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The National Highway Traffic Safety Administration's Vehicle Research and Test Center (VRTC) plans to evolve the state-of-the-art of steering system modeling for driving simulators with the ultimate goal being the development of a high fidelity steering feel model for the National Advanced Driving Simulator (NADS). The VRTC plans on developing reliable research tools that can be used to determine the necessary features for a steering model that will provide good objective and subjective steering feel. This paper reviews past and continuing work conducted at the VRTC and provides a plan for future work that will achieve this goal.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.