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.
Two-thirds of adults ready for cars that drive themselves
The latest Looking Further with Ford Trends Report reveals that behaviour is changing across key areas of our lives
Self-driving cars are a hot topic today, but if you had to choose, would you rather your children ride in an autonomous vehicle or drive with a stranger? You may be surprised to learn that 67 per cent of adults globally would opt for the self-driving car.
That insight is one of many revealed in the 2019 Looking Further with Ford Trend Report, released last week. The report takes a deep look into the drivers of behavioural change, specifically uncovering the dynamic relationships consumers have with the shifting landscape of technology.
Change is not always easy, particularly when it is driven by forces beyond our control. In a global survey of 14 countries, Ford’s research revealed that 87 per cent of adults believe technology is the biggest driver of change. And while 79 per cent of adults maintain that technology is a force for good, there are large segments of the population that have significant concerns. Some are afraid of artificial intelligence (AI). Others fear the impact of technology on our emotional wellbeing.
“Individually and collectively, these behavioural changes can take us from feeling helpless to feeling empowered, and unleash a world of wonder, hope and progress,” says Kuda Takura, smart mobility specialist at Ford Motor Company of Southern Africa. “At Ford we are deeply focused on human-centric design and are committed to finding mobility solutions that help improve the lives of consumers and their communities. In the context of change, we have to protect what we consider most valuable – having a trusted relationship with our customers. So, we are always deliberate and thoughtful about how we navigate change.”
Key insights from Ford’s 7th annual Trends Report:
Almost half of people around the world believe that fear drives change
Seven in 10 say that they are energised by change
87 per cent agree that technology is the biggest driver of today’s change
Eight in 10 citizens believe that technology is a force for good
45 per cent of adults globally report that they envy people who can disconnect from their devices
Seven out of 10 consumers agree that we should have a mandatory time-out from our devices
Click here to read more about the seven trends for 2019.
At last, cars talk to traffic lights to catch ‘green wave’
By ANDRE HAINZLMAIER, head of development of apps, connected services and smart city at Audi.
Stop-and-go traffic in cities is annoying. By contrast, we are pleased when we have a “green wave” – but we catch them far too seldom, unfortunately. With the Traffic Light Information function, drivers are more in control. They drive more efficiently and are more relaxed because they know 250 meters ahead of a traffic light whether they will catch it on green. In the future, anonymized data from our cars can help to switch traffic lights in cities to better phases and to optimise the traffic flow.
In the USA, Audi customers have been using the “Time-to-Green” function for two years: if the driver will reach the lights on red, a countdown in the Audi virtual cockpit or head-up display counts the seconds to the next green phase. This service is now available at more than 5,000 intersections in the USA, for example in cities like Denver, Houston, Las Vegas, Los Angeles, Portland and Washington D.C. In the US capital alone, about 1,000 intersections are linked to the Traffic Light Information function.
Since February, Audi has offered a further function in North America. The purpose of this is especially to enable driving on the “green wave”. “Green Light Optimized Speed Advisory” (GLOSA) shows to the driver in the ideal speed for reaching the next traffic light on green.
Both Time-to-Green and GLOSA will be activated for the start of operation in Ingolstadt in selected Audi models. These include all Audi e-tron models and the A4, A6, A7, A8, Q3, Q7 and Q8 to be produced from mid-July (“model year 2020”). The prerequisite is the “Audi connect Navigation & Infotainment” package and the optional “camera-based traffic sign recognition”.
Why is this function becoming available in Europe two years later than in the USA?
The challenges for the serial introduction of the service are much greater here than, for example, in the USA, where urban traffic light systems were planned over a large area and uniformly. In Europe, by contrast, the traffic infrastructure has developed more locally and decentrally – with a great variety of traffic technology. How quickly other cities are connected to this technology depends above all on whether data standards and interfaces get established and cities digitalise their traffic lights.
On this project, Audi is working with Traffic Technology Services (TTS). TTS prepares the raw data from city traffic management centres and transmits them to the Audi servers. From here, the information reaches the car via a fast Internet connection.
Audi is working to offer Traffic Light Information in further cities in Germany, Europe, Canada and the USA in the coming years. In the large east Chinese city of Wuxi, Audi and partners are testing networks between cars and traffic light systems in the context of a development project.
In future, Audi customers may be able to benefit from additional functions, for example when “green waves” are incorporated into the ideal route planning. It is also conceivable that Audi e-tron models, when cruising up to a red traffic light, will make increased used of braking energy in order to charge their batteries. Coupled with predictive adaptive cruise control (pACC), the cars could even brake automatically at red lights.
In the long term, urban traffic will benefit. When cars send anonymised data to the city, for example, traffic signals could operate more flexibly. Every driver knows the following situation: in the evening you wait at a red light – while no other car is to be seen far and wide. Networked traffic lights would then react according to demand. Drivers of other automotive brands will also profit from the development work that Audi is carrying out with Traffic Light Information – good news for cities, which are dependent on the anonymised data of large fleets to achieve the most efficient traffic management.
In future, V2I technologies like Traffic Light Information will facilitate automated driving.
A city is one of the most complex environments for an autonomous car. Nevertheless, the vehicle has to be able to handle the situation, even in rain and snow. Data exchange with the traffic infrastructure can be highly relevant here.