Ever-increasing urbanisation and the demand for development of cities is the catalyst needed to bridge both the greatest challenges and most creative solutions for a future of automotive sector, writes TREVOR HILL, head of Audi South Africa.
Ever-increasing urbanisation and the subsequent demand for development of cities is the catalyst needed to bridge both the greatest challenges and most creative solutions for a future of automotive sector. What we face now is undoubtedly the next automotive revolution.
And, it makes sense.
The city is where human life is expected to take the most significant quantum leap. Associated with this, is demand for technology that keeps (or even exceeds) the pace of how society will itself expect to be mobile.
According to McKinsey, Africa is urbanising faster than any other region – where cities are projected to gain an estimated 24-million more people each year until 2045. If the McKinsey numbers stack up, then it follows course that as an automotive sector our own investment in technology and innovation must adapt at a faster pace to meet what will be changing mobility demands.
The most logical question is, how?
For Audi, this starts with the integration of the car and its environment, especially as physical car ownership is expected to decline over time. Critical to this is an appreciation that ownership is not necessarily an indication of slower mobility demand, but rather points to the need to drive progress around innovation in the mobility space. Our work through the Audi Urban Future Initiative is just such a case in point. The initiative is an internal, interdepartmental think tank dedicated to issues of urban mobility.
The city and the car have been interacting for generations, but this latest phase of their evolution is different. Instead of urban planners designing cities around the automobile, engineers and developers are now designing cars around the functionality of the city.
With this in mind, Audi has pushed ahead with cooperation agreements with Boston and Mexico City, where we are working in partnership with local government to explore how Audi innovation technologies can be applied in an urban environment to trigger maximum benefit for both residents and businesses.
In the Boston metropolitan area, Audi is testing the advantages of its new technologies for the city in two different pilot projects. In the transformation of the city centre, car-to-X technologies will improve the traffic flow; while at the same time – automated parking will contribute to creating more space for other modes of traffic. In addition to this, Audi is working with the real-estate developers to combine the benefits of automated parking and smart fleet management.
The third Audi Urban Partnership is a joint project in Santa Fe, one of the leading business districts in Mexico City. Here, Audi is working with the association of the business district to develop ways to end permanent traffic congestion.All three projects profile the successes of our investment in technology and our ability to adapt to changing demands that will respond to the next automotive revolution.
This paradigm shift towards mobility that is compatible with the city will eventually make for an intelligent, sustainable and liveable city with zero emissions and networked traffic that flows easily. And at the heart of this new concept will be the individual, accessing mobility in the way most convenient to him or her, in harmony with the city, the environment and other road users.
As automakers, we are privileged to be at the apex of this pivotal innovation moment, where digitalization, sustainability and urbanization come together for our next great leap forward. While we are synonymous with making cars, we are also reinventing the way cars are used. In the future, many will choose not to own their cars, but to access them on demand.
Part of the newly defined future will be machine learning, where a computer, in our case the car operating system, learns from specific situations, and can later handle unforeseen events. The more miles it clocks, the better it becomes. At Audi, we have already developed a model car that uses machine learning for intelligent parking strategies. In the next step, we will transfer that to a real car.
Indeed, the car of the near future will be constantly collecting masses of data to facilitate automated driving in a type of traffic swarm intelligence. One car on its own knows little; many cars know a lot. Each individual car can help enhance the overall performance of all cars by providing data via the cloud.
Carmakers are finding solutions for many of cities’ greatest challenges. Electric mobility will – for example – reduce emissions. Self-parking cars will cut the space needed for parking, freeing up room to improve the quality of urban life. Intelligent car interfaces with traffic light information will optimise traffic flow.
With the legacy mobility model, having caused many of the environmental issues we currently face, a reinvention according to principles of artificial intelligence and connectivity could make city living more efficient and more enjoyable while also helping to put life on earth on a more sustainable path
The trigger to a smart future mobility system is one that benefits all stakeholders. For Audi, urbanisation is a vital source for future business solutions. That’s why it has become a central part in our corporate strategy. It is something that we are gearing our business and our cars towards and something we are excited to share with our customers in the places they live, work and shop.
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.