Real time rut profile measurement in varying terrain types using digital image correlation. (April 2019)

• Record Type: Journal Article
• Authors: Botha, Theunis; Johnson, Devin; Els, Schalk; Shoop, Sally
• Is Part Of: Journal of terramechanics. Volume 82(2019)
• Page Start: 53
• Page End: 61
• Publication Date: 2019-04
• Subjects: Real time -- Rut depth -- Stereo -- Terrain measurement; Trafficability -- Periodicals; Praticabilité (Routes) -- Périodiques; Trafficability; Periodicals; 629.222
• DOI: 10.1016/j.jterra.2018.12.003
• Languages: English
• ISSNs: 0022-4898

Abstract

Highlights: A compromise between accuracy of point cloud and computation efficiency exist. Stereo system works on various terrains from snow, mud to concrete roads. Rut depth can be automatically be measured from point cloud. Abstract: An important parameter in terramechanics is the rut depth produced when a vehicle traverses deformable soil. The rut depth provides a measure of vehicle tractability as well as the impact on the environment. Rut depth is not uniform on natural terrain and typically only a few manual points are measured. Synchronizing rut depth with other measurements is also problematic. This paper investigates the feasibility of using cameras to measure 3D terrain profiles from which a single rut depth measurement is obtained. Tests were performed on different vehicles, for various dynamic vehicle manoeuvres, over varying terrains including sand, mud, grassland, snow and ice. Results were validated using the traditional stick ruler method. Measurement frequencies of 58 Hz were obtained using affordable commercially off the shelf computational hardware and dedicated software. Determining whether a vehicle can traverse a terrain can significantly improve the vehicle mobility. Therefore, real time measurements of rut depth can be used to determine the mobility of vehicles in off-road conditions that can change rapidly due to environmental conditions e.g. rain or snow. The techniques described can assist in gathering terrain and vehicle mobility data that can be used directly to assist the driver in making safety related decisions.