2017
DOI: 10.1155/2017/3982753
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A Fuzzy Simulation Model for Military Vehicle Mobility Assessment

Abstract: There has been increasing interest in improving the mobility of ground vehicles. The interest is greater in predicting the mobility for military vehicles. In this paper, authors review various definitions of mobility. Based on this review, a new definition of mobility called fuzzy mobility is given. An algorithm for fuzzy mobility assessment is described with the help of fuzzy rules. The simulation is carried out and its implementation, testing, and validation strategies are discussed.

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Cited by 4 publications
(3 citation statements)
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“…Similarly, terrain height is defined as high if in the range of 0-300 m, medium 200-600 m, and low if greater than 500 m [32]. Under off-road traversing conditions, the vehicle speed is defined as low, if in the range of 0-15 km/h, medium 10-30 km/h, and high 20-40 km/h [28]. By comparing the calculated VCI 1 and VCI 50 to the CI, CI is defined as low if in the range of 0-500 kN/m 2 , medium 400-700 kN/m 2 , and high if greater than 700 kN/m 2 (See Appendix B for details of the specific rules setting).…”
Section: Mobility Prediction Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Similarly, terrain height is defined as high if in the range of 0-300 m, medium 200-600 m, and low if greater than 500 m [32]. Under off-road traversing conditions, the vehicle speed is defined as low, if in the range of 0-15 km/h, medium 10-30 km/h, and high 20-40 km/h [28]. By comparing the calculated VCI 1 and VCI 50 to the CI, CI is defined as low if in the range of 0-500 kN/m 2 , medium 400-700 kN/m 2 , and high if greater than 700 kN/m 2 (See Appendix B for details of the specific rules setting).…”
Section: Mobility Prediction Resultsmentioning
confidence: 99%
“…Fuzzy logic is a technique which uses the degree of truth instead of discrete values such as 0 or 1; it also uses "linguistic" variables such as "low", "medium", and "high", as well as numerical variables for the calculations. The relationship between inputs and outputs is given by some simple statements rather than complex mathematical equations [28]. Let A be a fuzzy subset.…”
Section: Mobility Cost Quantificationmentioning
confidence: 99%
“…The analysis, data quality control, and modelling of terrain trafficability factors based on probabilistic and statistical theories using the Bayesian theorem were applied in the work of Laskey et al (2010). Modelling using fuzzy logic in models and analysis of terrain trafficability was applied by Atkinson et al (2005), George et al (2017), Hofmann et al (20132015), Slocum (2003), Talhofer et al (2015) in raster analysis, where simple Boolean logic 4 was upgraded using the set theory. Gustafsson and Hägerstrand (2005) applied a special approach 4 Boolean algebra is a part of mathematical logic where the values of the variables are defined by logical operators "true" and "false", which are usually indicated by values 1 and 0.…”
Section: Modelling/structuring Of Physical-geographic Factors Of Terrmentioning
confidence: 99%