Naples, 2 July 2026 – Pirelli has entered into an agreement with RIDEsense, a start-up spun out from the Department of Industrial Engineering at the University of Naples Federico II and the MegaRide Group, which specialises in the development of advanced technologies for mobility, to collaborate on the development of new software solutions to be integrated into the Pirelli Cyber Tyre ecosystem. The agreement, which grants Pirelli a licence to use RIDEsense’s virtual sensor technology and includes specific safeguards regarding the granting of rights to third parties, also provides for Pirelli to acquire a 24.99% equity stake in RIDEsense, together with an option to increase its holding up to 100% of the company’s share capital.

The integration of the physical sensors used in the Pirelli Cyber Tyre system with RIDEsense’s virtual sensors (algorithms that process information generated by the sensors already installed in vehicles) will further expand the contribution of Cyber Tyre to the vehicle’s electronic safety systems. It will also strengthen existing functions, such as aquaplaning detection, while enabling the development of new capabilities related to tyre diagnostics and, more broadly, vehicle diagnostics. The Pirelli Cyber Tyre ecosystem therefore adds another key element in its evolution towards playing an increasingly important role in ADAS and autonomous driving systems.

PIRELLI CYBER TYRE

Already fitted as original equipment on selected vehicle models currently on the market, the Pirelli Cyber Tyre system is the world’s first integrated hardware and software solution capable of collecting data from sensors embedded in tyres and processing it using Pirelli’s proprietary software and algorithms. The information is transmitted to the vehicle’s electronic systems in real time, enabling new functions integrated with driving and control systems, including ABS, ESP and traction control. The aim of Pirelli’s technology is to improve vehicle safety, performance and efficiency. It can also be used to monitor the condition of road infrastructure, helping to identify situations that may pose potential risks to road users. Pilot projects for this application are already underway in collaboration with public authorities.

RIDEsense

RIDEsense’s technology is based on physics-based algorithms that model vehicle and tyre behaviour. It is available both as software, implementing virtual sensors within standard production vehicle electronic control units (ECUs), and as hardware through the development of the dedicated Kymes platform, designed to provide direct access to the testing and motorsport markets.

“More than 20 years ago, we embarked on the journey that led to the integration of data collection and transmission capabilities into tyres, giving rise to Cyber Tyre technology. Our agreement with RIDEsense will further expand the potential of this ecosystem by strengthening its software component, which lies at the very heart of Cyber Tyre,” said Piero Misani, Chief Technical Officer at Pirelli.

“This is a significant agreement for Italy,” commented RIDEsense Chief Executive Officers Flavio Farroni and Aleksandr Sakhnevych. “It brings together Italian research and industry to take a project that began more than ten years ago in Naples, within the Vehicle Dynamics Group at the University of Naples Federico II, and supported by the University’s technology transfer structures, onto Pirelli’s production lines. As mobility becomes increasingly connected, technologies capable of delivering greater safety, efficiency and driving quality are essential. This is the objective we share with Pirelli.”

PIRELLI

Founded in Milan in 1872, Pirelli is one of the world’s leading tyre manufacturers and the only global company exclusively focused on the Consumer tyre market, which includes tyres for cars, motorcycles and bicycles. With a distinctive positioning in the High Value segment, the Group has established itself as a global brand recognised for cutting-edge technology, premium manufacturing excellence and a passion for innovation deeply rooted in its Italian heritage. Pirelli’s technological leadership is also driven by the innovation and expertise gained through more than 115 years of involvement in motorsport. Today, the company competes in more than 350 car and motorcycle racing events and has been the Global Tyre Partner of the FIA Formula One World Championship since 2011.

RIDEsense

Founded in 2023 within the MegaRide ecosystem (a spin-off from the University of Naples Federico II that has also generated innovative companies including VESevo and Grip Advisor, and acquired Wriggle Solutions), RIDEsense was launched with the support of Iniziativa Cube and Innova et Impera. The company is now based at the Campania NewSteel incubator, operating within an advanced technology ecosystem supported by strong academic and industrial partnerships and protected by an international patent portfolio safeguarding its innovations.

MegaRide, a tech-transfer holding originating from the Vehicle Dynamics group at the University of Naples Federico II, which develops real-time models to simulate tire-road interaction,announces a collaboration with TU Brno Racing, the Formula Student team of the Brno University of Technology, for the upcoming racing seasons.

