The VR truck: There it isn’t!

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Virtual reality allows GM engineers to evaluate designs, check clearances under load, assess maintenance access and much more.

So, you’re sitting in this truck cab. You lean forward and look down over the hood. You stick your head out the window and look at the sides of the truck. You grab the steering wheel, but you’re grabbing air. This truck does not exist.

It’s part of General Motors Corp.’s Virtual Reality Center in Pontiac, Mich., and it’s how GM is doing a lot of commercial vehicle development these days.

GM used proprietary software known as Visualeyes, to project 2-D or 3-D math data files onto its “Powerwall.” This visualization software is used along with texture-mapping enhancements to make the math data files appear realistic.

For example, the truck’s frame rails are represented as painted metal, while the truck’s instrument panel looks like the vinyl counterpart in the production model, complete with electronic gauges and toggle switches. The Powerwall used to project the truck’s image is 5/8-inch thick plate glass, 10 feet tall and 24 feet wide – large enough to view most GM products at full-size.

GM also uses the University of Illinois at Chicago’s Cave Automatic Virtual Environment (CAVE), a full-immersion virtual experience, projecting four distinct views simultaneously. It’s used to evaluate the layout of the vehicle’s interior, as well as the ability to service the vehicle.

Math-based tools are employed in all aspects of GM’s medium-duty truck development, resulting in what the company insists are better products with shorter development cycles.

Not long ago, GM’s vehicle development process was 40 months long, according to Richard H. Gray, executive director, engineering process and math strategy. Today, some GM programs are fewer than 18 months long, with math being a key enabler for reducing development cycles.

“It gives us the capability of simultaneous design and build verification,” adds vehicle chief engineer Steve Matsil, “along with rapid, inexpensive issues resolution.”

Thanks to math-based tools, GM expects to: reduce the number of physical validation processes by 30 percent during development, and by 10 percent during validation; make 50 percent fewer engineering changes; reduce lead time by up to 50 percent for production tooling; and reduce overall time to market for new products.