Research on driving safety enhancement strategies for intelligent driving ecosystem based on deep learning technology

In recent years, safety issues in intelligent driving have occurred frequently. Deep learning technology, through continuous learning, has provided new ideas for its development. The intelligent driving ecosystem is supported by deep learning technology, covering the whole process of data acquisition, processing, and driving safety prevention, effectively supporting the iterative upgrading of the technology. This paper employs the methods of evolutionary games and supernetworks to systematically examine different behavioral analyses and conduct numerical simulation verification The results show that: (1) The higher the initial willingness of intelligent driving enterprises to participate, the more significant the positive facilitation effect is exerted by deep learning technology. (2) The government’s policy of directing scientific research institutions to support intelligent driving enterprises with deep learning has not had a positive effect but instead may have disrupted or destroyed the existing market landscape. (3) There is an interaction effect between the strategies of each subject, and deep learning technology, as an important tool, can effectively guide the intelligent driving ecosystem to improve driving safety. This paper provides an essential methodological reference for exploring the integration path of deep learning technology and the intelligent driving ecosystem to effectively improve driving safety.