Research on Autonomous Vehicle Technology Innovation Ecosystem in China Based on System Dynamics
Year: 2025
Type: article
Abstract: Based on the perspective of an innovation ecosystem, the system dynamics research method is used to construct a technological innovation ecosystem model of autonomous vehicles in China. Vensim PLE software was used for simulation to obtain the development trend of technological innovation from 2015 to 2030 and to explore the impact of various elements inside the system on the overall system. This research finds that the dynamic mechanism of China’s autonomous vehicle technology innovation ecosystem mainly includes the innovation resource supply subsystem, the technology innovation diffusion subsystem, and the incentive and guarantee subsystem. Each subsystem interacts to jointly promote continuous innovation and iterative upgrading of technology. Education investment, infrastructure construction, innovation platform construction, and other factors all have a positive impact on the technological innovation level of autonomous vehicles, and the effect of multiple parameter changes is far more significant than that of single factor changes. The number of research and development patents, level of technological innovation, actual adopters of technological innovation, and benefits of technological innovation are all showing a good growth trend in the future. Accordingly, it is concluded that there should be optimization of scientific research investment strategies, acceleration of infrastructure layout, and expansion of application scenarios. These insights provide a theoretical basis and practical guidance for promoting the high-quality development of autonomous vehicle technology in China.
Source: Systems
Authors: Ruiyu Feng, Yingqi Liu, Mu Li, Fei Zhou
Institutions: Beijing Jiaotong University, Shenzhen University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: Beijing Jiaotong University
Award: G7768937468
OpenAlex ID: W4409292926
