Interpolation methods for high-fidelity three-dimensional terrain surfaces

Detweiler, Zachary R.; Ferris, Joseph E.

doi:10.1016/j.jterra.2010.01.002

Cited by 24 publications

(16 citation statements)

References 11 publications

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“…As a result, PSD of road roughness while steering should also satisfy its statistical features. Based on the work presented in [14], a triangular mesh method is used for analysis.…”

Section: Steering Working Conditionmentioning

confidence: 99%

“…When radius R and sampling interval ∆l are known, coordinates of sampling point E can be located in the plane of triangle ACD. Then, road roughness at point E can be obtained by computing road roughness at points A, B, D. Following the procedure discussed above, road roughness of other points can be obtained as discussed in [14] and can be validated. Movement trace of the vehicle is typically not straight under various steering conditions.…”

Section: Steering Working Conditionmentioning

confidence: 99%

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Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Wang

Dong

et al. 2017

Applied Sciences

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Considering the importance of increasing driving safety, the study of safety is a popular and critical topic of research in the vehicle industry. Vehicle roll behavior with sudden steering input is a main source of untripped rollover. However, previous research has seldom considered road excitation and its coupled effect on vehicle lateral response when focusing on lateral and vertical dynamics. To address this issue, a novel method was used to evaluate effects of varying road level and steering wheel input on vehicle roll behavior. Then, a 9 degree of freedom (9-DOF) full-car roll nonlinear model including vertical and lateral dynamics was developed to study vehicle roll dynamics with or without of road excitation. Based on a 6-DOF half-car roll model and 9-DOF full-car nonlinear model, relationship between three-dimensional (3-D) road excitation and various steering wheel inputs on vehicle roll performance was studied. Finally, an E-Class (SUV) level car model in CARSIM ® was used, as a benchmark, with and without road input conditions. Both half-car and full-car models were analyzed under steering wheel inputs of 5 • , 10 • and 15 • . Simulation results showed that the half-car model considering road input was found to have a maximum accuracy of 65%. Whereas, the full-car model had a minimum accuracy of 85%, which was significantly higher compared to the half-car model under the same scenario.

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“…As a result, PSD of road roughness while steering should also satisfy its statistical features. Based on the work presented in [14], a triangular mesh method is used for analysis.…”

Section: Steering Working Conditionmentioning

confidence: 99%

Section: Steering Working Conditionmentioning

confidence: 99%

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Wang

Dong

et al. 2017

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…These point clouds require interpolation or subsampling to obtain a final point cloud which averages over all point cloud surfaces. Detwieler and Ferris [30] conducted a study on interpolation methods for three-dimensional terrain surfaces. They concluded that the Inverse Distance to a Power method was the recommended method when fine resolution is required to describe localized roughness and that Kriging is ideal for identifying global trends of the surface.…”

Section: Interpolationmentioning

confidence: 99%

Rough terrain profiling using digital image correlation

Botha

Schalk

2015

Journal of Terramechanics

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Road profiling is an important aspect of vehicle dynamics simulations especially over rough terrains. The accurate measurement of rough terrains allows for more accurate multi body simulations. Three dimensional road profiles are usually performed by utilising a line scan sensor which measures several points lateral to the road. The sensors range from simple road following wheels to LiDAR sensors. The obtained line scans are longitudinally stitched together using the orientation and position of the sensor to obtain a full three dimensional road profile. The sensor's position and orientation therefore needs to be accurately determined in order to combine the line scans to create an accurate representation of the terrain. The sensor's position and orientation is normally measured using an expensive inertial measurement unit or Inertial Navigation System (INS) with high sensitivity, low noise and low drift. This paper proposes a road profiling technique which utilises stereography, based on two inexpensive digital cameras, to obtain three-dimensional measurements of the road. The system negates the use of an expensive INS system to determine orientation and position. The data sets also require 2 subsampling which can be computationally expensive. A simple subsampling routine is presented which takes advantage of the structure of the data sets to significantly speed up the process.

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“…In the context of off-road vehicle simulations, terrain models fall into three categories of increasing complexity: rigid terrain where the main focus is an accurate surface profile [6][7][8][9], use of empirical relationships to find pressure and sinkage directly under the tire [10][11][12], or finite/discrete element approaches [13][14][15][16]. Any off-road vehicle dynamics simulation where the soil deforms considerably requires a terrain model that accurately reflects the deformation and response of the soil to all possible inputs of the tire in order to correctly simulate the response of the vehicle [17].…”

Section: Figure 2 Tire Geometry Used To Determine Collision Points Wmentioning

confidence: 99%

Compaction-Based Deformable Terrain Model as an Interface for Real-Time Vehicle Dynamics Simulations

Reid¹

2013

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Interpolation methods for high-fidelity three-dimensional terrain surfaces

Cited by 24 publications

References 11 publications

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Influence of Road Excitation and Steering Wheel Input on Vehicle System Dynamic Responses

Rough terrain profiling using digital image correlation

Compaction-Based Deformable Terrain Model as an Interface for Real-Time Vehicle Dynamics Simulations

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