ACM Journal on Autonomous Transportation Systems
Special Issue on Federated Learning for Mobile Edge Computing-empowered Autonomous Vehicle Systems

Important Dates
Submission Deadline: September 30, 2023
Reviews Completed: December 30, 2023
Major Revisions: January 31, 2024
Reviews of Revision Completed: February 28, 2024
Notification of Final Acceptance: March 31, 2024
Tentative Publication: April 2024

Autonomous Vehicle Systems (AVS) generate and process privacy-sensitive data and require efficient use of communication, computation, and storage resources. To address this, federated learning (FL) enables collaborative model training while protecting data privacy, as it keeps training data on individual clients and shares locally trained models. Combining FL with edge computing in AVS creates an integrated FL-Edge system, leveraging available vehicle resources and enabling ubiquitous intelligence. However, deploying FL in MEC-empowered AVS faces challenges due to diverse system capabilities, heterogeneous data distributions, and the dynamic networking environment.

Guest Editors
Jun Huang, South Dakota State University, USA
Peng Li, Aizu University, Japan
Mohsen Guizani, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi
Joel J. P. C. Rodrigues, COPELABS, Lusófona University, Lisbon, Portugal

Click here for the full Call for Papers and submission instructions.