Like in a fever-dream, race tracks, canyon roads, and highways were all empty. People—including driving enthusiasts and professional racers—stayed home in droves in response to the COVID-19 global pandemic. Engineers behind the tech curtain refined and redefined dynamic driving simulations. The hardware and software to simulate racing grew exponentially. Professional drivers streamed their simulated race series. Formula 1 launched the "Virtual Grand Prix" with name F1 drivers racing against competitors who were professionals from the e-sports arena. Competitive simulation boomed when everything else in the world seemed to have shut down.

The world is open again, and race tracks buzz with the resonance of race cars. Post-COVID, many enthusiasts and hobbyists dropped out of the race simulation world. Yet sim racing survived its volatile COVID fad status. It's thriving and more relevant than ever.

The Real Deal

Wani Finkbohner of RacingFuel Simulators AG in Horgen, Switzerland, described the gamut of responses he hears from stakeholders involved in the simulation industry. "Sometimes sim racers tell me that our simulator doesn't feel real. Sometimes real race drivers tell me that it's useless. But they keep coming back, and at the end it becomes indispensable for their training."

The "real deal" has been the focus since the start of sim racing. However, the "hardware was far behind software development," said Finkbohner.

"Our motivation was to build hardware as close as possible to a real race car—merge the two worlds and make it a beautiful and compact training machine," he said. "Our customers are mostly drivers and teams, but also institutions like universities. We are very obsessed with getting close to the 'real deal.'"

Dynisma in Bristol, United Kingdom, consists of a team of talented engineers who created an incredibly accurate, data-driven simulator specifically tailored toward the likes of F1.

"It's all about real correlation between what you see and feel in the simulator with what you get from the real car," said Simon Holloway. He stressed the importance of what the driver feels while using the simulated vehicle model, expressing how vital it is to have a one-to-one correlation when testing. "It's not just the vehicle model and the behavior of the vehicle itself. It's the tire model, the powertrain model, the aero model, and what you're driving on.

"What the physical tire is running over is obviously very important as well," he added. "We use LiDAR [Light Detection and Ranging] scan data for the surface the vehicle is actually driving on so that we can get really good correlation between the tarmac, the tire behavior, and the vehicle behavior, which then all leads to the performance."

The accuracy derives from telemetric data collected from the real race car. Engineers create a digital twin—a virtual replica of real-life conditions a driver sees, feels, and experiences on track, uploaded into the simulation. That includes factors like tire degradation, aero changes, weather conditions, "even down to the vibration from the powertrain," said Holloway.

Capturing the full scope of data from the race car, track, and weather conditions enables the engineers to create the correlating motion that mimics what drivers experience in-car. This increases driver immersion, which Holloway described as "closing the loop between the virtual model and the real driver-in-the-loop behavior."

Outputs from the simulation's hardware, like motion, steering, throttle, and braking, are read by software that leverages and interprets extrapolated telemetric data and issues commands based on inputs made by the driver. The software environment (e.g., iRacing) is the physics engine that generates what the telemetric data stream needs to interpret.

iRacing, for example, generates physics at 60Hz. Dynisma's sim reproduces motion cues up to 100Hz, which means it's interpreting driver inputs, issuing the proper command outputs, and updating up to 100 times per second. The ability to process a high bandwidth of information ensures Dynisma's simulator is never the bottleneck.

Driver-in-the-loop behavior is the human element part of the broader overall simulation feedback that includes software-in-the-loop and hardware-in-the-loop. Combining all three closes that feedback loop.

As alluded to by Holloway, Dynisma's sim is largely an engineer's tool to help with driver performance. Information will "communicate constantly" with data transferring between "the sim and the pit." The data is analyzed and checked in the sim, providing track conditions, weather conditions, setup ideas, and other minute changes. "Repainted curbs, or a new curb that wasn't there before," is information that can affect the driver and must be updated in the simulator, Holloway said.

A fascinating aspect of simulation is the application of being a race driving coach. E-sports drivers who compete on a professional level in sim racing are just as effective as a driving coach as a former racer, according to Marc-André Ladouceur of Advanced SimRacing in Montreal, Quebec, Canada. "We do have some very successful coaches who are e-sports champions who have never raced. They're telling Porsche Cup drivers how to drive, but they had never stepped foot on a race track."

Technology-Driven Accuracy

From floor-mounted designs to Hexapod Stewart platforms, cockpit designs serve as the basis for how the driver experiences immersion and perceives speed, which are necessary ingredients to accurately simulate racing.

"We've been working with iRacing since 2008," stated Sean Patrick MacDonald of SimCraft, Kennesaw, Georgia. He has been in the simulation space for 20 years. His initial introduction to simulation was at an early age when his father built a personal flight simulator. "In 1981, dad brought home a TRS-80, and all of a sudden it was like, 'What is this magical device?'" he recalled.

