智能化转型背景下自动驾驶产业化的中国实践
China's Practice of Industrializing Autonomous Driving in the Context of Intelligent Transformation
霍治方 1刘刚2
作者信息
- 1. 南开大学经济学院,天津 300071
- 2. 南开大学经济学院,天津 300071;中国新一代人工智能发展战略研究院,天津 300071
- 折叠
摘要
自动驾驶是当今交通社会转型的一种变革性力量.作为人工智能技术集中应用的典型场景,自动驾驶具备技术和社会"双重"属性,其产业化过程本质上是技术因素和社会因素相互建构的过程.基于175 家智能网联汽车企业的关系数据和819 份自动驾驶实地社会实验的问卷数据,对中国自动驾驶产业化实践方案的形成机制与理论逻辑进行系统分析.研究表明:自动驾驶在高环境嵌入性作用下,一方面嵌入中国复杂道路环境,另一方面嵌入中国独特社会环境,导致以单车智能为核心的技术路线难以为继,最终在一系列互补性技术创新和多元创新主体协同创新作用下,以车路协同为核心的智能网联汽车发展道路成为中国自动驾驶产业化的实践选择.
Abstract
Autonomous driving is a transformative force in today's transportation society.As a typical scenario for the concentrated appli-cation of artificial intelligence technology,autonomous driving possesses a"dual"nature of both technology and society.Its industrializa-tion process is fundamentally a co-construction process of technology and social factors.Based on relationship data from 175 intelligent connected vehicle companies and questionnaire data from 819 real-world social experiments on autonomous driving,a systematic analysis was conducted on the formation mechanism and theoretical logic of China's autonomous driving industrialization practice.The re-search indicates that,under the high environmental embeddedness of autonomous driving,it is embedded in China's complex road en-vironment on one hand and China's unique social environment on the other hand.This necessitates changes to the technology roadmap with a focus on single-vehicle intelligence.Ultimately,through a series of complementary technological innovations and collaborative in-novation efforts among diverse innovation actors,the development path of intelligent connected vehicles with vehicle-road coordination at its core has become the practical choice for the industrialization of autonomous driving in China.
关键词
自动驾驶/车路协同/环境嵌入/社会建构/社会实验Key words
Autonomous driving/Vehicle-road coordination/Environment embedding/Social construction/Social experiment引用本文复制引用
基金项目
中国工程院战略研究与咨询项目(2023-HY-11)
教育部哲学社会科学实验室专项基金研究项目(H0122702)
天津市智能制造专项资金项目(20201197)
出版年
2024
NETL
NSTL
万方数据