Jinhua Chen (majoring in Applied Informatics at the Graduate School of Science and Engineering) received the Young Researcher’s Encouragement Award at the 2024 IEEE 99th Vehicular Technology Conference (IEEE VTC2024-Spring).
・Winner
Jinhua Chen (first-year PhD student in Yu Lab, majoring in Applied Informatics at the Graduate School of Science and Engineering)

・Conference
The 2024 IEEE 99th Vehicular Technology Conference: IEEE VTC2024-Spring

・Date
June 24, 2024 ～June 27, 2024

・Awarded date
June 25, 2024

・Conference Venue
Marina Bay Sands Hotel, Singapore

・Award name
Young Researcher’s Encouragement Award

・Name of award-winning paper
Enhancing Production Planning in the Internet of Vehicles: A Transformer-based Federated Reinforcement Learning Approach

・Summary of research
“The Internet of Vehicles (IoV) brings significant economic benefits to countries. However, large-scale smart vehicle production planning remains challenging in the IoV. Currently,heuristic algorithms and solvers commonly used for these problems often lack scalability and fall into local optima. Moreover, security concerns about wireless data transfer arising from multi-factory manufacturing processes are garnering attention. To address these issues, this paper introduces an algorithm, TRL, which is a Transformer-based Reinforcement Learning for vehicle production planning problems. Furthermore, we propose a Transformer-based Federated Reinforcement Learning algorithm, named TFRL, tailored for large-scale manufacturing and secure wireless communication. Experimental results showcase the high performance and security of TFRL. It schedules 1000 orders in about 14 seconds and avoids exchanging plaintext during interaction. Compared to NSGA-II, the TFRL enhances computational speed by 95.11% and reduces constraint violation scores by 93.18%.”