Company Filing History:
Years Active: 2025
Title: Yubo Lian: Innovator in Autonomous Driving Technologies
Introduction
Yubo Lian is a prominent inventor based in Zhenjiang, China. He has made significant contributions to the field of autonomous driving through his innovative research and development. His work focuses on enhancing the capabilities of autonomous vehicles using advanced algorithms and cognitive systems.
Latest Patents
Yubo Lian holds a patent for a "Complex network cognition-based federated reinforcement learning end-to-end autonomous driving control system, method, and vehicular device." This patent presents a federated reinforcement learning (FRL) end-to-end autonomous driving control system and method, as well as vehicular equipment, based on complex network cognition. The FRL algorithm framework, designated as FLDPPO, is specifically designed for dense urban traffic. It combines rule-based complex network cognition with end-to-end FRL through a carefully designed loss function. FLDPPO employs a dynamic driving guidance system to assist agents in learning rules, enabling them to navigate complex urban driving environments and dense traffic scenarios. Furthermore, the framework utilizes a multi-agent FRL architecture, where models are trained through parameter aggregation to safeguard vehicle-side privacy, accelerate network convergence, reduce communication consumption, and achieve a balance between sampling efficiency and high robustness of the model.
Career Highlights
Yubo Lian is affiliated with Jiangsu University, where he contributes to the academic and research community. His work has garnered attention for its innovative approach to solving real-world problems in autonomous driving. His research is pivotal in advancing the technology that underpins modern vehicular systems.
Collaborations
Yubo Lian collaborates with notable colleagues, including Yingfeng Cai and Sikai Lu. Their combined expertise enhances the research output and innovation potential within their projects.
Conclusion
Yubo Lian is a key figure in the development of autonomous driving technologies, with a focus on federated reinforcement learning systems. His contributions are shaping the future of transportation and enhancing the safety and efficiency of urban driving.