About Deterministic and non-Deterministic Vehicular Communications over DSRC/802.11p
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 work, we introduce a priority-aware deterministic access protocol called Vehicular Deterministic Access VDA. VDA is based on 802.11p/DSRC and allows vehicles to access the shared medium in collision-free periods. Particularly, VDA supports two types of safety services emergency and routine safety messages with different priorities and strict requirements on delay. To avoid long delays and high packet collisions, VDA allows vehicles to access the wireless medium at selected times with a lower contention than would otherwise be possible within a two-hop neighborhood by the classical 802.11p Enhanced Distributed Channel Access or Distributed Coordination Function schemes. A non-VDA-enabled vehicle, that is, a vehicle not configured with the optional VDA capability over 802.11p, may start transmitting on the shared channel just before or during the VDA opportunities reserved for vehicles with VDA capabilities. To avoid the aforementioned issues and prevent interfering transmissions from VDA-enabled vehicles and non-VDA-enabled vehicles, we also proposed a novel scheme called extended VDA. We analyzed the impact of several design tradeoffs between the contention free period/contention period dwell time ratios on the performance of safety applications with different priorities for VDA and extended VDA. Simulations show that the proposed schemes clearly outperform the backoff-based schemes currently used by 802.11p in high communication density conditions while bounding the transmission delay of safety messages and increasing the packet reception rate. Copyright © 2012 John Wiley & Sons, Ltd.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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