Founded in 2010, TU Brno Racing brings together students from different academic backgrounds who design, manufacture and test a new single-seater each year. The team has developed multiple generations of race cars over time and regularly competes in international Formula Student events.

The collaboration focuses on supporting the team’s vehicle modeling and simulation activities through dedicated educational programmes and technical expertise in tire dynamics. TU Brno Racing will work on comparing simulation outputs with the actual behavior of the car, using this process to improve model consistency and make virtual analysis more effective during vehicle development.

The activity will allow the team to build a clearer understanding of tire dynamics and their influence on vehicle performance, supporting more informed decisions in setup definition and control strategies while reducing the need for extensive physical testing.

By bringing experience gained in top-level motorsport categories, including Formula 1, Formula E and MotoGP, into a Formula Student environment, MegaRide aims to support the practical growth of young engineers and contribute to the development of skills applied directly to vehicle dynamics.

Austria was not a race where the fastest-looking final stint automatically decided the result. On a short lap like Spielberg, the margin between strategy gain and tire-age penalty is small, and that is where Russell’s race was built.

The front group stayed on a similar strategic structure. Russell, Verstappen and Antonelli all started on medium and then completed the race on two hard stints. The difference was mainly in timing: Russell committed earlier, stopping around lap 19 and then again in the low 40s. Verstappen and Antonelli extended the middle stint and therefore had a fresher hard tire for the final phase.

The fuel-corrected lap time plot makes this trade-off quite clear. Russell’s final stint does not appear to be the lowest-degradation one of the three. His trend moves from the high 1:09s towards the mid 1:11s by the end. Verstappen shows a slightly flatter late-race evolution, while Antonelli’s last hard stint is probably the cleanest of the front group.

Estimated final-stint degradation is close rather than extreme: Russell around 0.11–0.13 s/lap, Verstappen roughly 0.10–0.12 s/lap, with Antonelli slightly lower. So the result is more a matter of when the tire performance was available and whether it could be converted into track position.

That is the key point. Russell accepted more tire age at the end, but had already placed the car in the right position before the final offset became significant. Verstappen and Antonelli came back with better tire life, but the advantage was not large enough or early enough to reverse the order.

The gapper supports the same reading. The main reshuffling comes around the pit windows, especially between laps 20 and 50. After that, the gaps compress again at the front, but without a complete change in race structure.

At team level, Mercedes has the strongest aggregate race pace, with a median just below 1:12. Red Bull, McLaren and Ferrari are packed in the same performance band, separated by only a few tenths. Racing Bulls, Audi and Alpine form the next group around the 1:13 region, while the lower midfield moves towards the mid-1:14s.

The violin plot adds a useful detail: Russell’s lap distribution is compact in the low 1:11s / low 1:12s, while Verstappen has comparable peaks but a wider spread. Antonelli’s late pace stands out, although the race had already been shaped before that final run.

In the end, this was a very technical Austria win built on the balance between degradation, pit timing and clean-air execution.

F1 BARCELONA-CATALUNYA GP 2026 | Hamilton wins it through stint pace

Hamilton’s race came together through pace, tire control and a three-stop strategy timed around the VSC. He started on soft, switched to hard, ran the medium in the middle phase and returned to hard around lap 41. That final stop cost less under Virtual Safety Car conditions and allowed him to rejoin ahead of Russell and Norris on a much fresher set. From there, he controlled the last stint and finished roughly twenty seconds clear of Russell.

The fuel-corrected plot shows how the race developed. Early on, Hamilton, Russell and Norris are close, mostly between 1:18 and 1:21 as the first sets age. The gap opens on the final hard stint. Hamilton’s fitted trend begins below 1:19 and rises to just under 1:22 by the flag. Russell runs around two to five tenths slower through much of the same phase, while Norris shows the steepest late-stint increase and ends close to 1:23.

Hamilton’s degradation rate in that final stint is roughly 0.13–0.14 s/lap. Russell is nearer 0.16 s/lap, Norris around 0.17–0.18 s/lap. The fresh hard gave Hamilton a lower starting offset and a flatter progression, enough to turn the VSC window into a decisive advantage rather than simply recover the extra pit stop.

The gapper makes the strategy easier to read. Each pit cycle reshapes the order, yet Hamilton rebuilds the margin every time. Russell and Norris remain in the same performance group; Verstappen falls towards the forty-second region and Piastri approaches one minute by the end. The late sequence exaggerates some of the final gaps, but the race had already moved in Hamilton’s direction before the last phase.

