FLEXE: Investigating Federated Learning in Connected Autonomous Vehicle Simulations

Author(s)

Lobato, Wellington ; Da Costa, Joahannes B. D. ; de Souza, Allan M. ; Rosario, Denis ; Sommer, Christoph ; Villas, Leandro A. ; IEEE

• Document type: Journal article
• Source: 2022 IEEE 96TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2022-FALL); v. N/A, p. 5-pg., 2022-01-01.

Abstract

Due to the increased computational capacity of Connected and Autonomous Vehicles (CAVs) and worries about transferring private information, it is becoming more and more appealing to store data locally and move network computing to the edge. This trend also extends to Machine Learning (ML) where Federated learning (FL) has emerged as an attractive solution for preserving privacy. Today, to evaluate the implemented vehicular FL mechanisms for ML training, researchers often disregard the impact of CAV mobility, network topology dynamics, or communication patterns, all of which have a large impact on the final system performance. To address this, this work presents FLEXE, an Open Source extension to Veins that offers researchers a simulation environment to run FL experiments in realistic scenarios. FLEXE combines the popular Veins framework with the OpenCV library. Using the example of traffic sign recognition, we demonstrate how FLEXE can support investigations of FL techniques in a vehicular environment. (AU)

• FAPESP's process: 19/19105-3 - Dynamic vehicle cloud for autonomous vehicle application support
• Grantee: Wellington Viana Lobato Junior
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
• Grantee: Nelson Luis Saldanha da Fonseca
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 21/13780-0 - Fault-tolerant control for vehicular edge computing
• Grantee: Joahannes Bruno Dias da Costa
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• FAPESP's process: 18/16703-4 - Vehicular cloud computing for information management in intelligent transportation systems
• Grantee: Joahannes Bruno Dias da Costa
• Support Opportunities: Scholarships in Brazil - Doctorate