On 15 February 2026, Red Bull pilot Dario Costa made aviation history. He landed a Zivko Edge 540 aircraft on a moving cargo train. Then he took off again from the same container. No one had ever done this before.​ ​

The location was Afyonkarahisar, Türkiye. The track stretched 2.5 kilometres. The train ran at 120 km/h. Costa had a 50-second window to complete both the landing and the takeoff.​​

Blind, Fast, and Precise
The challenge sounds impossible. It nearly is. The landing required Costa to approach at near-stall speed, just 87 km/h, whilst the train ran at 120 km/h. Costa flew blind on approach. The container became visible only seconds before touchdown.

Severe wake turbulence complicated every phase of the approach. A moving target shrinks from any angle. Margins measured in centimetres, not metres. Aviation consultant Filippo Barbero described the task clearly: “Precision had to be absolute“.

Costa holds five Guinness World Records. He is the only Italian to qualify, compete and win in the Red Bull Air Race. Even for him, this project stood apart. “The greatest test was learning to land blind on a very small moving runway,” he said.

Where the Hypercar Meets Aviation
This is where Rimac enters the story. Costa needed a training tool that could replicate a high-speed, moving reference point. Nothing conventional could do the job. No simulator prepares a pilot for real-world speed alignment at 87 km/h. Only a handful of vehicles on earth reach those speeds with the required precision.​

Rimac deployed the Red Bull and the Nevera hypercar at Pula Airport in Croatia. The three-day programme gave Costa a physical, moving surface against which to practise speed synchronisation, alignment judgement, and reaction timing.​

The Nevera R delivers 2,107 horsepower through four electric motors. It covers 0–100 km/h in 1.81 seconds and hits 300 km/h in just 7.89 seconds. The car set 24 world records in 2025, including a 0–400–0 km/h run in 25.79 seconds. Top speed reached 431.45 km/h. No combustion hypercar matches that acceleration profile. Crucially, the Nevera R delivers it with absolute controllability at exactly the speeds Costa needed.​​

The standard Nevera produces 1,914 horsepower and reaches 412 km/h. Both cars use Rimac‘s next-generation torque vectoring. The system distributes power between all four wheels with microsecond precision. That precision is exactly what Costa needed on approach.​​

Engineering Beyond the Car
Rimac’s contribution went far beyond providing two hypercars. The engineering team, drawing directly on their expertise in composite structures and precision ergonomics from Nevera development, built a fully custom seat for Costa’s aircraft cockpit.​

The cockpit left almost no space. Rimac moulded the seat precisely to Costa’s body. Engineers calibrated it for maximum stability, optimal control feedback, and reduced fatigue under extreme manoeuvres. As far as the team knows, this marks the first application of this level of seat engineering in a race aircraft.​

Rimac engineers are now working with Costa on aerodynamic optimisation of his aircraft canopy using computational fluid dynamics expertise developed for the Nevera programme. The collaboration continues.​

Mate Rimac, Founder and CEO, framed the project with characteristic directness: “Dario needed to train something that had never been done before. There was no established method. Our hypercars gave him a real, moving, high-speed reference point; something only a handful of vehicles on the planet could provide“.​

Why This Matters
This project reveals something important about what performance engineering can achieve outside the motorsport circuit. Rimac built a car that broke 24 world records. Then that same car trained a pilot to land on a moving train.​​

The crossover between automotive engineering and aviation is rarely this direct. Rimac demonstrated that precision performance technology transfers across disciplines. The Nevera R exists not just to go fast. It exists to make the previously impossible, possible.



























