Audi Q2 ‘deep learning concept’ explores possibility of self-learning intelligent parking technology

Article by Christian A., on December 6, 2016

Autonomous cars are slowly but surely gaining more appeal among drivers around the world. While a complete self-driving system has yet to be launched, carmakers have been finding ways to make sure it would be plausible and viable in the near future.

Now, Audi is showcasing at the Conference and Workshop on Neural Information Processing Systems (NIPS) in Barcelona, Spain (December 5 to 10, 2016) a new technology that it believes would be one of the keys for autonomous cars – a self-learning system that could intelligently park by itself. Developed by Audi subsidiary Audi Electronics Venture (AEV), this technology is showcased through an Audi Q2 small crossover – more specifically a 1:8 scale model car – that could develop intelligent parking strategies. In a sense, this model car called the “Audi Q2 deep learning concept” is able to learn through trial and error. How does this concept achieve that?

Of course, there is a lot of sensing involved. The Audi Q2 deep learning concept is installed with sensor technology that makes use of two mono cameras – one mounted on the front facing forward and another fitted on the posterior facing rearward. In addition, this sensor technology makes use of 10 ultrasonic sensors installed around the Audi Q2 deep learning concept. These two cameras and ultrasonic sensors transmit data to a central on-board computer that in turn translates these data into control signals for steering and the electric motor.

To demonstrate the ability of the Audi Q2 deep learning concept, Audi featured an area that measures 3 meters x 3 meters, representing a parking area. Without any outside interference, the Audi Q2 deep learning concept autonomously tries to look for a suitable parking space (marked by a metal frame). Here, the Audi Q2 deep learning concept will first – through its sensors – ascertain its current position in relation to the parking space. Then, the model’s central on-board computer will then calculate how the Audi Q2 deep learning concept would drive – in a safe manner – to the selected parking space. As needed, the Audi Q2 deep learning concept would maneuver forward or in reverse, steering accordingly until it has safely parked in the intended space. Amazing, isn’t it?

But what is more amazing is what underpins this ability self-parking ability – something that Audi called as “deep reinforcement learning” or what we call learning through trial and error. Every successful maneuvers and actions of the Audi Q2 deep learning concept is being recorded autonomously by an algorithm logs successful actions, thereby gaining more knowledge through experience. Then, this algorithm refines the parking strategy for the Audi Q2 deep learning concept. Take note that this is a continuous process, which means that the more the system learns, the more it could tackle harder parking maneuvers.

Audi Electronics Venture – based in Gaimersheim, Germany –plans to transfer this technology to a real Audi car. The carmaker, meanwhile, plans to employ this system in 2017 in the central driver assistance controller (zFAS) in the next generation of the Audi A8.

Press Release

Automatic intelligent parking: Audi at NIPS in Barcelona

It’s one of the world’s most important specialist conferences for artificial intelligence: Every year the Conference and Workshop on Neural Information Processing Systems (NIPS) presents advances in the fields of machine learning and computational neuroscience. Audi is showcasing its expertise at the conference for the first time. From December 5 to 10, 2016, in Barcelona, the premium automaker is showing with the aid of a scale model how a car develops intelligent parking strategies. The car manufacturer is also providing specialists and potential applicants with information on jobs in innovative fields.
Self-learning systems are a key technology for piloted driving cars. That’s why Audi has already built up a wealth of know-how in machine learning. The company is the only automaker represented at NIPS with its own stand and a showcase. A 1:8 scale model car – the “Audi Q2 deep learning concept” – is demonstrating an intelligent parking process. On an area measuring 3 x 3 meters, it autonomously searches for and finds a suitable parking space in the form of a metal frame, and then parks itself there.

The Audi Q2 deep learning concept’s sensor technology consists of two mono cameras, facing forward and toward the rear, along with ten ultrasonic sensors positioned at points all around the model. A central on-board computer converts their data into control signals for steering and the electric motor. On the driving surface, the model car first determines its position relative to the parking space. As soon as it perceives the position, it calculates how it can safely drive to its targeted destination. The model car maneuvers, steers and drives forward or in reverse, depending on the situation.

The model car’s parking ability is made possible by deep reinforcement learning. In other words, the system essentially learns through trial and error. To begin, the car selects its direction of travel at random. An algorithm autonomously identifies the successful actions, thus continually refining the parking strategy. So in the end the system is able to solve even difficult problems autonomously.

The Audi Q2 deep learning concept is a pre-development project of Audi Electronics Venture (AEV), an AUDI AG subsidiary in Gaimersheim, Germany. In the next step, the developers are transferring the parking-space search process to a real car.

The Audi global network encompasses not only research institutes, but also companies from hotspots in California’s Silicon Valley, Europe and Israel. The premium manufacturer is working with partners including Mobileye, the world’s leading company in the field of image recognition. In this partnership, the two companies combined their expertise to develop a deep learning-based software for environment perception systems. Audi will use the software for the first time in 2017, in the central driver assistance controller (zFAS) in the new generation of the Audi A8. NVIDIA, a leader in the field of hardware systems with an associated development environment, was an important partner in the development of the zFAS. These technical solutions will enable the customer to enjoy piloted driving in traffic jam situations as well as piloted parking.

Audi is further intensifying its collaborations with partners from high-tech industries through an increasing degree of integration of components with artificial intelligence (AI). These forms of artificial intelligence are important for dealing with challenging situations such as urban traffic. It enables piloted driving cars to evaluate their complex surroundings and perform necessary driving maneuvers accordingly.

Also at NIPS to gain insights into these and other exciting developments will be AI specialists interested in working on innovations at Audi. Specialists and HR experts from the company will be at the event to provide them with information on a range of career opportunities. At Audi the specialists will have opportunities to help shape the role of AI in the automotive industry by applying their knowledge in the areas of machine learning, cloud computing, data analytics and vehicle architecture.

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