Measurements of the Benefits of Edge Computing on Autonomous Driving

Abstract

As the level of autonomous driving(AD) increases, the number of sensors in a single vehicle increases, and the required computing power also increases rapidly. The intelligence level of AD depends on algorithms and hardware performance. However, due to the problems such as limited production cost or computing resources, some vehicles may not have enough computation power for high level of AD. To overcome such obstacles, the distributed AD system architecture based on edge computing has become a trend. We build an edge computing-based distributed AD system on top of Robot Operating System(ROS2) and measure the performance with different settings. Our test results show the feasibility of AD systems centered on edge computing units, which open new research directions for exploiting edge computing in a more diverse way.