Big steps in AI

Audi presents pre-development technology at the Neural Information Processing Systems conference in California.

The scope of Audi’s Artificial Intelligence (AI) continues to impress and point to a stunning future with the company showing extraordinary new technology at the NIPS conference in the US.

5 December, 2017


As the mainstream reality of autonomous driving comes ever closer, all eyes are on Long Beach in California this week for the annual NIPS conference (Neural Information Processing Systems), where Audi is presenting exciting new technology that brings the reality even closer.

Last year Audi became the first automotive brand to take part in the conference, which takes place each December and this year returns as a co-sponsor. Perhaps the most important international meeting on AI, it allows leaders in their respective fields to showcase new technology and ideas that further the world of AI. This year, Audi is showing pre-development technology that will allow vehicles to accurately map in 3D their environments, allowing for unprecedented levels of accuracy in navigation and dealing with the material world around them.

The new technology uses a mono camera that uses AI to generate an extremely precise 3D model of a vehicle’s environment.
A requirement for automated driving is a mapped image of the environment that is as precise as possible – at all times. Artificial intelligence is a key technology for this. 

A project team from the Audi subsidiary Audi Electronics Venture (AEV) is presenting a mono camera at the Conference that uses artificial intelligence to generate an extremely precise 3D model of the environment. This technology makes it possible to capture the exact surroundings of the car.
A conventional front camera acts as the sensor. It captures the area in front of the car within an angle of about 120 degrees and delivers 15 images per second at a resolution of 1.3 megapixels. These images are then processed in a neural network which is where semantic segmenting occurs, in which each pixel is classified into one of 13 object classes. This enables the system to identify and differentiate other cars, trucks, houses, road markings, people and traffic signs.
The system also uses neural networks for distance information. The visualisation is performed here via ISO lines – virtual boundaries that define a constant distance. This combination of semantic segmenting and estimates of depth produces a precise 3D model of the actual environment.
Audi engineers had previously trained the neural network with the help of ‘unsupervised learning’.

In contrast to supervised learning, unsupervised learning is a method of learning from observations of circumstances and scenarios that does not require pre-sorted and classified data. The neural network received numerous videos to view of road situations that had been recorded with a stereo camera. As a result, the network learned to independently understand rules, which it uses to produce 3D information from the images of the mono camera. The project of AEV holds great potential for the interpretation of traffic situations.

In addition, the Audi team from the Electronics Research Laboratory of Belmont, California, are demonstrating a solution for purely AI-based parking and driving in parking lots and on highways. In this process, lateral guidance of the car is completely carried out through neural networks. The AI learns to independently generate a model of the environment from camera data and to steer the car.

In developing autonomous driving cars, Audi is benefiting from a large network in the artificial intelligence field of technology. The network includes companies in the hotspots of Silicon Valley, in Europe and in Israel.

The new Audi A8 (pictured) is the first car in the world developed for conditional automated driving at Level 3 (SAE). The Audi AI traffic jam pilot handles the task of driving in slow-moving traffic up to 60km/h, provided that laws in the market allow it and the driver selects it.

 

"Audi is showing pre-development technology that will allow vehicles to accurately map in 3D their environments, allowing for unprecedented levels of accuracy in navigation and dealing with the material world around them."