no code implementations • 23 Oct 2023 • Hao Guo, Collin Meese, Wanxin Li, Chien-Chung Shen, Mark Nejad
The results indicate that the proposed system can facilitate secure and decentralized federated learning for real-world traffic prediction tasks.
no code implementations • 31 May 2023 • Maryam Shaygan, Collin Meese, Wanxin Li, Xiaolong Zhao, Mark Nejad
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a critical problem globally, resulting in negative consequences such as lost hours of additional travel time and increased fuel consumption.
no code implementations • 23 Jun 2020 • Zijia Zhong, Mark Nejad, Earl E. Lee
Intersection is a major source of traffic delays and accidents within modern transportation systems.
Multiagent Systems
no code implementations • 16 Mar 2020 • Zijia Zhong, Earl E. Lee, Mark Nejad, Joyoung Lee
For both of the clustering strategy, CAVs increase the average lane change frequency for HVs.
Multiagent Systems