Similarities Between Wheels and Tracks: A “Tire Model” for Tracked Vehicles
Bibliographic record
Abstract
As an important component of land transportation systems, tracked vehicles (TRVs) and wheeled vehicles (WVs) have developed independently in parallel, particularly in the modeling of vehicle-ground interactions. However, their differences are not as significant as they appear. This paper introduces a simplified terramechanics-based track-ground interaction model for the motion control of TRVs on firm ground. The simplified interaction model addresses the problem that the terramechanics-based models are too complex to be applied to optimization-based real-time control algorithms. Interestingly, the proposed track-ground interaction model closely resembles to the tire model used for WVs. Through comparison, we present the unified mechanisms underlying vehicle-ground interactions. In our approach, TRVs can be treated as a special type of skid-steer WV, which benefits the theories and methods of wheel vehicles to be deployed in the TRV domain. Finally, we verify the proposed interaction model with extensive dynamic data from a real dual motor-driven TRV to demonstrate its effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".