AI and digital twin at the heart of IndyCar racing

The digital twin, AI and predictive analytics help fans simulate IndyCar Series races with NTT, including the iconic Indianapolis 500. Learning optical sensing combined with crowd flow monitoring also provides valuable indicators to the organizers of these American automobile races.

When Marcus Ericsson, driver of the Chip Ganassi Racing team, won the Indianapolis 500 last May, it was in a car equipped with more than 140 sensors exporting data feeding in particular predictive analysis algorithms, but also motor racing fans. NTT, a Japanese telecom operator and partner of Penske Entertainment for the NTT IndyCar Series, including the Indy 500 race, collected around 8 billion data points from sensors in Marcus Ericsson’s car and those of his 32 competitors. With data collected from previous seasons and the first five events of the NTT IndyCar Series, NTT uses a combination of data analytics, digital twins and artificial intelligence (AI) to give fans access to insights in-depth, real-time information on overtaking, pit stop predictions and other race elements.

“From a business and sporting perspective, our sport has always been about developing technology,” said SJ Luedtke, vice president of marketing at IndyCar. « If you go back to the early days of the Indianapolis Motor Speedway, it was, in some ways, built as a proving ground for the emerging auto industry and a place where many automakers based here in Indianapolis and across the Midwest could bring in their latest inventions and test them.” Today, according to SJ Luedtke, NTT and IndyCar are continuing that tradition by thinking about how to use data beyond the track to drive engagement. « We want to take all of this technology and the data it creates and find ways to create elements of engagement off the track for our fans, sponsors and other stakeholders involved in the sport, in order to make it more engaging, more entertaining, and ideally attract other fans who may not be interested in automobiles, but who may be very tech-savvy and love data and/or storytelling,” explains she.

Improve the experience of motor racing fans

To this end, NTT creates a digital twin for each car in the series. Historical data provides a baseline, and each car is equipped with over 140 sensors that collect millions of data points during the race to feed the digital twin. This data ranges from speed and oil pressure to tire wear and G-forces. NTT uses AI and predictive analytics on digital twin data to provide fans with insights that previously , were only accessible to race team engineers, including race strategies and predictions, interceptions and battles for position, the performance impact of pit stops and the effects of fuel levels and tire wear.

IndyCar provides this information to fans through its interactive app and social media channels. He also provides information to the NBC production team. “There is an opportunity for our most avid fans to connect with a sport they love or a driver or team they love,” says SJ Luedtke. « That’s where the data and analytics come in. We’re working with the team to take those millions of data points over a 90-minute run and help fans understand what’s going on. »

Make predictions with AI

For example, says SJ Luedtke, it’s common to watch the front of the race, but sometimes what happens in the middle of the pack gets lost in the fray. “People are vying for places to move up in the overall point system,” she adds. « We’re able to look at that data in real time and then start making predictions using AI and the smart platform. » You might not change the channel if the NBC analyst mentions that your favorite driver is in position seven, but could go past position six in five laps because they’re in contention for the championship, she continues.

« We also have the ability to bring in casual viewers to help them understand what’s going on in the race, » she adds. « Being able to tell a story of why someone got ahead through different key components, or data based on two drivers’ pit stops, allows us to explain the sport to new fans. » In just over three years, IndyCar has doubled the engagement and dwell time in its race weekend app, says SJ Luedtke. « It’s about being able to watch your favorite driver’s telemetry in real time in sync with the onboard camera while racing, so you feel like you’re in the cockpit with them, » she says. « You see a lot of the telemetry and key data points working in their vehicle. »

To a more connected site

On technology, Bennett Indart, vice president of Smart World Solutions at NTT, calls the partnership « a priority business approach » to « improve the fan experience, encourage others to play the sport, provide forum to enrich IndyCar with data”. To this end, NTT also uses the data to improve the on-site fan experience. It deployed its Smart Venue solution at the Indianapolis Motor Speedway (IMS). The app is inspired by efforts to create connected cities attracting more than 350,000 fans on race days.

« We think of it more as the idea of ​​mobilizing and planning how a city will operate for a day, whether it’s moving people around, serving them through emergency services, or being able to see around corners where we could send someone before an incident even occurs,” says SJ Luedtke. For IndyCar, Smart Venue’s AI provides total venue visibility, with data calibrated every 30 seconds with greater than 90% accuracy. AI-based optical sensing technologies, combined with real-time gateway throughput data, enable crowd movement monitoring, analysis and escalation of alerts. They also provide information on crowding and congestion at specific gates and tunnels. Ultimately, this provides better response times to respond more effectively to potential issues and risks.

For supporters, the Smart Venue gives better insight into the quickest and least congested routes through the world’s biggest sporting event. “On any given race day, it becomes the second largest city in Indiana,” says Indart. “You can imagine 350,000 people trying to get to the Indianapolis Motor Speedway. For several years, we have been helping the operations team understand where the bottlenecks are. This year we actually added a feature to provide that to the fans themselves on their mobile devices.” “It’s all about data and data-driven approaches to solving business scenarios,” adds Indart.

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