MacDonald shifted his attention to the past and studied the principles of rigid-body dynamics. He credited Leonard Euler, the discoverer of rigid-body dynamics in the 18th century.

Rigid-body dynamics is a branch of physics that studies the concepts of kinematics, kinetics, center of mass, and moments of inertia. By studying these concepts, MacDonald recognized that these principles explain how external forces influence the chassis of a race car—a perfect fit to simulate the physics a driver feels, especially when racing.

Human perception of motion was the target that MacDonald aimed to understand and emulate with his company's cockpit. "The way we perceive motion—proprioception—is inside the inner ear [through the vestibular system] and skin. Those are the two main factors that actually allow us to sense movement in motion.

"Your brain processes your proprioceptive information. It's a human sense," he added. "If your brain believes it, your brain is not going to lie about it. It's going to show that it believes it."

Working with Dr. David Ferguson from Michigan State University, they conducted an experiment consisting of three amateur drivers piloting GT3 cars at Mid-Ohio Sports Car Course in Lexington, Ohio, then followed up with testing on a simulation rig.

Using SimCraft's rigid-body dynamics cockpit, an EEG (electroencephalogram)—a medical test that measures electrical activity of the brain—illustrated "no noticeable loss of focus or attention over time," said MacDonald. These results were published in an academic white paper (non-peer reviewed) in which MacDonald surmised, "The brain never lies."

Proficient software coding and rigid-body dynamics activate the center mass physics experienced in the cockpit. Theoretically, it deceives the driver's brain as well as the driver's proprioceptor senses and vestibular system.

MacDonald addressed software programming. "I essentially take the data—I only make a copy of it when I absolutely have to—and I found I could pass it down so fast through this algorithm that it would turn into a motion command," he said. "The time it took from getting a raw piece of iRacing physics to issuing a motion command through the series of algorithms was less than one millisecond."

Physical aspects create latency downstream from the code. "These are 'off the shelf' motion controllers, actuator systems. But being able to actually sense the movement in the cockpit physically with a sensor that's tied back into our software to determine the delta between sending the command to the motion control system, I'm missing a 10-millisecond window, which in latency equation is a huge amount of time," MacDonald said.

Second, the hardware architecture design leverages rigid-body dynamic principles. Utilizing the six degrees of freedom—roll, pitch, yaw, sway, heave, and surge—motion physics addresses behaviors that occur when the vehicle chassis experiences forces enacted upon it.

MacDonald demonstrated how SimCraft's cockpit functions. He held his cellphone with his two index fingers, placed strategically on the sides (often where volume or power buttons tend to be located), demonstrating the location of his phone's center mass.

SimCraft's center-aligned motion system "builds its chassis and actuator systems around physical gimbals that pivot the entire cockpit—driver, controls, seat, display, and all—around a fixed center of mass. Every axis is physically aligned with the appropriate vector.

"By doing this, SimCraft replicates not just the sensation of motion, but the origin of motion, ensuring that motion cueing and body response are aligned. This eliminates the primary flaw in seat-shakers, G-seats, four-post, and Hexapod Stewart platforms: They don't rotate or move from the same place that real forces on a vehicle do," according to product details listed on SimCraft's website.

MacDonald and his team designed each aspect (hardware, middleware, and software) as a theoretical solution to model how the brain recognizes and perceives reality.

While the team at SimCraft believes in the effectiveness of a rigid-body approach, Dynisma opted for a motion-generated platform approach derived from an engineer-centric design and offered a product that simulates the exact feel and feedback a driver experiences based on live telemetric data.

"With the motion technology, we've generated low latency and high bandwidth," said Holloway. "Traditional simulators have a lot of latency in them at a pretty low bandwidth. Typically, it would be something between 40 and 50 milliseconds of latency."

Holloway explained that the human aspect of the driver-in-the-loop feedback reacts at "around 100 milliseconds," creating a supplemental latency of 50 milliseconds on the vehicle model. The additional dormancy causes driver deficiency, so they can't "catch the slide."

The further downstream the programming gets from the source of driver input, the higher the latency increases. "Often, you'll get drivers complaining that they can't drive the simulator because it keeps spinning, and they can't catch it," said Holloway. "This is due to the latency that's involved. We brought that latency down to 3 to 5 milliseconds [end-to-end]—which means that it reacts just like a real car does."

Dynisma employs a "direct drive" system that "reduces friction to imperceptible levels, eliminating backlash and inertia, delivering an immediate and dynamic sensory experience," according to company sources. Utilizing a direct-drive system, the actuators are comprised of rocker-pushrod motors attached directly to the platform. This setup assists in the six degrees of freedom, creating a near instantaneous outcome when the driver makes an input. The less mechanical filtering that occurs, the less latency the driver will experience. Rather, the information and immersion of the driver's vestibular system increases, enriching facets like the perception of speed and motion associated with realistic driver feel.

