Open Source Summit Japan & Automotive Linux Summit 2020

To achieve a goal of accident-free roads with increased road safety, 5G C-V2X and autonomous driving ecosystem players are developing AI/ML enabled solutions leveraging the data from the in-vehicle sensors and traffic infrastructure. While conventional ML approaches rely on centralized servers to process the data from distributed entities, this is not always feasible in this case because of the inaccessibility of private data and large communication overhead required to transmit raw data to central ML processors. In such cases, decentralized approaches of federated learning, will be a good fit. In this presentation, we will discuss how technologies like edge computing and AI on edge can help develop context-aware 5G C-V2X use cases and provide cooperative awareness to each C-V2X enabled devices in vicinity. We will also talk about the open source frameworks to implement distributed V2X use cases and focus on key technical challenges of federated learning in wireless communications