A multitude of scholars and industry professionals acknowledge that autonomous driving is a predominant trend in automotive innovation, influencing the industry alongside trends in electric and shared mobility as well as connectivity of vehicles. These technological trends that shape the automotive industry are fueled by the increasing demand of younger generations of drivers which prioritize digital technologies, access to information, comfort, convenience, and the sharing instead of owning mobility. As autonomous driving has not only the potential to redefine the automotive landscape, but also other societal topics such as urban planning, it seems crucial to understand its historical evolution, geographical dynamics, key players and key applications. In contrast to existing fragmented case studies or small-scale samplings, this study is the first to offer a comprehensive analysis of the evolution of autonomous driving by using an extensive patent dataset comprising over 23,000 priority-patents dating back to 1960. By synthesizing this huge dataset, we uncover the development of autonomous driving, hereby, revealing how key players, applications, and markets have shaped its journey. Thus, this research not only contributes to understanding the historical landscape but also provides strategic foresight for stakeholders navigating the future of mobility.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Decoding the Patent Landscape: Insights into the Evolution of Autonomous Driving

  • Daniel Runkel,
  • Michael Stephan

摘要

A multitude of scholars and industry professionals acknowledge that autonomous driving is a predominant trend in automotive innovation, influencing the industry alongside trends in electric and shared mobility as well as connectivity of vehicles. These technological trends that shape the automotive industry are fueled by the increasing demand of younger generations of drivers which prioritize digital technologies, access to information, comfort, convenience, and the sharing instead of owning mobility. As autonomous driving has not only the potential to redefine the automotive landscape, but also other societal topics such as urban planning, it seems crucial to understand its historical evolution, geographical dynamics, key players and key applications. In contrast to existing fragmented case studies or small-scale samplings, this study is the first to offer a comprehensive analysis of the evolution of autonomous driving by using an extensive patent dataset comprising over 23,000 priority-patents dating back to 1960. By synthesizing this huge dataset, we uncover the development of autonomous driving, hereby, revealing how key players, applications, and markets have shaped its journey. Thus, this research not only contributes to understanding the historical landscape but also provides strategic foresight for stakeholders navigating the future of mobility.