An Enhanced C-V2X Mode 4 Resource Selection Scheme for CAV Platoons in a Multilane Highway Scenario
Bibliographic record
Abstract
This paper proposes an enhanced C-V2X mode 4 resource selection scheme for CAV platoons to support reliable intra-platoon message delivery. The enhanced scheme introduces three enhancement mechanisms, which aim to address merging collisions and hidden-node collisions in intra-platoon message delivery and enhance the sensing-based semi-persistent scheduling (SPS) scheme standardized by 3GPP. A resource partition mechanism is introduced to avoid merging collisions among vehicles moving in opposite directions; an intra-platoon cooperative mechanism is introduced to enable the leader of a platoon to know the resource occupation status on the hidden nodes of the platoon and thus avoid hidden-node collisions; and a packet collision detection mechanism is introduced to enable a non-platoon vehicle to detect and avoid merging collisions due to lane-change maneuvers. Simulation results demonstrate that compared with the standardized SPS scheme, the enhanced scheme can improve the efficiency of intra-platoon message delivery in terms of the intra-platoon packet delivery ratio.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".