Paper
10 May 2007 Developing Markov chain models for road surface simulation
Author Affiliations +
Abstract
Chassis loads and vehicle handling are primarily impacted by the road surface over which a vehicle is traversing. By accurately measuring the geometries of road surfaces, one can generate computer models of these surfaces that will allow more accurate predictions of the loads introduced to various vehicle components. However, the logistics and computational power necessary to handle such large data files makes this problem a difficult one to resolve, especially when vehicle design deadlines are impending. This work aims to improve this process by developing Markov Chain models by which all relevant characteristics of road surface geometries will be represented in the model. This will reduce the logistical difficulties that are presented when attempting to collect data and run a simulation using large data sets of individual roads. Models will be generated primarily from measured road profiles of highways in the United States. Any synthetic road realized from a particular model is representative of all profiles in the set from which the model was derived. Realizations of any length can then be generated allowing efficient simulation and timely information about chassis loads that can be used to make better informed design decisions, more quickly.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wescott B. Israel and John B. Ferris "Developing Markov chain models for road surface simulation", Proc. SPIE 6564, Modeling and Simulation for Military Operations II, 65640J (10 May 2007); https://doi.org/10.1117/12.720066
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Roads

Data modeling

3D modeling

Computer simulations

Stochastic processes

Statistical modeling

Analytical research

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