Biometric data fuels 1.92-second F1 pit stop
Information compiled to help improve Williams Martini crew’s performance
It will take you about 1.92 seconds to read this sentence.
That’s how long it took the Williams Martini Racing team to complete the fastest pit stop of the 2016 Formula One season at the Abu Dhabi Grand Prix, earning the DHL Fastest Pit Crew award.
Think about that: changing all four tires on an F1 car in less than two seconds. It was a combination of human effort and biometric data in the high-tech world of F1 racing.
Avanade — a global company headquartered in Seattle that provides IT consulting and services — started collecting and evaluating a range of biometric data from the Williams pit crew last season, including heart rate, breathing rate, temperature and peak acceleration. There can be as many as 20 people on an F1 pit crew and stops can include changing tires, replacing damaged parts and adjusting front wings. Refuelling was banned at the end of the 2009 season.
Montreal’s Lance Stroll and Brazil’s Felipe Massa are the two drivers for the Williams team.
Williams pit crew members wear chest straps with sensors that monitor their biometric data and that information is displayed through Avanade’s Biometrics Analytics Dashboard and monitored by Gemma Fisher, the team’s human performance specialist.
Times have certainly changed since Graeme Hackland, the Chief Information Officer of Williams Martini Racing, first started in F1 20 years ago. Hackland was hired by Williams in 2014 to lead the team’s digital transformation and he brought in Avanade to help. Hackland said Williams will admit it probably underinvested in IT and digital technology before then and had fallen behind some of the other F1 teams in that area.
Before 2014, Hackland said there was data generated by the Williams cars, but the team’s engineers weren’t seeing it in real time. One of Hackland’s first tasks was to get the data quickly to the team’s engineers at the track and back in England at Williams headquarters. There are 200 to 300 sensors built into each of the Williams cars and Hackland said that over a Grand Prix race weekend between 140 and 160 gigs of data can be analyzed if both cars complete the race. He noted that doesn’t include all the engine data Mercedes-Benz collects.
There’s also the biometric data from the pit crew. This year, Fisher is also analyzing how much sleep crew members get, along with their diet, and the crew members are working out with a physical trainer between races.
Hackland said the pit crew members weren’t thrilled at first about their biometric data being analyzed.
“It’s like anyone ... when you start capturing data about people, they worry how you’re going to use it,” Hackland said. “Are you going to pull me out of the pit stop? But, actually, how we’ve used it is to make sure that that person is performing at their optimum.” Hackland has watched video of last season’s 1.92-second pit stop and was amazed by the performance.
“I’ve actually seen the footage from above in slow motion and everything was perfect,” he said. “The driver stopped in exactly the right position … because if the driver’s slightly out, the guys have got to move and you’re losing .2, .3 of a second. So the driver stopped perfectly in the right position and everyone just executed perfectly.
“The wheel gun went on, the person taking the tire off didn’t bump into the guy putting the tire on,” Hackland added. “We didn’t have any of that in this almost perfect pit stop where just everything went right. The lights came on as they were supposed to, there wasn’t another car coming down the pit lane at the moment that we released him. So choosing when you pit someone is just as important as the rest of it.”
Heading into the Canadian Grand Prix, the Williams pit crew hadn’t been able to crack the twosecond barrier for a pit stop this year. Hackland said that’s partly due to the fact the Pirelli tires are heavier than they were last year.
But Hackland said he can see a day in the future when there is a one-second pit stop in F1.
“We think that’s doable with humans,” he said. “You could turn that into something robotic, but we think we can still achieve that with humans. It will require equipment, process and people being at their optimum performance.”
It’s like anyone ... when you start capturing data about people, they worry how you’re going to use it.