After the steam engine, assembly line production and automation in production, digitisation is having the biggest impact on the automotive industry, writes TREVOR HILL, Head of Audi South Africa.
As the “fourth industrial revolution” championed by the World Economic Forum’s Klaus Schwab gains momentum, it’s thrilling to anticipate what this means for the automotive industry – and as a result, cities of the future.
Schwab and the WEF link the emergence of breakthrough technologies such as artificial intelligence to a revolution in how business and society function together into the future. It makes sense. But, what this vision needs most, is for industries like ours to take the lead in translating theory into a tangible reality.
As with everything today, this happens within a context of constant change. The automotive industry is itself experiencing its own “fourth revolution”, and Audi is responding by transforming itself into an automotive brand that owns the future. Our focus is on driving progress as an innovator intentionally crossing the divide between a traditional model as motor vehicle manufacturer to being a hybrid business, where our vehicles enable superior mobility for goods and people in a more modern city.
Critical to this, is how we seamlessly integrate artificial intelligence across our product range. We know that the application of artificial intelligence opens up a new dimension of performance for vehicle products and that AI has an exponential impact on what we call the “mobility value chain”.
This means embracing the fact that future growth will no longer occur in the traditional car business, but instead it will shift to the usage of mobility products and services. Areas such as autonomous driving, new and sustainable drive concepts, mobility services and digitalisation of the car and vehicle environment are all examples of where our industry should be moving.
As a digital car company, Audi is digitising all processes: from product development with virtual reality, to the factory with intelligent robots and to sales with the latest digital technology. To enable this, we have expanded our business model to ensure that services appear alongside our products.
This by no means eliminates the need for automotive production and technology, but instead makes a giant leap forward in how traditional technologies play a greater part in society through the inclusion of AI. With this in mind, we are focusing our business on developing alternative powertrains, integrated mobility solutions, autonomous driving technologies and a significantly greater level of connectivity that will help us better evolve the entire mobility value chain as soon as 2020.
Much of our focus is centered on the concept of the 25th hour. The 25th hour is built on the premise that in the future, self-driving cars will navigate fluently through the city – without a steering wheel, without a driver. Users will have free time. Free time that we at Audi call the “25th Hour” of the day.
Already, models such as the new A4 and new Q7 point the way ahead. Their online services, grouped together under the term Audi Connect, link them to the Internet, the infrastructure and to other vehicles. Their assistance systems operate predictively. For instance, they can alert the driver to a tight bend that comes just after the crest of a hill, or Traffic Jam Assist can take charge of the steering in slow-moving traffic on good roads, at a speed of up to 60 km/h. These technologies represent a pre-stage to piloted driving, which will be introduced in series production in 2017 with the next A8 generation.
Outside of what is included in the latest generation of luxury sedans, we are entering a time of swarm intelligence, where cars communicate with each other and with infrastructure, then use this information to plan optimum routes and speeds. A technology called Traffic Light Information (TLI) is already in place in Las Vegas, where it communicates with traffic lights and provides drivers with a “time to green light” countdown on the head-up vehicle display, telling them when the light is due to change.
Cars communicating with the infrastructure around them can also cut fuel consumption in urban traffic by up to 15 percent, as cars “surf the green wave”, adjusting their speed to ensure each traffic light turns green as they reach it.
The latest generation of mild-hybrid vehicles feature electrical systems that can coast with the engine switched off and the drivetrain decoupled, an extended start-stop mode and a high level of brake-energy recuperation. This is another step toward affordable, practical, fully electric vehicles
The buzzwords in automotive design these days are autonomy, intelligence and innovation. The vehicles of the future will continually learn and develop, while the technology adapts to people’s individual needs. Cars’ AI, or artificial intelligence will also suggest appropriate services and book them if desired by its passengers, like a concierge.
The latest software can also be downloaded as required, so you will be able to update your car in the same way you update your phone or your computer. From now on, your car can order functions on demand and always have the most up-to-the-minute capabilities – downloaded straight from the internet, as you need them.
The car of the future will be a car uniquely customised to client needs. It will be constantly learning, updating its knowledge and fine-tuning the user experience to suit the driver’s preferences. Your car can create working conditions that are even more pleasant and productive than in the office.
Piloted parking is another revolutionary innovation already available in the cars of today, such as the new Audi A8. You no longer even need to be seated in your vehicle while you park – your car does it all for you, more accurately and requiring less parking space.
This has further implications for urban design, as the space required for parking areas can be reduced. Indeed, the very idea of mobility is changing. Even the principle that you need to own a single personal vehicle to be mobile is being questioned.
Car companies are offering mobility solutions that allow you to pick up a car when required, or to change the model of car you drive several times during a year. Thanks to advancements in automation, innovation and artificial intelligence, motoring and mobility is about to change permanently. How we get around has always been part of what defines us humans, and we are about to take a quantum leap into an exciting new phase of our existence.
It’s quite a time to be alive.
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.