生态驾驶智能系统与算法：专利综述
Eco-driving Intelligent Systems and Algorithms: A Patent Review
AI总结：
本文基于424项Google Patent专利，系统综述了生态驾驶智能系统与算法，重点分析了2016年后219项涉及深度学习及物理组件的专利，揭示其技术分类、五类应用方向及主要授权地域。
摘要：
交通运输行业仍然是温室气体排放的重要来源，这凸显了对智能系统提升车辆能源效率的需求。已开发系统的知识产权应通过专利加以保护。然而，目前尚无关于生态驾驶智能系统的专利综述。与科学论文不同，专利文献既表明发明人的新颖性，也表明其商业化潜力。为填补这一研究空白，本文提供了生态驾驶智能系统与算法的专利综述。本文分析了Google Patent数据库中的424项专利。专利分析结果显示，排名前三的合作专利分类为：Y02T——与交通运输相关的气候变化减缓技术（50.7%）、B60W——不同类型或不同功能的车辆子单元的联合控制（34.4%）以及B60L——电动车辆的推进（20.2%）。其中219项专利是在2016年深度学习流行之后提交的，可归为五类：车辆能量管理、智能驾驶、生态与可持续驾驶、燃油消耗降低和驾驶行为优化。此外，全部219项专利都涉及智能系统的物理组件和/或新颖的机器学习/深度学习算法。并且，其中超过70%的专利由中国国家知识产权局授予。
英文摘要：
The transportation industry remains a significant contributor to greenhouse gas emissions, highlighting the requirement for intelligent systems to enhance vehicle energy efficiency. The intellectual property rights of developed systems should be protected by patents. However, there is no patent overview of eco-driving intelligent systems. Unlike a scientific article, a patent documentation indicates both novelty and commercialization potential of an inventor. To address this research gap, this paper provides a patent overview of eco-driving intelligent systems and algorithms. 424 patents in the Google Patent database are analyzed. The patent analysis results show that the top three Cooperative Patent Classifications are: Y02T - climate change mitigation technologies related to transportation (50.7%), B60W - Conjoint control of vehicle subunits of different types or different functions (34.4%) and B60L - Propulsion of electrically-propelled vehicles (20.2%). 219 patents were filed after 2016 when deep learning became popular and can be categorized into five groups: vehicle energy management, smart driving, ecological and sustainable driving, fuel consumption reduction, and driving behavior optimization. Furthermore, all 219 patents involve the physical components of the intelligent system and/or novel machine learning/deep learning algorithms. Moreover, over 70% of them are granted by the China National Intellectual Property Administration.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
