Processing power in autonomous vehicles

August 20, 2018 //By Bryce Johnstone
Processing power in autonomous vehicles
During the course of the next 20-30 years, autonomous vehicles (AVs) will transform our driving habits, the transportation industry and wider society. We will not only be able to hail a car to our doorstep and send it away once used, AVs will also challenge the idea of personal car ownership, as well as have a positive impact on the environment and congestion. It’s expected that by 2030, one in four cars on the road will be self-driving (ABI Research).

Industry experts have defined five levels in the progression of autonomous driving. Each level describes the extent to which a car takes over the task and responsibility from the driver, and how the car and driver interact. A feature such as adaptive cruise control is an

example of an Advanced Driver Assistance Systems (ADAS) and can be considered a Level 1 capability. Currently, some new cars appearing on the market are achieving Level 2 functionality, but as an industry, we have barely scratched the surface of ADAS systems, let alone full autonomy.

Fig. 1: the five levels of autonomous driving.

The levels of autonomous driving

As we go through the levels of autonomy, processing power will be vital to achieving the vision of full autonomy, where the driver can have “hands off, eyes off and brain off”. At this stage, people in the car are just passengers and as there is no driver, there is no need for a steering wheel. However, before we get there we should first understand the various levels between non-autonomous to fully autonomous driving.

There are three main elements to ADAS/AV; sensing, compute and actuation.

Sensing captures the current state of the world around the vehicle. This is done using a mix of sensors – RADAR (long and medium range), LIDAR (long range), Camera (short/medium range), infrared and ultrasonic. Each of these senses and captures its own variant of the surrounding environment that it ‘sees’. It locates objects of interest and importance within this view, such as cars, pedestrians, road signs, animals and the curvatures of the road.

Fig. 2: What the car sees LIDAR, RADAR & Camera views.

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