In a rapidly evolving automotive industry, where machine learning (ML) and deep learning (DL) technologies are becoming the backbone of innovation, a new study offers a comprehensive look at global patent trends. Published in the journal *Artificial Intelligence*, the research, led by ChoongChae Woo of the Department of AI Mobility at Hanseo University in South Korea, analyzed 5,314 patent applications filed between 2005 and 2022 across the five major patent offices (IP5). The findings provide a roadmap for industry stakeholders and policymakers, highlighting both opportunities and potential blind spots in the race to dominate smart mobility.
The study identifies seven key sub-technology domains where ML and DL are making waves in the automotive sector. Vehicle control and infrastructure traffic control lead the pack, reflecting the industry’s focus on autonomous driving and smart transportation systems. However, emerging growth in battery management and occupant analytics suggests a shift toward enhancing vehicle efficiency and passenger experience. “The concentration of patents in these areas underscores the industry’s priorities,” Woo explains, “but it also reveals gaps that could become critical in the future.”
One of the most striking findings is the disparity in patenting strategies among major automotive players. Companies like Toyota and Bosch are pursuing a balanced approach, securing patents across the United States, Europe, and China, while others, such as Ford and GM, are focusing on dual-market coverage in the U.S. and China. This divergence highlights how market priorities, regulatory environments, and technological objectives shape corporate strategies. “The data shows that firms are tailoring their patent portfolios to align with their strategic goals,” Woo notes, “whether that’s global dominance or targeted market penetration.”
Geographically, the United States leads in overall patent filings, but Japan stands out with a notably high share of triadic patents—those filed in the U.S., Europe, and Japan—indicating a strong global reach. This suggests that Japanese companies are positioning themselves for international competition, a strategy that could pay off as the automotive industry becomes increasingly interconnected.
Perhaps the most concerning revelation is the underrepresentation of security-related technologies in patent filings. As vehicles become more connected and autonomous, cybersecurity will be paramount. “This is a potential blind spot in current innovation efforts,” Woo warns. “Addressing this gap will be crucial for ensuring the safety and reliability of future automotive technologies.”
The study’s insights are particularly relevant for the energy sector, where advancements in smart mobility could drive demand for innovative energy solutions. As electric and autonomous vehicles become more prevalent, the need for efficient battery management and intelligent infrastructure will grow, creating new opportunities for energy companies to collaborate with automotive manufacturers.
By mapping the technological and strategic landscape of ML/DL innovation in the automotive industry, this research provides actionable insights for industry practitioners and policymakers alike. As Woo concludes, “Understanding these trends can help stakeholders optimize their intellectual property portfolios and guide future R&D agendas.” For the energy sector, this means staying ahead of the curve by investing in technologies that align with the automotive industry’s evolving needs. The road ahead is paved with innovation, and those who navigate it wisely will shape the future of smart mobility.