Paper presented at ISTVS 2025 | 55th Conference of the International Society for Terrain-Vehicle Systems https://doi.org/10.56884/M7EPI3Y7
Authors: Amir Khosravian, Sadegh Yarmohammadisatri, Corina Sandu, Yinglong HE, Davide Tavernini
Keywords: Off-road mobility; Vehicle dynamics; Tire-terrain interaction; Deformable terrain modeling; Flexible tire modeling
Abstract:
Accurate simulation of off-road vehicle dynamics on deformable terrains remains computationally challenging despite advances in vehicle dynamics modeling. In this paper, we develop an efficient yet high-fidelity off-road simulation toolbox, which incorporates the Hybrid Soft Soil Tire Model (HSSTM), a semi-empirical, experimentally validated off-road tire model, and the widespread simulation platform IPG CarMaker. This integration enables high-fidelity simulations on deformable terrains and facilitates the development of off-road vehicle control algorithms for highly dynamic scenarios. The integrated tire-vehicle model provides a tool for simulating the ride, handling, and mobility of off-road vehicles. HSSTM models the tire as discretized lumped masses with Kelvin-Voigt elements on a 3D deformable terrain. Unlike rigid-ring models, HSSTM captures tire flexibility, which is crucial for simulating tire dynamics on medium-hard to rigid terrains. To enhance computational efficiency, we adopt a Dynamic Terrain Adaptation algorithm that models only a localized portion of the terrain around the vehicle, dynamically updating as the vehicle navigates. Simulations on non-deformable terrain demonstrate that HSSTM tire forces are in good agreement with existing on-road tire models (e.g., MF-Swift). Further, simulations on deformable terrains in longitudinal and lateral scenarios (including force coupling) confirm accurate off-road dynamics representation across various terrain types. The plug-in assesses contact patch pressure, normal and shear forces, elastic and plastic sinkage, and multi-pass effect. Finally, a sensitivity analysis across various simulations with different tire and terrain discretization levels evaluates the accuracy/efficiency trade-off of our plug-in.
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