At Mobile World Congress, Ericsson launched the Connected Vehicle Marketplace, which allows Original Equipment Manufacturers (OEMs), partners and motorists to be part of innovation and connectivity in the automotive industry.
Ericsson has launched a solution to reduce the complexities of building digital service ecosystems for connected vehicles. Called the Connected Vehicle Marketplace, it allows Original Equipment Manufacturers (OEMs), partners and motorists to be part of innovation and connectivity in the automotive industry.
Scania becomes the first customer to use the new solution, with Scania One, an open customer platform that gives fleet owners, drivers and fleet owners’ customers, access to services that will help increase efficiency and productivity, while contributing to a reduced carbon footprint.
Building on the success of the Ericsson Connected Vehicle Cloud, the Connected Vehicle Marketplace is a controlled and secure environment for OEMs to put new digital services into the hands of their drivers. The solution is the first of its kind and will enable OEMs to fully control the inclusion of third-party digital services seamlessly and efficiently, all integrated into one digital marketplace.
Börje Ekholm, President and CEO of Ericsson, announced the new Connected Vehicle Marketplace during Ericsson’s Media and Analyst briefing at Mobile World Congress in Barcelona on February 27.
Ekholm says: “Empowering innovation is crucial for Ericsson, and is an essential part of the successful future for not only the automotive industry, but also a whole host of others. We are committed to enabling the right mix of connectivity, security and ideas across all industries, and today’s launch of Connected Vehicle Marketplace for the automotive industry is just one example of this.”
Through the connected vehicles, Scania knows the logistical flow in the operations of fleet owners’ customers, ranging from large-scale construction sites, to public transport, to long haul transport. With Scania One, the digital tools are placed in the hands of fleet owners and drivers to ensure gains in these flows are realized and waste is eliminated.
“Compared to many other industries, the transport industry is making rapid progress in digitalization. However, we cannot make this shift alone and this is a great example of the kind of partnership that moves both our industries forward,” says Henrik Henriksson President and CEO, Scania. “Now we are taking some serious steps translating the partnership into real business for us with bottom line impact for our customers.”
Roger Lanctot, Associate Director in Global Automotive Practice, Strategy Analytics, says: “Ericsson is in a position to deliver almost any content, service or application to any device or use case, whether it’s in the home, car, or on a mobile device. With its horizontal IoT capabilities, proven today towards the connected vehicle, Ericsson now brings together all possible usage scenarios.”
The number of connected vehicles is growing rapidly – both for commercial vehicles and passenger cars. Scania has announced that there are now 250,000 connected vehicles, which amounts to more than two-thirds of all vehicles it has sold the past five years. Moreover, Strategy Analytics predicts 382 million connected vehicles by 2025.
Until now, there was no way for OEMs to share data efficiently, securely and in a scalable manner with third-parties. Ericsson’s Connected Vehicle Marketplace enables OEMs to create a connected ecosystem for core partners as well as innovators who want to come up with new innovative services for the automotive industry, to realize the full potential of connected vehicles.
Ericsson Connected Vehicle Cloud is powered by Ericsson’s IoT solution – IoT Accelerator – bringing secure world-class mobile connectivity management and trustworthy technology partnership, with IoT E2E systems, and rapid IoT deployment and monetization capabilities.
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.