Roborace this weekend showed its self-driving Robocar on the city streets of Formula E’s Paris ePrix, making it the first driverless car on the streets of Paris.
The driverless race car performed a demonstration for the crowds at Les Invalides in the French capital and wowed the fans with a successful showcase of its autonomous capabilities. The demonstration saw the car negotiate its way around 14 turns of the 1.9km circuit without a human in the vehicle, entirely self-driven by autonomous software.
“We are extremely proud and excited to see the Robocar perform this demonstration in front of all the fans in Paris,” said Roborace CEO Denis Sverdlov. “It is another major milestone on this incredible journey. The team has worked so hard to get us to this point in a short amount of time, the car is alive and it has emotion and its own personality already. Roborace is the only company in the world right now testing driverless technologies on city streets without a human in the car – this is something truly unique.”
The Robocar is designed by Daniel Simon, the automotive futurist who creates vehicles for Hollywood sci-fi blockbusters including Tron Legacy and Oblivion, It weighs 1000kg and measures 4.8m long and 2m wide. It has 4 motors of 300kW each, a 540kW battery and is capable of speeds over 200mph. The car uses a number of technologies to ‘drive’ itself including 5 lidars, 2 radars, 18 ultrasonic sensors, 2 optical speed sensors, 6 AI cameras, GNSS positioning and is powered by Nvidia’s Drive PX2 brain, capable of up to 24 trillion A.I. operations per second to be programmed by teams’ software engineers using complex algorithms.
At the car’s unveiling in Barcelona in February, Chief Design Officer Daniel Simon said: “This needs to be the superhero of self-driving cars. An ambassador for this amazing rise of artificial intelligence.”
Roborace’s open A.I. platform allows 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” to ensure all efforts will be focussed on advancing the software for everyday road cars to adopt.
Roborace will continue to perform demonstrations at Formula E events during the remainder of the season.
Meet Aston Martin F1’s incredible moving data centre
The Aston Martin Red Bull Racing team faces a great deal more IT challenges than your average enterprise as not many IT teams have to rebuild their data center 21 times each year and get it running it up in a matter of hours. Not many data centers are packed up and transported around the world by air and sea along with 45 tonnes of equipment. Not many IT technicians also have to perform a dual role as pit stop mechanic.
The trackside garage at an F1 race is a tight working environment and a team of only two IT technicians face pressure from both the factory and trackside staff to get the trackside IT up and running very fast. Yet, despite all these pressures, Aston Martin Red Bull Racing do not have a cloud-led strategy. Instead they have chosen to keep all IT in house.
The reason for this is performance. F1 is arguably the ultimate performance sport. A walk round the team’s factory in Milton Keynes, England, makes it abundantly clear that the whole organization is hell bent on maximizing performance. 700 staff at the factory are all essentially dedicated to the creation of just two cars. The level of detail that is demanded in reaching peak performance is truly mind blowing. For example, one machine with a robotic arm that checks the dimensions of the components built at the factory is able to measure accuracy to a scale 10 times thinner than a human hair.
This quest for maximum performance, however, is hampered at every turn by the stringent rules from the F1 governing body – the FIA. Teams face restrictions on testing and technology usage in order to prevent the sport becoming an arms race. So, for example, pre-season track testing is limited to only 8 days. Furthermore, wind tunnel testing is only allowed with 60% scale models and wind tunnel-usage is balanced with the use of Computational Fluid Dynamics (CFD) software, essentially a virtual wind tunnel. Teams that overuse one, lose time with the other.
In order to maximize performance within uniquely difficult logistical and regulatory conditions, the Aston Martin Red Bull Racing team has had to deploy a very powerful and agile IT estate.
According to Neil Bailey, Head of IT Infrastructure, Enterprise Architecture and Innovation, their legacy trackside infrastructure was “creaking”. Before choosing hyperconverged infrastructure, their “traditional IT had reached its limits”, says Bailey. “When things reach their limits they break, just like a car,” adds Bailey.
The team’s biggest emphasis for switching to HPE’s hyperconverged infrastructure, SimpliVity, was performance. Now, with “the extra performance of SimpliVity, it means it doesn’t get to its limits,” says Bailey. HPE SimpliVity has helped reduce space, has optimized processing power and brought more agility.
