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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.

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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.

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Cars connect to traffic lights

New Jaguar Land Rover technology using Vehicle-to-Infrastructure (V2X) connects cars to traffic lights so drivers can avoid getting stuck at red and help free up traffic flow in cities.

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The world’s first traffic lights were installed exactly 150 years ago outside the Houses of Parliament in London. Since then drivers around the globe have spent billions of hours waiting for green. With Jaguar Land Rover’s latest tech, however, their days could be numbered.

The Green Light Optimal Speed Advisory (GLOSA) system allows cars to “talk” to traffic lights and inform the driver the speed they should drive as they approach junctions or signals.

Widespread adoption of the V2X technology will prevent drivers from racing to beat the lights and improve air quality by reducing harsh acceleration or braking near lights. The goal is for the V2X revolution to create free-flowing cities with fewer delays and less commuter stress.

The connected technology is currently being trialed on a Jaguar F-PACE, as part of a £20 million (R371 million) collaborative research project.

Like all Jaguar or Land Rover vehicles today, the F-PACE already boasts a wide range of sophisticated Advanced Driver Assistance (ADAS) features. The connected technology trials are enhancing existing ADAS features by increasing the line of sight of a vehicle when it is connected via the internet to other vehicles and infrastructure. GLOSA is being tested alongside a host of other measures to slash the time commuters spend in traffic.

For example, Intersection Collision Warning (ICW) alerts drivers when it is unsafe to proceed at a junction. ICW informs drivers if other cars are approaching from another road and can suggest the order in which cars should proceed at a junction.

Jaguar Land Rover has also addressed time lost to searching for a parking space by providing real-time information of available spaces to drivers and developed an Emergency Vehicle Warning to alert motorists when a fire engine, police car or ambulance is approaching. The advanced technology builds on the connected systems already available on the Jaguar F-PACE such as Adaptive Cruise Control.

Oriol Quintana-Morales, Jaguar Land Rover Connected Technology Research Engineer, said: “This cutting-edge technology will radically reduce the time we waste at traffic lights. It has the potential to revolutionise driving by creating safe, free-flowing cities that take the stress out of commuting. Our research is motivated by the chance to make future journeys as comfortable and stress-free as possible for all our customers.”

The trials are part of the £20 million government-funded project, UK Autodrive, which has helped accelerate the development of Jaguar Land Rover’s future self-driving and connected technology. As well as strengthening the Midlands’ position as a hub of mobility innovation. Britain’s biggest car maker, headquartered in Coventry, is working on connected technology as part of its pledge to deliver zero accidents, zero congestion and zero emissions.

Connected technology will link the vehicle to everything around it, allowing seamless, free-flowing traffic that will pave the way for delivering self-driving vehicles.

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Roborace reveals new vehicle

Roborace has given its fans a first look at what the new competition vehicle for Season Alpha will look like at the WebSummmit conference in Lisbon, Portugal.

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DevBot 2.0 utilizes sensors similar to that in Robocar and is also fully electric, but has the addition of a cockpit for a human driver.

Season Alpha will see teams comprising of both a human driver and an AI driver. Lap times from the duo will be compared with that of other human + machine teams to determine a winner.

DevBot 2.0 will be launched in the new year but Roborace CEO Lucas Di Grassi has shared some first glimpses of what 2019 holds for the series in an interview on stage at WebSummit.

Season Alpha will see teams compete starting in Spring 2019 using the DevBot 2.0 vehicles to develop their automated driving systems, with professional drivers teaching the AI how to improve, as well as learning from the AI how to better their own performance.

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