Preview active suspension design for convoy vehicles
Bibliographic record
Abstract
Convoy vehicles, defined as individual vehicles traveling with close following distances on a specified path, have been recently the subject of research especially in military applications. Convoy vehicles are used to carry soldiers, weapons and army supplements. Military drivers are often young and inexperienced, and more prone to lose control of vehicles on rough terrain. In addition, Intelligent Vehicle Highway Systems with autonomous civilian vehicles travelling in platoons are an active research and experimentation topic. -- The idea of communicating dynamic responses between preceding and following vehicles, to improve the followers' ride comfort and handling, has been identified as a research need for convoy vehicle systems. -- This research implements a form of preview control to improve the vertical dynamics of convoy vehicles. An academic virtual convoy, composed of a lead vehicle with active suspension system, and a follower vehicle with preview-controlled active suspension, is developed in MATLAB and SIMULINK. Preview control gives a theoretical improvement over active control by further decreasing sprung mass acceleration (ride quality) and/or improving road holding. Quarter car models with two degrees of freedom (DOF) are employed for modeling and simulation. In contrast to conventional preview control with look-ahead sensors, the vertical response states of the lead vehicle are used to generate feed forward control gains in addition to feedback control gains for the preview controller of the follower vehicle. The results show improved ride comfort and road holding of the follower vehicle with the novel preview approach compared to a lead vehicle with active suspension. Moreover, the power demand for the follower vehicle suspension is much less than for the lead vehicle. Longitudinal dynamics of a convoy system, with five vehicles, are evaluated and an adaptive cruise control system is implemented to control the longitudinal aspects of the convoy such as relative space and velocity among vehicles. Future work will implement the state-based preview controller into such a convoy, with variations in following distance, to test the robustness of the method.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".