To simultaneously enable multiple autonomous driving services on affordable embedded systems, we designed and implemented {\pi}-Edge, a complete edge computing framework for autonomous robots and vehicles. The contributions of this paper are three-folds: first, we developed a runtime layer to fully utilize the heterogeneous computing resources of low-power edge computing systems; second, we developed an extremely lightweight operating system to manage multiple autonomous driving services and their communications; third, we developed an edge-cloud coordinator to dynamically offload tasks to the cloud to optimize client system energy consumption. To the best of our knowledge, this is the first complete edge computing system of a production autonomous vehicle. In addition, we successfully implemented {\pi}-Edge on a Nvidia Jetson and demonstrated that we could successfully support multiple autonomous driving services with only 11 W of power consumption, and hence proving the effectiveness of the proposed {\pi}-Edge system.
@article{arxiv.1901.04978,
title = {PI-Edge: A Low-Power Edge Computing System for Real-Time Autonomous Driving Services},
author = {Jie Tang and Shaoshan Liu and Bo Yu and Weisong Shi},
journal= {arXiv preprint arXiv:1901.04978},
year = {2019}
}