An Enhanced Resource Selection Scheme for Efficient Intra-Platoon Message Delivery
Bibliographic record
Abstract
This paper proposes an enhanced resource selection (eInP-RS) scheme for efficient intra-platoon message delivery of cooperative awareness messages (CAMs) and decentralized environmental notification messages (DENMs). To achieve this goal, the eInP-RS scheme allows each vehicle to transmit CAM and DENM packets on a C-V2X channel (CH1) and an 802.11p channel (CH2), separately, and introduces four mechanisms to enhance the standardized sensing-based SPS scheme. A contention window (CW) size adjustment mechanism is introduced to enable a vehicle to adjust its CW size according to the information it collects on CH1 in order to avoid potential packet collisions on CH2; a resource partition mechanism is introduced to divide frequency-time resources in a selection window into two sets in order for vehicles moving in opposite directions to select different resources and thus avoid potential merging collisions on CH1; an intra-platoon cooperation mechanism is introduced to enable the PL of a platoon to know the resource and channel occupation information of the platoon's hidden nodes on CH1 and CH2; and a packet collision detection mechanism is used to enable a non-platoon vehicle to detect packet collisions occurring on both channels after a lane-changing maneuver to avoid potential merging collisions. Simulation results show that the proposed eInP-RS scheme outperforms the standardized sensing-based SPS scheme in terms of the intra-platoon CAM/DENM delivery ratio and the average intra-platoon DENM delivery delay.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".