Automatic steering control in tractor semi-trailer vehicles for low-speed maneuverability enhancement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, a controller for an automated steering articulated vehicle with the special capability to reduce off-tracking in low-speed maneuvers is proposed. Conventional tractor–trailers have a large off-tracking in low-speed maneuvers. In the proposed vehicle, all wheels of the tractor and trailer are steerable (all wheel steering). The controllers of the tractor and trailer work independently, and each one consists of two layers. A fuzzy controller and a PID controller are designed in the upper and lower layer, respectively, to control the actuators. The aim of the controller is to ensure that the end points of both the tractor and the trailer exactly follow the path of tractor’s first point. To assess the performance of proposed controller as well as steerability effect of all wheels in low speeds, the TruckSim simulation software is used. The simulation results confirm that the proposed approach improves the maneuverability and accuracy of path tracking not only compared to conventional vehicles but also to the conventional tractor–active trailer scheme, which was previously proposed by a number of studies. Additionally, it reduces lateral tire forces to enhance the working life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it