Towards a dynamic edge ai framework applied to autonomous driving cars

Abstract

This work proposes an innovative solution in the field of Edge AI in order to efficiently exploit new hardware components available on the market at low cost. Edge AI means that algorithms are processed locally on a hardware device. The algorithms use data (sensor data or signals) that are created on the own device. The idea of this paper focuses on demonstrating the validity of the proposed solution by implementing an autonomous driving system that exploits communication between intelligent agents. In this case, our self-driving cars are equipped with a low-cost device that allows you to recognise objects along the way and consequently take actions by running a machine learning model. The presence of a machine learning model also allows the developer to modify it by extending the flexibility and application possibilities of the proposed solution.