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CES: BlackBerry QNX launches new car OS

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At CES in Las Vegas this week, BlackBerry announced its QNX Software Development Platform 7.0. This 64-bit OS is said to raise the bar for security and performance in cars.

At CES 2017 in Las Vegas this week, BlackBerry announced its most advanced and secure embedded operating system (OS) for the automotive industry. QNX Software Development Platform 7.0 (QNX SDP 7.0) is a 64-bit OS that “raises the bar for security and performance in cars”. At CES 2017, the technological capabilities of QNX SDP 7.0 is being demonstrated in BlackBerry QNX’s 2016 Jaguar XJ and 2017 Lincoln MKZ concept cars.

“With the push toward connected and autonomous vehicles, the electronic architecture of cars is evolving – from a multitude of smaller processors each executing a dedicated function, to a set of high performance domain controllers, powered by 64-bit processors and graphical processing units,” said John Wall, senior vice president and head of BlackBerry QNX.

“To develop these new systems, our automotive customers will need a safe and secure 64-bit OS that can run highly complex software, including neural networks and artificial intelligence algorithms. QNX SDP 7.0 is suited not only for cars, but also for almost any safety- or mission-critical application that requires 64-bit performance and advanced security. This includes surgical robots, industrial controllers and high-speed trains.”

BlackBerry provided the following information:

QNX SDP 7.0 provides high performance and enhanced kernel-level security through an array of features, including microkernel architecture, file encryption, adaptive time partitioning, a high availability framework, anomaly detection, and multi-level policy-based access control.

Featuring the next-generation QNX Neutrino Realtime OS and QNX Momentics Tool Suite, this reliable OS helps guard against system malfunctions, malware, and cyber attacks by implementing a multi-level, policy-driven security model that incorporates best-in-class security technology from BlackBerry. The OS also offers a safety pedigree proven by certification to ISO 26262 ASIL D (the highest level achievable) for automobiles and to IEC 61508 SIL 3 for industrial automation systems, and by compliance with IEC 62304 for life-critical Class III medical devices.

As automakers look to consolidate domain functions such as infotainment, telematics, and digital instrument clusters into a virtual cockpit controller, QNX SDP 7.0 provides a realtime OS that supports 64-bit for the ARMv8 and Intel x86-64 architectures, along with virtualization capabilities. QNX SDP 7.0 can help ensure that these automated systems perform all processes and actions reliably, within the pre-defined amount of time needed for successful and safe execution.

Must-See Concept Cars at CES

BlackBerry QNX is unveiling a Jaguar XJ concept car with a new digital cockpit design that combines the infotainment and instrument cluster functionality. It shows two operating systems running safely and securely on a single System-on-a-Chip (SoC) processor. BlackBerry QNX hypervisor software safely separates and isolates the infotainment system and graphics, meaning the infotainment system can safely re-start without affecting the instrument cluster. BlackBerry worked with Rightware Cluster UI to build the QNX Cluster graphics monitor that can detect failures in the safety system.

The Jaguar XJ concept car also features BlackBerry’s QNX Acoustics Management Platform (AMP) for clear high-definition in-car communication, active noise control, and engine sound enhancement.

BlackBerry QNX is also taking the wraps off of its autonomous Lincoln MKZ concept car, showing QNX SDP 7.0 capabilities in action on Renesas’ CES test track. BlackBerry QNX worked with Renesas, the University of Waterloo, and Polysync to develop the prototype vehicle that demonstrates Society of Automotive Engineers (SAE) Level 4 autonomous driving capabilities.

Using LiDAR, radar, forward-facing cameras, global positioning systems (GPS), and inertial measurement units (IMU), the car can detect obstacles on the road, anticipate dangerous driving situations, and present warnings to avoid collisions to keep drivers and passengers safe. The QNX Platform for ADAS processes data generated from the sensors in realtime, and also records and plays back the data off-line for feature development and testing.

Also on display at BlackBerry’s CES booth is a 2017 Aston Martin Vanquish model that is now shipping with BlackBerry QNX’s latest in-vehicle infotainment software technology. The new infotainment system is the control center, seamlessly integrating audio, hands-free communication and vehicle status technologies into the cabin. It also has an upgraded satellite navigation system with a quicker address input, advanced traffic information, and support for Apple CarPlay.

BlackBerry Radar

BlackBerry is also showcasing BlackBerry Radar, its secure end-to-end hardware and software asset tracking solution for the transportation and logistics industry. Radar provides more sensor readings, more often than any other solution on the market today. This allows customers to accurately monitor assets, manage yards, analyze utilization, measure efficiency, and reduce theft based on a near realtime view of the fleet.

Availability

QNX SDP 7.0 is the latest in a string of momentum updates BlackBerry has made in its software transformation, and comes less than a month after the company released a mobile-native, secure software platform for the Enterprise of Things, and two weeks after the unveiling of the BlackBerry QNX Autonomous Vehicle Innovation Centre. The beta release of QNX SDP 7.0 is available now for evaluation and product development. General availability is scheduled for Q1 2017.

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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.

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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.”

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Motor Racing meets Machine Learning

The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK

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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.

DeepRacer on the inside

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.

DeepRacer on the outside

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.”

AWS CEO Andy Jassy unveils DeepRacer

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.

  • Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube

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