Ferrari also leads the aggregate ranking plot, with a median close to 1:22.1. Mercedes is almost level, McLaren sits around 1:22.5 and Red Bull slightly higher. Since the box plot combines both drivers, compounds and stint lengths, the violin distributions are useful here. Hamilton has a strong concentration of laps around 1:20.8–1:21.4, plus another dense area near 1:22.7–1:23.2. Russell and Norris spend less time in the quickest band and their distributions are shifted upwards.

For Hamilton, this was a huge win. His first for Ferrari came after a long wait, and it arrived with a race that demanded commitment from both driver and pit wall. Ferrari was quicker than expected in Barcelona, took the VSC opportunity without hesitation and had the pace to make the aggressive strategy work. Hamilton finished it with an excellent final stint.

F1 MONACO GP 2026 | Antonelli in a race of his own, Ferrari left with questions

Antonelli had Monaco by the throat from the first stint. Pole, clean air, and a Mercedes that looked properly hooked up through the slow sections.

Before the neutralisations, the race was already stretched. At lap 56, the gapper had Hamilton around +30 s, Hadjar at +85–90 s, and several cars beyond +100 s. Russell had slipped into lapped-traffic territory despite running fourth earlier. The flag shows +6.2 to Hamilton and +23.3 to Hadjar; the race trace was harsher than the final gaps.

Antonelli’s fuel-corrected pace explains why. His first stint mostly sits between 1:13.0 and 1:14.5. Through the middle phase, he stays in the 1:14.5–1:15.2 window with limited scatter. The car rotated, put traction down and repeated the lap without a visible drop-off. Hamilton is the closest reference, often between 1:13.2 and 1:15.7. Hadjar is higher, with many laps around 1:15.5–1:16.6.

Leclerc did not have the same evening. Ferrari’s aggregate pace was good. The ranking plot puts the team median close to 1:17:0 s, with the central box around 1:16:6–1:17:4. Mercedes is similar on median, but broader because Russell stretches the upper tail. McLaren sits nearer 1:18:3 s; Red Bull is centred higher than Ferrari. That explains Ferrari P1 in the ranking plot. It does not change the individual picture: Antonelli was the reference. Leclerc’s DNF leaves the brake topic open. Brembo has asked for telemetry review before conclusions. Ferrari had pace; the result still feels incomplete

Wear: low. In the violin plot, Antonelli’s useful race mass is around 1:16:0–1:17:3. Hamilton is close but messier, near 1:16:5–1:17.6 with more scatter. Hadjar shifts upward, mainly in the 1:17:5–1:19:0 band.

Without the late interruptions, this was a one-stop Monaco. The open question moves to the next tracks: how much of Antonelli’s gap survives when tire management becomes less optional?

F1 CANADIAN GP 2026 | Antonelli controls, McLaren pays for the start call

Antonelli leaves Montreal with a fourth consecutive win and a championship lead that now looks like performance, not momentum. The Canadian GP gives a clear technical picture: Mercedes built the result early, Russell’s technical issue changed the internal race dynamic, and McLaren lost too much ground before its real pace could be judged.

Race pace
The first stint is where Mercedes looks strongest, from the race gapper and the fuel-corrected plot, Antonelli runs in the lower lap-time reference of the front group through the opening 25–30 laps. Early in the run, his fuel-corrected pace is roughly 0.3–0.5s/lap ahead of Hamilton and Verstappen. The ranking plot says the same: Mercedes has a median around 1:15.7, while Ferrari and Red Bull sit in the 1:16.1–1:16.2 range. Around four to five tenths on the central pace distribution. McLaren is around 1:16.8–1:17.0, affected by the opening laps.

Strategy
McLaren’s start on Intermediates is the key technical error of the race. Norris and Piastri immediately enter a different race sequence: tire phase mismatch, traffic, lost track position and negative gap evolution before the car can run in clean air.

Russel
Russell’s retirement on lap 30 changes the second half of the race. Until then, Mercedes had two cars on the front, and the most natural comparison was still internal. Once Russell stops, Antonelli has less reason to keep pushing. That shows after the stop: his gapper trend becomes much closer to Hamilton and Verstappen. More management than attack, with the margin already built.