Barriers In Simulation

Despite simulation racing's continual growth in innovation and users, axiomatic factors are holding back deep simulation from occurring. Gravity is the major barrier that stunts simulators' immersion across the board, Finkbohner said.

"The lack of G-forces and the poor integration of augmented/virtual reality cause motion sickness. It occurs when there is a mismatch between the visual signals sent to the brain and the physical sensations felt by the body, leading to symptoms like dizziness, nausea, and discomfort," he explained.

When the driver's proprioception and vestibular system don't align with the visual feedback the brain is deciphering, especially when witnessing a 3D space from a VR headset, "the brain expects certain physical movements," like G-forces, to be felt by the body, Finkbohner said.

MacDonald said the team at SimCraft doesn't try to simulate sustained G-force, "because it's a fool's errand." The forces of gravity, when pushed beyond the resting gravity humans experience daily, are incredibly tiring for the driver.

"They're getting some exercise of their arms and their legs in the sim. But trying to recreate sustained G-force without actual gravity—unless you're moving around a warehouse with a sim—you're moving great lengths to try and create sustained G-force," he said.

Rupert Scheucher and Guillermo Pezzetto of AVL Racetech in Graz, Austria, cited several "persistent barriers" in the sim space, including tire modeling, complex aerodynamics, suspension compliances, high-frequency response, and model complexity versus real-time performance. They noted these limitations "require ongoing research and development.

"Accurately simulating the complex, non-linear behavior of a tire, particularly at the limit of adhesion, remains a significant challenge," they explained. "Capturing the intricate and often turbulent airflow around a racing car with complete fidelity is a challenge, taking into consideration the influence of the tires, flexible aerodynamics, interaction with other vehicles, etc."

Scheucher and Pezzetto listed off-road environments as a "notable area of ongoing development" in which AVL is "making progress." The progress they look to improve is quite a challenge to simulate. Road race courses with a tarmac track surface routinely evolve throughout a race day. Weather variability will affect factors like the limit of adhesion for tire traction. Track temperatures change by the hour; so too does the ambient air density or density of air in context to altitude. These aspects create barriers even for simulation.

Holloway at Dynisma detailed weather in simulation as another variable when testing. "The weather's probably warmed up a little bit, so the track conditions are different. So, it's very difficult to objectively test what you've changed and definitely say, 'that's better, or this is better,' because the conditions that you're driving in are always changing."

 

The Next Frontier

AVL is broadening the scope of simulation capabilities by developing new "soft-soil tire models." Scheucher and Pezzetto said they're developing a "specialized application" for these conditions, one that can be used for a lunar rover. Addressing other areas of motorsports is the next natural step in race simulation. They stated Functional Mock-up Unit (FMU) and Applied Artificial Intelligence as areas "currently commanding significant attention."

"Functional Mock-up Unit facilitates the straightforward integration of third parties and/or user-developed models into our simulation framework. The application of recent advances in AI, when combined with a robust, first-principles understanding of the physics involved, is yielding unique solutions for numerous complex applications. This includes the modeling of intricate components such as internal combustion performance, braking systems, and aerodynamics.

"Furthermore, AI is driving the development of new optimization algorithms capable of handling multiple input variables to target a suite of output KPIs [key-point indicators], a task that was previously computationally prohibitive," stated sources at AVL.

Surpassing the evolution of simulation is an immediate frontier that experts in the field are calling for: regulation.

"I think misinformation is a big challenge in the industry. There's no authority that says, 'This is a great sim I have,'" said Ladouceur of Advanced SimRacing. "We'll see something cool on the internet. We'll start speaking to someone, and we'll end up buying something that could have been a lot better for $10,000 cheaper. That is a big challenge in the industry today because there's no standard."

 Ladouceur proposed a likely future that may include global regulations on simulation rigs. "I think an international body like the FIA will start giving parameters for simulation training. I see a future where there's an FIA homologation for certified training equipment."

Despite the horizon of simulation possibilities yet to be discovered or studied, MacDonald looks to continually close the gap with reality. While Ferguson rated the Michigan State sim at 90%, MacDonald shared his goals. "I want a 91%. I want to know how to get to 92%. I want to know how to get up to 99%. Is 100% achievable? Probably not. But if the body's responding, and you're able to measure the body's response to a sim, and you're currently rated at a 90%—I want to know how to get higher."

 

Sources

Advanced SimRacing
advancedsimracing.com

AVL Racetech
avlracetech.com

Dynisma Ltd.
dynisma.com

RacingFuel Simulators AG
racingfuel-simulators.com/en

SimCraft
simcraft.com

 

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