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Review of current developments in terrain characterization and modeling

As computational power builds to meet the needs of ground vehicle designers, the focus has begun to shift from laboratory testing of prototype parts and subsystems to computational simulations of the vehicle. In the automotive and defense industries, large strides have been made in simulating full vehicle responses, such as durability. These simulations are most meaningful when excited by proper mathematical models that accurately characterize the terrain. It is important to understand the roughness indices that are used to judge the terrain profiles. The state-of-the-art in terrain characterization and modeling is reviewed in this work for models including Power Spectral Density (PSD), Markov Chains, Autoregressive Integrated Moving Average (ARIMA), Parametric Road Spectrum (PRS), Shifted Spatial Range Spectrum (SSR), Direct Spectrum Estimation (DSE) and Transformed Direct Spectrum Estimation (TrDSE). The applicability, limitations, and benefits of these models are assessed based on their effectiveness in capturing the stochastic nature of the terrain being characterized. A discussion of terrain characterization usage to advance reliability testing concludes this work as an example of the applicability of this technology.