Proposing a framework for evaluating learning strategies in vehicular CPSs

Paper in proceeding, 2022

Highly-connected Vehicular Cyber-Physical Systems (VCPSs) offer manifold opportunities for distributing learning across the contained vehicles, road-side units and servers. However, simulating and evaluating particular distributed learning schemes poses a difficult problem in requiring realistic modeling of the vehicular fleet, communication, and the learning itself. In this work, we postulate a set of requirements for a framework simulating a complete learning workflow in a VCPS, and propose a modular architecture for it. Using a prototype implementation, we show with an example experiment the capabilities the proposed framework delivers for evaluating novel learning schemes in custom scenarios.