A Unified Lateral Preview Driver Model for Road Vehicles
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
This paper presents a unified lateral preview driver model for closed-loop dynamic simulations of road vehicles. Numerous driver models have been proposed for Single-Unit Vehicles (SUVs). Some SUV-based driver models have been applied to closed-loop simulations of Multi-Trailer Articulated Heavy Vehicles (MTAHVs). However, the dynamics of MTAHVs is significantly different from that of SUVs, and drivers of Multi-Unit Vehicles (MUVs) have different driving performance and skills. Very few driver models have been proposed for closed-loop simulations of MUVs. This paper designs the unified driver model, considering the dynamic features of both SUVs and MUVs. The driver model is derived using a sliding mode control (SMC) technique, and it distinguishes itself from conventional driver models with a number of features. Simulations demonstrate the applicability and effectiveness of the proposed driver model.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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