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MWC: First driverless electric race car takes stage

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Roborace this week revealed the world’s first driverless electric racing car, The Robocar, live on stage at Mobile World Congress in Barcelona.

The futuristic car was unveiled on stage by Denis Sverdlov, Roborace CEO alongside Daniel Simon, Roborace Chief Design Officer. They were delivering a keynote address on the evolution of autonomous vehicles, showing how Roborace is a platform for the world’s best engineers to advance the software that will change our roads for the better.

“This is a huge moment for Roborace as we share the Robocar with the world and take another big step in advancing driverless electric technology,” said Sverdlov. “It was very important for us that we created an emotional connection to driverless cars and bring humans and robots closer together to define our future. The progress with Devbot (the development version of Robocar) on track and building the Robocar in less than a year has been extraordinary and we cannot wait to continue the journey of learning with the Robocar.”

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Daniel Simon is the automotive futurist who creates vehicles for Hollywood sci-fi movies ,including Tron Legacy and Oblivion. Robocar weighs 975kg and measures 4.8m long and 2m wide. It has 4 motors 300kW each, 540kW battery, is predominantly made of carbon fibre and will be capable of speeds over 320kph. The car uses a number of technologies to drive itself including 5 lidars, 2 radars, 18 ultrasonic sensors, 2 optical speed sensors, 6 artificial intelligence (AI) cameras, and GNSS positioning. It is powered by Nvidia’s Drive PX2 brain, capable of up to 24 trillion AI operations per second, to be programmed by the teams’ software engineers using complex algorithms.

“Roborace opens a new dimension where motorsport as we know it meets the unstoppable rise of artificial intelligence,” said Shimon. “While pushing the boundaries of engineering, we styled every single part of the Robocar. We take special pride in revealing a functional machine that stays true to the initial concept shared, a rarity in automotive design and a testament of our determination. It’s a great feeling to set this free.”

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Roborace provides an open AI platform with fixed hardware for companies to develop their own driverless software and push the limits in an extreme and safe environment. The series is designed to be a competition of intelligence, so all teams will use the same Robocar. By ensuring the hardware is consistent, all efforts will be focussed on advancing the software.

The Robocar provides a platform for high profile brands to play a role in redefining tomorrow’s cities through technology. The launch car’s livery includes the logos of Lego, Visa, DHL, Allianz, Nvidia, Charge and Michelin.

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The ‘brain’ of the Robocar, the NVIDIA DRIVE PX 2, uses AI to tackle the complexities inherent in autonomous driving. It utilises deep learning for 360-degree situational awareness around the car, to determine precisely where the car is and to compute a safe, efficient trajectory.

“Roborace and NVIDIA today push the boundary to accelerate the development of deep learning systems for safer passenger and commercial vehicles,” said Rob Csongor, Vice-President & GM of automotive for NVIDIA.

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Roborace has been performing demonstrations with its more functional looking development cars, known as Devbots. In their last outing, the cars performed a world first as Roborace became the first company to put two driverless cars on display simultaneously on a custom-built city street track at Formula E’s ePrix in Buenos Aires. Roborace will continue to use DevBots for demonstrations and testing, introducing the Robocar into public displays during 2017 with two Robocars taking to the track together later this year.

* Follow Roborace at YouTube.com/Roborace, Facebook.com/Roborace, and @roborace on Twitter and Instagram.

 

 

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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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