Ferrari and Red Bull
Hamilton’s race is very solid, especially in the final stint on Mediums. His pace is consistent enough to make Ferrari a genuine second place car on the day, not just a car promoted by Russell’s retirement. Verstappen executes cleanly, but Red Bull looks closer to Ferrari than to Mercedes in race pace. Good enough for the podium fight. Not enough to pressure Antonelli.
Leclerc is less visible in the overall race shape: not slow in absolute terms, but never on a trajectory that could change the podium order.

Takeaway
Canada was a strong first phase followed by a managed second half and Antonelli controlled what he had built. Hamilton made Ferrari effective at the right moment whereas Verstappen maximised a Red Bull that did not quite have the pace to attack. McLaren compromised the race at the start with a tire call that the data did not support afterwards.

Seaside Racing is a self-funded open-knowledge format dedicated to on-track vehicle dynamics research. The track becomes an open-air laboratory where data collected in real operating conditions support academic research and give industrial partners a validation ground for models, products and new technologies.

Vehicle list:

• 124 Spider (MegaRide) 
• Tesla Model Y (University of Naples Federico II)  
• Alfa Giulia (University of Padova) 
• WRC-spec Rally car  
• Competition Kart 
• Sport bike 

For the experimental activities, the signature MegaRide 124 Spider will be joined by a wider testing fleet, including the Tesla Model Y, the Alfa Giulia from the University of Padova, a go-kart and a motorcycle, extending the programme across different vehicle architectures and testing scenarios. Activities will include tire characterization with different tire manufacturers, gravel rally tire testing in quarry conditions, particulate emissions measurements, ABS and ESC characterization, go-kart handling sensitivity and motorcycle acquisitions to support sensing system development. 

The main activities planned are: 

• Characterization of Apollo tires on the MegaRide 124 Spider through handling tests and objective manoeuvres, mainly aimed at studying tire wear behaviour;  
• Gravel rally tire characterization with the MegaRide 124 Spider, combining quarry-based gravel testing and on-track sessions;  
• Characterization of Pirelli tires on the Tesla vehicle using the TRICK methodology;  
• Data acquisition on the Tesla vehicle related to particulate emissions;  
• Dynamic characterization of ABS and ESC control systems on the Alfa Giulia;  
• Go-kart handling characterization with sensitivity analysis on different setup configurations;  
• Sport bike signal acquisition to characterize a rider alert system based on seat vibration. 

The “magic formula” is the Seaside Method, where equipment, expertise and experimental objectives are brought together in a shared testing programme. The data collected on track are shared with the participants who contributed to the activities, so that each run becomes part of a common technical base for analysis, validation and future development. 

A project that blends technical excellence, scientific curiosity and human collaboration, made possible by a growing network of people, companies and institutions.

F1 MIAMI GP 2026 | Antonelli wins, but McLaren looks like the car to beat

Antonelli won by just over 3s from Norris, Piastri half a minute back, Russell more than 40s behind, Verstappen fifth after a recovery drive. The result is clear enough, but the pace picture is a bit less comfortable. More, Leclerc’s P8 deserves a word before anything else: before the spin, the damage, and the penalty, he was in the podium conversation. Then, the final laps undid most of what had been a quietly strong race.

Strategy
Medium-Hard, no real surprises. Degradation was present but never took over: no dramatic collapse, no offset extreme enough to force a second stop into anyone’s plans. Thermal degradation, especially with high temperatures, had been a major concern in Florida in the past, but over the last two years, the phenomenon has been significantly reduced.

Pace picture
The team-level picture is fairly readable. McLaren ahead of Mercedes on median race pace, both in the low 1:33s. Ferrari roughly 0.4–0.6s/lap back, but their distribution varied significantly across different periods of the race. Red Bull is not far from Ferrari in some windows, but with less consistency. Mercedes won, but after the updates, McLaren looks like the stronger package. Enough, though, to say Norris was not just sitting there because of track position.

Race overview
That is what makes Antonelli’s win worth something. Fuel-corrected, the two were often within a couple of tenths through the long Hard stint. Norris had the car, possibly even a slight edge underneath, but never enough to force the race open. Antonelli gave him very little: no weak phase, no scrappy lap, no moment where an attack started to look realistic. Not domination. Just a very controlled win against what may have been the quicker car. Piastri says something similar about the McLaren, but his race was less tidy than Norris’: wider variance through the Medium phase, and the final gap reflects that. Russell is the uncomfortable internal comparison for Mercedes. Same car, different story. From mid-race onwards, he moved away from Antonelli’s pace quite visibly, and forty seconds is a gap that traffic and race phases alone do not explain. Ferrari split in two. Leclerc had podium-level pace for most of the afternoon, then the final laps erased it. Hamilton finished ahead on paper after the penalty, but his race was considerably more anonymous. Verstappen’s fifth is a decent save. The long Hard stint kept Red Bull in the points after the early mistake, but the pace does not put them anywhere near the Mercedes-McLaren level. More of a race patched together well than a real performance signal.