One of the first and most important use cases they switched to hyperconverged infrastructure was post-processing trackside data. During a race weekend each car is typically fitted with over 100 sensors providing key data on things like tyre temperature and downforce multiple times per second. Processing this data and acting on the insights is key to driving performance improvements. With their legacy infrastructure, Bailey says they were “losing valuable track time during free practice waiting for data processing to take place.” Since switching to HPE SimpliVity, data processing has dropped from being more than 15 minutes to less than 5 minutes. Overall, the team has seen a 79% performance boost compared to the legacy architecture. This has allowed for real time race strategy analysis and has improved race strategy decision making.
Data insights helps the team stay one step ahead, as race strategy decisions are data driven. For example, real time tyre temperature data helps the team judge tyre wear and make pit stop decisions. Real time access to tyre data helped the team to victory at the 2018 Chinese Grand Prix as the Aston Martin Red Bull cars pitted ahead of the rest of the field and Daniel Ricciardo swept to a memorable victory.
Hyperconverged infrastructure is also well suited to the “hostile” trackside environment, according to Bailey. With hyperconverged infrastructure, only two racks are needed at each race of which SimpliVity only takes up about 20% of the space, thus freeing up key space in very restricted trackside garages. Furthermore, with the team limited to 60 staff at each race, only two of Bailey’s team can travel. The reduction in equipment and closer integration of HPE SimpliVity means engineers can get the trackside data center up and running quickly and allow trackside staff to start work as soon as they arrive.
Since seeing the notable performance gains from using hyperconverged infrastructure for trackside data processing, the team has also transitioned some of the factory’s IT estate over to HPE SimpliVity. This includes: Aerodynamic metrics, ERP system, SQL server, exchange server and the team’s software house, the Team Foundation Server.
As well as seeing huge performance benefits, HPE SimpliVity has significantly impacted the work patterns of Bailey’s team of just ten. According to Bailey, the biggest operational win from hyperconverged infrastructure is “freeing up engineers’ time from focusing on ‘business as usual’ to innovation.” Traditional IT took up too much of the engineers’ time monitoring systems and just keeping things running. Now with HPE SimpliVity, Bailey’s team can “give the business more and quicker” and “be more creative with how they use technology.”
Hyperconverged infrastructure has given Aston Martin Red Bull Racing the speed, scalability and agility they require without any need to turn to the cloud. It allows them to deliver more and more resources to trackside staff in an increasingly responsive manner. However, even with all these performance gains, Aston Martin Red Bull Racing has been able to reduce IT costs. So, the users are happy, the finance director is happy and the IT team are happy because their jobs are easier. Hyperconvergence is clearly the right choice for the unique challenges of Formula 1 racing.
Body-tracking tech moves to assembly line
Technology typically used by the world’s top sport stars to raise their game, or ensure their signature skills are accurately replicated in leading video games, is now being used on an auto assembly line.
Employees at Ford’s Valencia Engine Assembly Plant, in Spain, are using a special suit equipped with advanced body tracking technology. The pilot system, created by Ford and the Instituto Biomecánica de Valencia, has involved 70 employees in 21 work areas.
Player motion technology usually records how athletes sprint or turn, enabling sport coaches or game developers to unlock the potential of sport stars in the real world or on screen. Ford is using it to design less physically stressful workstations for enhanced manufacturing quality.
“It’s been proven on the sports field that with motion tracking technology, tiny adjustments to the way you move can have a huge benefit,” said Javier Gisbert, production area manager, Ford Valencia Engine Assembly Plant. “For our employees, changes made to work areas using similar technology can ultimately ensure that, even on a long day, they are able to work comfortably.”
Engineers took inspiration from a suit they saw at a trade fair that demonstrated how robots could replicate human movement and then applied it to their workplace, where production of the new Ford Transit Connect and 2.0-litre EcoBoost Duratec engines began this month.
The skin-tight suit consists of 15 tiny movement tracking light sensors connected to a wireless detection unit. The system tracks how the person moves at work, highlighting head, neck, shoulder and limb movements. Movement is recorded by four specialised motion-tracking cameras – similar to those usually paired with computer game consoles – placed near the worker and captured as a 3D skeletal character animation of the user.
Specially trained ergonomists then use the data to help employees align their posture correctly. Measurements captured by the system, such as an employee’s height or arm length, are used to design workstations, so they better fit employees.