Standing on the beach watching clouds scuttle across a post-storm sky, I asked the lifeguard standing next to me what he did on his days off. “Watch the weather, ” he said. “Can’t help it.” Like a bus driver rides the bus and a magazine writer gobbles up other magazines. Which was how Idiscovered a company in Canada that’s developing a new version of the automobile simulator.
Vehicle simulators aren’t new; they’re in widespread use for teaching potential license holders how to become proficient on everything from passenger cars to trucks to well, buses. So widespread that about four years ago, I was asked to take a look at the state of the art of simulators in the heavy equipment industry. With a sense of all-knowingness, I concluded that simulator-based training was “making tentative inroads” in construction, “propelled by the need for skilled operators and increased productivity, high operating costs, and potentially looming safety regulations.”
I had evidence. Major manufacturers—Caterpillar, John Deere, Volvo—were making simulators available and only too happy to talk about their benefits. Simulators give operators the opportunity to practice maneuvers until they have them fully mastered, and in a controlled, safe environment, which decreases “operator anxiety.” Simulators are efficient—multiple operators can be trained simultaneously on multiple machines; and more cost-effective, saving on owning, maintenance, and operating costs while freeing up the real machines for the job site. Industry associations, technical schools, junior colleges, and large construction companies, tended to give them a thumbs up. A professor at technical school in Pennsylvania insisted that putting students in a simulator before they take a seat on a live machine makes them feel more comfortable, which makes them feel more self confident, which gets them digging efficiently a lot faster.
The then-executive director of the Operating Engineers Training Institute of Ontario wanted me to know that it takes a minimum of 180–200 hours of seat time before an apprentice can go onto a job site and operate a machine safely and efficiently. Overall, the logic seemed to be, “Give a new operator enough time in a simulator and when he emerges, he’ll be a much better operator.” That is, any and all new operators regardless of prior training or experience, if any.
A man named John Hildreth at the University of North Carolina at Charlotte, begged to differ. There are caveats. The first one seemed obvious: “The more realistic a simulator, the more an operator tends to operate it like he would a real machine.” Which accounts for the introduction of motion platforms that suggest the feel of executing an earthmoving procedure when the machine is underway. Hildreth was also concerned that a simulator’s effectiveness is “highly dependent” on the scenarios built into it. Most importantly, he worried that the construction industry wasn’t clear about what it wanted from simulator-based training. “Are we trying to get the student proficient with the machine or with the procedure?” Are we trying to teach operators to safely operate a specific machine or to efficiently and effectively produce work? (Which brings up the question of according to whose criteria?)
Most simulators, from cars to cranes, are set up with a control station facing a 180-degree viewing area (a set of two to three computer monitors), often with two smaller side windows meant to mimic side-view mirrors and occasionally a rear screen to show operators what’s going on behind them. The software that drives the images exposes the user of the platform to the problems, circumstances, or jobs they’re likely to encounter in the real world and offers opportunities to practice meeting the tests the simulator throws at them.
The problem is that the set-up is phony and as such, requires some suspension of disbelief on the part of the platform operator: I am not sitting in this office chair looking back and forth at two computer screens; I’m out in a huge empty field in South Dakota excavating a pad for a new Walmart.Additionally, the visuals can often be cartoony, and mobility platforms aside, real-world effects are often limited.
In contrast, the new DriverLab automobile simulator being developed by the Toronto Rehabilitation Institute uses an actual vehicle—an Audi A3 (engine removed) mounted on a turntable that can swivel a full 360 degrees. Instead of a couple of screens in front of you and maybe a screen at the back, the A3 is surrounded by seamless gray, so that the computer-based images drop the user effortlessly into a discrete, self-contained environment. The goal is to make the driver’s experience behind the wheel seem as real as possible, resulting in a more accurate, individualized evaluation of his or her performance.
Lights shine dazzlingly like they do when a set of high beams is coming at you in the rain; bright LEDs are precisely synchronized to the images of the cars they’re supposed to be attached to, adjusted for size, width, and glare as they approach. To simulate the sun (as for example, when you crest a hill, and the setting sun is at just the angle to block your view), the system uses a special lamp of appropriate color balance and brightness on a robotic arm. The unit is even equipped with a specially designed nozzle to spray varying kinds of rain on the A3’s windscreen. Activators simulate how the Audi handles under rapid acceleration, under different driving conditions (snow, for example, which produces changes in handling, braking, and visibility the driver has to reckon with), and in different driving environments—bumpy terrain, heavy-trafficked city streets, a dark mountain road at night. And while all this is happening, the simulator’s cameras are continuously tracking where a driver’s hands, feet, and eyes are at any given time, while a voice recorder records what he says in the course of putting the A3 through its paces.
