B^2SFL: A Bi-level Blockchained Architecture for Secure Federated Learning-based Traffic Prediction

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.

Federated Learning Privacy Preserving +1

Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities

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.

Time Series Traffic Prediction