Audi dealers in Germany, the United Kingdom and Spain are now starting to deploy the Audi VR experience, a fully functional virtual reality application for customer consultation at dealerships.
The Audi VR experience is being launched as the first fully functional virtual reality application for customer consultation at dealerships.
Audi dealers in Germany, the United Kingdom and Spain are now starting to deploy the virtual reality headset installation, with additional markets and locations to follow. With the VR solution, customers can get an extremely realistic experience of their individually configured car, down to the last detail. The VR experience explains Audi technologies intuitively and offers customers the opportunity to immerse themselves virtually in extraordinary moments from the world of the four rings. As part of Audi’s comprehensive initiative for digital innovation at dealerships, the VR experience is completely integrated into the brand’s IT systems.
“With the VR experience we have developed a full-fledged sales tool for Audi dealers. It offers our customers more information and certainty when making their purchasing decision, as well as a special excitement factor,” says Nils Wollny, Head of Digital Business Strategy/Customer Experience at AUDI AG. “With this, we are taking the next step in our strategy to combine digital innovation with the strengths of the bricks-and-mortar dealership.”
Digital technologies like the VR headset allow dealers for the first time to present the entire Audi model range, including all equipment options, during the customer dialogue. Originating at Audi City, the digital showroom concept for downtown locations, the brand is bringing a variety of digital solutions to dealerships throughout the markets. More than 400 “Customer Private Lounges” – a digitalized consulting suite – are already in use, and additional locations coming soon. The new VR experience adds to the dealer’s digital toolbox.
With the VR headset, prospective buyers can configure their individual dream car and explore even the smallest details from an extremely realistic perspective, selecting from several hundred million possible models and equipment variants. The VR application allows users to become completely immersed in the virtual world, conveying an all-encompassing, detailed image prior to the purchase decision. The configured Audi is experienced in three dimensions and 360 degrees, with all light and sound effects. Various environments, times of day, and light conditions also contribute to the true-to-life virtual experience of sitting in the car. The interior can also be observed from every perspective, down to the surface of the decorative inlays, depending on the position relative to the virtual light source.
The visualization through the Audi VR experience is based on the construction data of the Audi models. An “x-ray vision” can therefore allow tech-savvy users to also take a look beneath the surface of the car, into the structure of its technical components. Future VR software upgrades will also offer demo features about Audi innovations that can be tested only to a limited extent during a real test drive – such as different light technologies at night and in poor visibility.
In addition, the VR headset offers customers the chance to experience special Audi moments an expectation that more and more customers associate with buying a car. Racing fans can, for instance, immerse themselves virtually in the atmosphere of the Le Mans 24 Hours race: reminiscent of Audi victories at this iconic endurance race, the customer gets an up-close experience during a pit stop alongside the crew of mechanics.
In most markets, dealerships will run the VR application on the Oculus Rift headset from Audi’s primary project partner Oculus. To allow the complex data models to be processed for virtual reality, Audi worked with its strategic visualization partner Zerolight to develop an especially high-performance graphics engine. The Audi VR experience was introduced for the first time in a beta version for test operation in 2015 at selected dealers in Brazil and Germany. Feedback from customers and dealers has enriched the further development of the system.
Virtual reality is used by Audi in numerous areas of the company – from sales and technical development to automotive production. For example, the company uses VR headsets to train logistics employees for their assignments at the worldwide production plants of the four rings.
Project Bloodhound saved
The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.
Two weeks ago, and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.
“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.
“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”
Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.
“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.
“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”
The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.
The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”
Motor Racing meets Machine Learning
The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK
The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.
Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.
Now there’s a new name to add to the roster of technology giants driving the future.
Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com, last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.
AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.
But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.
AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.
Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.
As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.
“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.
“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”
Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information.
During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.
This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.
“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.