In the study of 30 people with a range of experience levels in handling a rifle, researchers at The Ohio State University found that a ballistic simulator captured data on the shooters’ accuracy, decision-making and reaction time – down to the millimeter in distance and millisecond in time – on a consistent basis. 

In addition to confirming that the simulator – called the VirTra V-100 – is a dependable research tool, the findings could lead to establishing the first-ever standardized performance scores for virtual reality ballistics training. 

“To our knowledge, we’re the first team to answer the question of whether the simulator could be converted to an assessment tool and if it’s credible to use it day-to-day,” said Alex Buga, first author of the study and a PhD student in kinesiology at Ohio State. 

“We’ve figured out how to export the data and interpret it. We’ve focused on the three big challenges of marksmanship, decision-making and reaction time to measure 21 relevant variables – allowing us to put a report in a user’s hand and say, ‘This is how accurate, precise, focused and fast you are.’” 

The study was published online June 6 in The Journal of Strength and Conditioning Research. 

U.S. military leaders and law enforcement agencies have shown an interest in increasing the use of virtual reality for performance assessment, said Buga and senior study author Jeff Volek, professor of human sciences at Ohio State. Earlier this year, an Ohio Attorney General Task Force on the Future of Police Training in Ohio recommended incorporating virtual reality technology into training protocols. 

Volek is the principal investigator on a $10 million U.S. Department of Defense grant focused on improving the health of military service members, veterans and the American public. As part of that initiative, the research team is investigating the extent to which nutritional ketosis reduces detrimental effects of sleep loss on cognitive and physical performance in ROTC cadets – including their shooting ability as measured by the VirTra simulator. Verifying the simulator’s results for research purposes triggered the attempt to extract and analyze its data.

“We were using it as an outcome variable for research, and we found that it has very good day-to-day reproducibility of performance, which is crucial for research,” Volek said. “You want a sensitive and reproducible outcome in your test where there’s not a lot of device or equipment variation.”

Because the lab also focuses on human performance in first responders, researchers’ conversations with military and law enforcement communities convinced Buga that data collected by the simulator could be more broadly useful. 

“I created a few programs that enabled us to calculate the shooting data and produce objective training measures,” he said. “This equipment is close to what the military and police use every day, so this has potential to be used as a screening tool across the country.” 

Users of the simulator operate the infrared-guided M4 rifle by shooting at a large screen onto which different digitally generated visuals are projected – no headset required. The rifle at Ohio State has been retrofitted to produce the same recoil as a police or military weapon. 

The study participants included civilians, police and SWAT officers, and ROTC cadets. Each was first familiarized in a single learning session with the simulator and then completed multiple rounds of three different tasks in each of three study performance sessions. 

In the first task, participants fired at the same target a total of 50 times to produce measures of shooting precision. The decision-making assessment involved shooting twice within two seconds at designated shapes and colors on a screen displaying multiple shape and color choices. In the reaction-time scenario, participants shot at a series of plates from left to right as rapidly as possible. 

Internal consistency ratings showed the simulator generated good to excellent test-retest agreement on the 21 variables measured.

All participants were well-rested and completed the study sessions at about the same time of day. Self-evaluations showed that participants’ overall confidence about their shooting performance increased from their first to final sessions. They also rated the simulator as a realistic and a low-stress shooting assessment tool. 

The low stress and well-rested conditions were important to establishing baseline performance measures, the researchers noted, which then would enable evaluating how injuries and other physical demands of first-responder professions affect shooting performance. 

“This simulator could be used to assess the effectiveness of specific training programs designed to improve shooting performance, or to evaluate marksmanship in response to various stressors encountered by the same law enforcement and military personnel,” Buga said. “These novel lines of evidence have enabled us to push the boundaries of tactical research and set the groundwork for using virtual reality in sophisticated training scenarios that support national defense goals.” 

Additional co-authors, all from Ohio State, included Drew Decker, Bradley Robinson, Christopher Crabtree, Justen Stoner, Lucas Arce, Xavier El-Shazly, Madison Kackley, Teryn Sapper, John Paul Anders and William Kraemer.

Called the Vehicle-in-Virtual-Environment (VVE) method, it allows the testing of driverless cars in a perfectly safe environment, said Bilin Aksun-Guvenc, co-author of the study and a professor of mechanical and aerospace engineering at Ohio State.

Imagine a driverless car is placed in the middle of an empty parking lot. Although it is driving, it isn’t reacting to the real world, but to input from the software, which tells the car what the road looks like, and what cars, pedestrians and hazards it is meeting along the way.

“With our software, we’re able to make the vehicle think that it’s driving on actual roads while actually operating on a large open, safe test area,” said Aksun-Guvenc. “This ability saves time, money, and there is no risk of fatal traffic accidents.”

The study, published recently in the journal Sensors, found that by immersing self-driving machines in a virtual environment, the technique can help the car learn to avoid possible car collisions, increase pedestrian safety, and react to rare or extreme traffic events. 

Although autonomous driving technologies have become a much more common sight on the road in the last few years, due to the sheer number of accidents these systems have caused, the way these technologies are tested deserves closer scrutiny, Aksun-Guvenc said.

“Our future depends on being able to trust any and all road vehicles with our safety, so all of our research concepts pertain to working towards that goal,” said Aksun-Guvenc, who is also co-director of Ohio State’s Automated Driving Lab, a research group originally formed in 2014 to advance  autonomous vehicle technologies.

Current approaches for demonstrating autonomous vehicle functions involve testing software and technology first in simulations and then on public roads. Yet this method essentially turns other road users into involuntary participants in these driving experiments, said Aksun-Guvenc, and such risks can make the entire development process costly, inefficient, and potentially unsafe for both drivers and pedestrians alike. 

To overcome the limitations of these faulty assessments, researchers in this study replaced the output of high-resolution sensors in a real vehicle with simulated data to connect its controls to a highly realistic 3D environment, much like giving the machine a VR headset or virtual reality glasses. After feeding the data to the autonomous driving system’s computers and syncing the car’s real motions with the simulations’, researchers were able to show that it behaves as if the virtual environment were its true surroundings in real time.  

But what makes their software especially powerful, said Levent Guvenc, co-author of the study and also co-director of the Automated Driving Lab, is the strength of how flexible their virtual environment can be. “When actual senses are replaced by virtual senses, the model can be easily changed to fit any kind of scenario,” said Guvenc.

Because the VVE method can be calibrated to maintain the properties of the real world while modeling rare events in the virtual environment, it could easily simulate extreme traffic scenarios, like someone jumping in front of a vehicle, to mundane ones like pedestrians waiting at a crosswalk, he said. 

Additionally, with the help of a communication app for vehicle-to-pedestrian connectivity, the software can use Bluetooth to communicate between a pedestrian with a mobile phone and a phone in the test vehicle. The researchers had a pedestrian actually dart quickly across a simulated road a safe distance from the test vehicle. But the Bluetooth signal told the car that the person was darting right in front of it.

“The beauty of the method is that road users can share the same environment at the same time without being in the same location at all,” said Guvenc. And although generating these super-realistic environments can take time, he said the technological challenge of syncing different environments to use in real-time simulations is one challenge their team has solved. 

The team has also filed a patent for the technology. In the future, Guvenc said he’d also like to see it be integrated into traffic guidelines made by groups such as The National Highway Traffic Safety Administration. 

“We could see this technology becoming a staple in the industry in the next five or 10 years,” said Guvenc. “That’s why we’re focusing on building more applications for it.” 

Other Ohio State co-authors were Xincheng Cao, Haochong Chen and Sukru Yaren Gelbal.