DSAM: Dual-Strategy Simulation Acceleration-Based Model for Uncrewed Ground Vehicle Mobility Prediction

The Next-Generation NATO Reference Mobility Model (NG-NRMM) currently integrates numerical simulation technologies based on the discrete element (DE) method and finite element (FE) method to predict the global mobility map of unmanned ground vehicles over soil terrains. However, computational efficiency remains a significant challenge. To address this issue, we propose an accelerated global mobility prediction method, DSAM. Unlike previous studies that focused solely on terrain modeling or computational acceleration, DSAM introduces a dual-strategy synergy that combines data-driven FE-DE coupling with adaptive soil patch computation to achieve order-of-magnitude simulation speedup. Specifically, our method enhances simulation efficiency through two primary strategies: First, in terrain modeling, we introduce a data-driven FE-DE coupling approach to overcome the computational dimensionality challenges inherent in DE simulations. Second, in simulation computation, we propose a non-complete moving soil patch method combined with multi-CPU parallel processing to substantially improve the real-time performance of mobility simulations. Experiments using real terrain data show that DSAM significantly improves prediction efficiency while maintaining accuracy.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-05-28
DOI
https://doi.org/10.1109/tvt.2025.3574523
Citations
2
Primary Topic
Simulation and Modeling Applications
Type
article
Field-Weighted Citation Impact
2.43
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article

DSAM: Dual-Strategy Simulation Acceleration-Based Model for Uncrewed Ground Vehicle Mobility Prediction

Chunmao Jiang, Runxin Niu, Chen Hua, Yuliang Wei
2 citations
IEEE Transactions on Vehicular Technology
Simulation and Modeling Applications
2.43
article

DSAM: Dual-Strategy Simulation Acceleration-Based Model for Uncrewed Ground Vehicle Mobility Prediction

Chunmao Jiang, Runxin Niu, Chen Hua, Yuliang Wei
article en
2 citations

Abstract

The Next-Generation NATO Reference Mobility Model (NG-NRMM) currently integrates numerical simulation technologies based on the discrete element (DE) method and finite element (FE) method to predict the global mobility map of unmanned ground vehicles over soil terrains. However, computational efficiency remains a significant challenge. To address this issue, we propose an accelerated global mobility prediction method, DSAM. Unlike previous studies that focused solely on terrain modeling or computational acceleration, DSAM introduces a dual-strategy synergy that combines data-driven FE-DE coupling with adaptive soil patch computation to achieve order-of-magnitude simulation speedup. Specifically, our method enhances simulation efficiency through two primary strategies: First, in terrain modeling, we introduce a data-driven FE-DE coupling approach to overcome the computational dimensionality challenges inherent in DE simulations. Second, in simulation computation, we propose a non-complete moving soil patch method combined with multi-CPU parallel processing to substantially improve the real-time performance of mobility simulations. Experiments using real terrain data show that DSAM significantly improves prediction efficiency while maintaining accuracy.

IEEE Transactions on Vehicular TechnologyVol. 74(11)
Chinese Academy of Sciences (CN), Hefei Institutes of Physical Science (CN), Changzhou Institute of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 11%
Simulation and Modeling Applications
2.43
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DSAM: Dual-Strategy Simulation Acceleration-Based Model for Uncrewed Ground Vehicle Mobility Prediction — Chunmao Jiang, Runxin Niu, et al. · IEEE Transactions on Vehicular Technology (2025) | TGRS Research Map | TGRS