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Generation of stochastic mobility maps for large-scale route planning of ground vehicles: A case study

Ramon Gonzalez, Paramsothy Jayakumar, Karl Iagnemma   
Journal of Terramechanics, Volume 69, February 2017, Pages 1-11, ISSN 0022-4898,  
This paper describes a simple and efficient methodology to generate a mobility map accounting for two sources of uncertainty, namely measurement errors (RMSE of a Digital Elevation Model) and interpolation error (kriging method). The proposed methodology means a general-purpose solution since it works with standard and publicly-available Digital Elevation Models (DEMs). The different regions in the map are classified according to the geometry of the surface (i.e. slope) and the soil type. A real USGS DEM demonstrates the suitability of the proposed methodology: (1) interpolation of a 26 × 40 -km2 DEM to a finer resolution (30-m to 20-m); (2) analysis of the number of random realizations to account for the variability of the data; (3) efficient computation time (4-million-point DEM requires less than 30 min to complete the whole process); (4) route planning using the stochastic mobility map (constraints in slope and soil properties). UNCLASSIFIED: Distribution Statement A. Approved for public release; distribution is unlimited. #27681    
Keywords: Stochastic conditional simulation; Geographical Information System (GIS); Next-Generation NATO Reference Mobility Model (NG-NRMM); Digital Elevation Model (DEM); Soil moisture