Overkill, you say? Perhaps for the average driver. But DriverLab is being developed for a specialized segment of the driving public—older drivers who are in danger of losing their licenses. Currently the system that decides yeah or nay about allowing gray hairs on the road is arbitrary. Either you’re capable and can drive or you aren’t and you can’t—ever again, under any circumstances, a decision that’s based on a range of slippery variables from medical conditions and prescription drugs to predictable hallmarks of aging such as less acute eyesight and slowing reflexes. The assumption being that if your reaction time isn’t up to freeway driving, you’ll also be a menace driving down to the mini mart to get a quart of milk.
Designed to test how good individual older driver license holders perform in a variety of circumstances, the DriverLab goal is that regulatory agencies could use its evaluations to issue licenses that reflect individual skills, proficiencies, and limitations, keeping drivers off the freeway who aren’t suited for that kind of driving while making it possible for them to drive across town to visit the grandchildren.
We learn via an interrelated system of three different modes–cognitive, affective, and psychomotor. Cognitive learning refers to the straightforward acquisition of knowledge, followed by comprehension (I get it), application (I can use it) and the more high level skills of analysis and evaluation (I’ll do it because I have to in order to accomplish x, w, or z.) Affective learning objectives are a function of individual interests, attitudes, values, and emotional biases, which affect the degree that a person is aware of or sensitive to the existence of certain ideas or information and feels OK to follow, commend, or recommend said material to others.
It’s the third area of learning, psychomotor, that can be the sticky wicket. The first time I heard this term I was sitting in a dental chair in a university clinic. The faculty member who was supervising the dental student standing over me with drill in hand, explained that people like me were necessary so that people like this student could test and perfect their psychomotor skills—combining what they had learned about doing a procedure with the physical skills to accomplish it. Or as the experts put it, psychomotor refers to the “physical encoding of information with movement and/or with activities where muscles are used to express or interpret information or concepts.” Which, it seems to me, to be where simulators shine. We don’t want to know, for example, that the driver in the DriverLab knows he’s supposed to stop at a stop sign, but that he sees the sign and his reflexes are good enough that he stops.
When I wrote that article about simulators four years ago, I unwittingly glossed over a number of important factors. Before they hit the simulators, for example, future heavy equipment operators should be thoroughly up to speed first, on the basics of how that particular piece of heavy equipment operates, second, on industry-sanctioned procedures for completing the particular task being asked of them and third, the industry’s standards for achieving it.
Hildreth’s ideal would be teaching simulators that are customized to incorporate an organization’s individualized way of doing things. Aligned with this recommendation, he argues for a way to “play” with various factors that can affect productivity and demonstrate to operators the effects of their responses (much in the same fashion as DriverLab tests older drivers’ proficiency in grossly antithetical circumstances)—in the dirtmover’s case, changes in soil type changes, unexpected precipitation, or light changes.
Four years ago, Arnold Free, COO at Montreal-based CM Labs Simulations Inc., would have agreed—given that simulators offer the opportunity to capture objective details about individual student performance, Free maintained that learning retention is higher with variety of scenarios that feature unanticipated events, which leads to more effective learning and a wider operator skill set. “This kind of training goes beyond learning the basics of controls. It’s about how to use that machine in typical work environments.”
Hildreth takes it farther. “What if you have the ability to program a simulator to build a virtual job site where you could run through an entire operation and improve your opportunity for success the first time around?”
The people at the Toronto Rehabilitation Institute realize that it will take a while for their mature driver simulator to catch on and even more time for motor vehicle departments to complete the delicate task of developing varyingly restrictive licenses. In the meantime, they figure families of mature drivers will welcome the opportunity to validate to their relatives that it’s time to hang up the keys. But they neglect the drivers themselves, who might be all too happy to pay to practice driving under a variety of potential scary driving scenarios and unfamiliar conditions. Score one for the old folks—virtual reality here we come.
