Mobility is essential to today’s world. We travel to get to work, to go shopping, and to meet friends and family – in short, effective transport impacts on all aspects of our modern lives. Access to mobility is critical to economic growth and progress, bringing more opportunities and better productivity. At the same time however, growing environmental concerns and a looming shortage of fossil fuels have created tension between our ever-growing demand for mobility and the health of our planet.
Growing populations, increasing urbanization and economic and social development mean that there are more cars on our roads each day. The knock-on effects of this are greater levels of congestion and longer times spent commuting, which means more stress and higher levels of aggression on the road. Skyrocketing levels of air pollution – to which transportation is one of the leading contributors – has negative effects on both health and climate change, both of which are key issues in global policy agendas.
So, the writing has been on the wall for some time. The gold standard in automotive technological progress has thus been to achieve a radical reduction of engine emissions and the development of electric cars has been at the forefront of this charge. We have now entered the beginning of a new era, as more and more of these vehicles take to the roads. Electric cars are now at the cusp of the mass market, with a steady stream of new models set to reach the consumer in future. Last week, we launched the Audi e-tron, our first all-electric-drive SUV, at a world premiere in San Francisco – one huge leap forward in pursuit of our goal. Audi will also bring more than 20 electrified models to the market by 2025, from the compact class to the full-size category. Around a dozen models will be all-electric, while the remainder will be plug-in hybrids for emission-free driving on shorter journeys.
Powering this development is ongoing improvement in battery technology, with increasing energy density and lengthened driving ranges possible between charges. Consumers have noted that they feel confident using electric cars for day-to-day use once battery technology can sustain a driving range of 300 or more kilometres, which is now possible. The Audi e-tron has a range of 400 kilometers, making it ideal for long distance driving. Drivers who charge the e-tron overnight can set off in the morning in full confidence that they won’t need to stop at a charging station as they go about their day.
What this technological progress also means however, is that the levels of power and performance achieved by an electric car draw ever closer to those of traditional engines. For anyone who loves high strung, powerful engines and the rush of adrenaline that comes from flooring the throttle on an empty stretch of road, this is no small thing. At Audi, we are lucky to be surrounded by some of the most exceptional engines ever produced, so few people understand the thrill of an extraordinary driving experience better than we do. So, the holy grail is to achieve this same performance with vastly improved economy.
The Audi e-tron’s electric drive has two asynchronous motors, one at the front, one at the rear, with a total output of 300 kW of power. This allows the Audi e-tron to accelerate from 0 to 100km/h in just 5.7 seconds.
The next step will be the development of electric cars suitable for those who regularly drive long distances, entailing further advances in battery technology, and the development of a network of charging stations across the country. The battery for the Audi e-tron is designed to last the entire life cycle of the vehicle. When charged at a high-power charging station at up to 150 kW, the Audi e-tron can be restored to 80% in less than half an hour. At 22 kW, the Audi e-tron can charge its battery to 100% in around four and a half hours.
For city dwellers, however, the age of electric mobility has well and truly arrived. Rapid advances in technology continue to drive progress; the rise of electric cars is only one of many developments set to transform transportation as we know it, heralding a cleaner, more efficient future.
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.