related to ICV technology, and analyzes the trend of patent applications and national/institutional applications.On this basis, this article researches technology hotspots and patentee cooperation from the perspective of social networks, and proposes the technology research and development prospects of China's ICV companies based on the characteristics of domestic enterprise technology development and cooperation status.The results show that the research of ICV technology has entered a period of steady growth, and formed three core technology and industrial development zones in North America, Europe and East Asia.The research hotspots include perception, decision-making, communication, and control systems upstream of the industrial chain.Among them, the research of control technology and its algorithm is at the relatively core position.From the perspective of cooperative network, although the technical layout of various research subjects has different emphasis, the patent cooperation relationship is weak.In the future, Chinese enterprises still need to seize the opportunity of the epidemic to tackle cutting-edge hot technologies, strengthen the inter-enterprise cooperation network and accelerate the construction of test sites.
刘颖琦, 周菲, 席锐. 后疫情时期中国智能网联汽车产业技术研究与合作网络:国际专利视角[J]. 中国科技论坛, 2021(5): 32-45.
Liu Yingqi, Zhou Fei, Xi Rui. Technology Research and Cooperative Network of China ICV Industry in the Post-Epidemic Era:the Perspective of International Patent. , 2021(5): 32-45.
[1] 李克强,戴一凡,李升波,等.智能网联汽车(ICV)技术的发展现状及趋势[J].汽车安全与节能学报,2017,8(1):1-14.
[2] KIM T J.Automated autonomous vehicles:prospects and impacts on society[J].Journal of transportation technologies,2018(8):137-150.
[3] BUI K H N,JUNG J J.Internet of agents framework for connected vehicles:a case study on distributed traffic control system[J].Journal of parallel and distributed computing,2017,116(10):89-95.
[4] GUANETTI J,KIM Y,BORRELLI F.Control of connected and automated vehicles:state of the art and future challenges[J].Annual reviews in control,2018,45(5):18-40.
[5] PATEL P,PAVITT K.The technological competencies of the world's largest firms:complex and path-dependent,but not much variety[J].Research policy,1997,26(2):141-156.
[6] FABRY B,ERNST H,LANGHOLZ J,et al.Patent portfolio analysis as a useful tool for identifying R&D and business opportunities——an empirical application in the nutrition and health industry[J].World patent information,2006,28(3):215-225.
[7] 王海波,刘羽波.基于创新力与专利竞争力分野的技术竞争力管理初探[J].电子知识产权,2017(8):64-70.
[8] BREITZMAN A F,MOGEE M E.The many applications of patent analysis[J].Journal of information science,2002,28(3):187-206.
[9] 谭红英.国际与国内车联网专利知识图谱对比分析[D].重庆:重庆大学,2014.
[10] [10]袁雨.专利网络视角下中国车联网关键技术发展研究[D].北京:北京理工大学,2015.
[11] 王雅薇,周源,陈璐怡.我国人工智能产业技术创新路径识别及分析——基于专利分析法[J].科技管理研究,2019,39(10):210-216.
[12] 邹本涛,王曰芬,曹嘉君,等.人工智能研究前沿识别与分析:基于高产作者多属性综合研究视角[J].情报理论与实践,2019,42(9):22-27.
[13] 姜宇星,王曰芬,范丽鹏,等.人工智能研究前沿识别与分析:基于主要国家(地区)对比研究视角[J].情报理论与实践,2019,42(9):8-15.
[14] 谢明远,白硕.自动驾驶专利技术分析[J].河南科技,2017(14):57-58.
[15] 施志霞.基于专利地图的自动驾驶技术发展研究[D].上海:华东理工大学,2016.
[16] 章帆,王雪娇.基于专利的无人驾驶汽车技术景观分析[J].科技管理研究,2017,37(5):33-37.
[17] 田朝辉,方思.基于专利组合的智能网联汽车企业技术竞争力评价研究[J].情报探索,2017(11):27-33.
[18] 王静,饶刚,谢晶.基于专利的智能网联汽车产业技术分析[J].中国发明与专利,2017,14(11):55-62.
[19] 李昌,伊惠芳,吴红,等.无人驾驶汽车专利技术主题分析——基于WI-LDA主题模型[J].情报杂志,2018,37(12):50-55+42.
[20] 谷林洲,邵云飞.复杂网络视角下中国新能源汽车产业的技术创新网络及其优化策略[J].技术经济,2016,35(1):16-21.
[21] 曹霞,李传云,林超然.基于新能源汽车的专利合作网络演化研究[J].科研管理,2019,40(8):179-188.
[22] 刘雅琴,余谦.新能源汽车专利合作网络的结构特征及演化分析[J].北京理工大学学报(社会科学版),2019,21(6):31-40.
[23] 王黎萤,池仁勇.专利合作网络研究前沿探析与展望[J].科学学研究,2015,33(1):55-61+145.
[24] 向希尧,裴云龙.跨国专利合作网络中技术接近性的调节作用研究[J].管理科学,2015,28(1):111-121.
[25] 柴占祥,聂天心.自动驾驶改变未来[M].北京:机械工业出版社,2018.
[26] 车云,陈卓.智能汽车:决战2020[M].北京:北京理工大学出版社,2018.