Takeaway
Miami leaves Mercedes in a slightly odd position: they won, but the fastest car on the day was probably Papaya. Antonelli made it count anyway, and that is exactly why this result matters.

At the SPS MegaRide will present two simulator demos built around the integration of real vehicles and physics-based models for durability and thermal management applications.

• On the HexaRev, MegaRide will showcase an activity based on the digital twin of its instrumented 124, which will also be on display at the stand. The activity will focus on durability and will link the simulator to the real vehicle setup, equipped with a dynamometric wheel, an S-Motion optical sensor, the WOM Testing Technologies device and accelerometers by Be CAE & Test.

• On the DiM400, MegaRide will run a Formula E demo driven by a professional driver. The activity will focus on the thermal balance between the braking system and the battery, using a Vi-CarRealTime vehicle model with brake thermal modelling and a Functional Mock-up Unit battery model with thermal behaviour. The driver will adjust the regeneration level through a dedicated control, directly affecting the temperature balance between battery and brakes. Higher regeneration increases battery temperature and lowers brake temperature, while lower regeneration shifts the thermal load back to the braking system.

The conference programme will also include two technical speeches developed with industrial partners.

The first “Multi-scale Wet Tire Dynamics: Modelling and Validation in a VI‑grade Simulator”, with Pirelli, will focus on multi-scale wet tire dynamics modelling and validation in a VI-grade simulator.

The second “Customer-oriented virtual tire wear assessment using multi-physical simulations.”, with Stellantis, will present a virtual tire wear assessment workflow based on MegaRide’s weaRIDE model and applied to more than 50,000 km of simulated driving.

Race result
Kimi Antonelli took his second straight win at Suzuka, beating Piastri by 13.7s and Leclerc by another 1.5s. The Safety Car helped, but it did not decide the race on its own. What decided it was the pace Mercedes and Antonelli unleashed after the restart.

Strategy
This was essentially a one-stop race built around Medium to Hard. Piastri, Leclerc, and Russell stopped before or around the Safety Car window, while Antonelli stayed out longer and converted that timing into track position. A fortunate break, yes, but one he still had to validate on pace.

Ranking plot
The ranking plot suggests a very tight lead group. Mercedes, McLaren, and Ferrari all sit around median race laps in the low 1:34s, with McLaren looking like the clearest second force this time. Then there is a step to the mid-1:35s, where Gasly, Verstappen, Lawson, and Ocon form a compact midfield cluster. Red Bull, once again, looked much closer to that fight than to the podium battle.

Violin plot
Antonelli stands out most in the second stint. His 2nd stint is full of laps in the 1:33s, and the distribution is remarkably dense: not only fast, but extremely repeatable. Piastri and Leclerc were strong too, but Antonelli looks like the real metronome of the race.

Fuel-corrected lap time
The fuel-corrected view reinforces the same picture. Antonelli was already recovering after a poor launch in stint one, but after the restart, he appeared roughly 0.4-0.6s per lap quicker than the main podium group for several laps. Once the pace converged, the gap was already built.

Race gapper
The gapper explains the outcome even better. After the Safety Car, Antonelli’s line has the strongest slope of the leaders: he simply drove away. Behind him, Piastri, Leclerc, and Russell show very similar gradients, while Norris and Hamilton were a step further back. Russell, for the second straight weekend, paid against his teammate in both qualifying and race trim.

Midfield
Behind the top four, Gasly and Verstappen were split by just 0.3s at the flag, with Lawson and Ocon only about a second behind. That says a lot about the current balance: the pack is compressed, and Verstappen is currently trapped in it.

Bigger picture
Now comes a one-month break after the cancellations of Bahrain and Saudi Arabia. Teams will use it to develop aggressively, but the FIA also has work to do. Too much of the racing still revolves around energy management, and that remains one of the main weaknesses of this rules cycle.

Takeaway
Yes, the Safety Car mattered. But the data points somewhere else: Antonelli had the fastest pace, the cleanest second stint, and the most convincing post-restart execution. He did not just inherit Suzuka. He earned it.