Path planning and re-planning of lane change manoeuvres in dynamic traffic environments
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
Automatic lane change is of utmost importance in designing autonomous vehicles and driver assistant systems. In this study, a novel path for lane change manoeuvres, based on mathematical functions, is introduced. To obtain a suitable path for lane change manoeuvres, four functions, namely quintic, septic, sinusoidal, and tangent functions, were examined. The analysis revealed that, according to the ISO Standards and peak acceleration criterion, a quintic function has the advantage of passenger comfort over other path functions. After choosing the appropriate path, an algorithm for re-planning the lane change path, based on dynamic traffic conditions, was proposed. The simulation results show that the proposed algorithm is capable of designing the path in various traffic conditions. Moreover, the algorithm can navigate the vehicle to the initial lane, if the manoeuvre is not possible. Our analytical results showed that the designed paths are suitable, comfortable, and safe.
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