A Taxonomy of Data Communication Protocols for Vehicular Ad Hoc Networks
Bibliographic record
Abstract
Vehicular ad hoc networks (VANETs) are the potential core of the intelligent transportation system (ITS), which aims to increase people safety and improve transportation efficiency. This chapter provides the first known taxonomy of VANET data communication protocols, based on road dimension, neighbor knowledge, acknowledgment, start of forwarding, competition to retransmit, vehicle connectivity, urgency, and message contents. It examines several types of multihop communications, required by novel ITS, and explains the ingredients of the most relevant existing communication protocols. The chapter outlines the existing solutions and highlights their drawbacks. The existing geocasting can be divided into two groups, depending on urgency metrics: reliability oriented (RO) protocols, and time critical (TC) solutions; these are discussed in the chapter. Controlled Vocabulary Terms automated highways; data communication equipment; vehicular ad hoc networks
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 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".