Autonomous driving paper index
The interplay between AI and technological relatedness in shaping regional innovation in Europe
One-line summary
This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity. Using a novel three-way longitudinal dataset (670 four-digit CPC classes × 302 NUTS-2 regions × nine four-year periods, 1986–2021) and leveraging a deep learning-based identification of AI patents, we show that two broad mechanisms operate in parallel. First, in accordance with the extant literature, technologies that are cognitively close to a region’s existing patent portfolio enjoy higher patenting activity, confirming that relatedness remains a strong and persistent predictor of innovative output. Second, local AI endowments are positively associated with patenting across technological fields, even after conditioning on relatedness, indicating that AI plays an enabling and cross-cutting role in a given regional innovation system. Moreover, the interaction between relatedness and AI turns out to be negative and statistically significant, implying that AI attenuates the extent to which local innovative efforts depend on the technology’s proximity to the regional portfolio. In sum, AI appears to enhance overall local innovative activity while reducing its reliance on pre-existing regional knowledge structures.
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