Research on Performance and Function Testing of V2X in a Closed Test Field
Bibliographic record
Abstract
The V2X and cooperative vehicle infrastructure system (CVIS), which leverage the efficient information interactions through V2V, V2I, V2P, and V2N, are known as the advanced and effective technology in reducing traffic accidents and improving traffic efficiency. The complex technical characteristics of V2X and highly reliable service demand of typical V2X applications call for the test needs before the large-scale deployment of V2X. It indicates that the performance and function of V2X devices should be systematically tested and evaluated in extreme and boundary conditions of driving and communication environments before being broadly deployed and applied in infrastructures. Motivated by the previously mentioned needs, a performance and function testing scheme of V2X in a closed test field is studied. According to the analytical viewpoint from the physical layer and MAC layer, the proposed research systematically analyses the technical differences of DSRC and LTE-V, which are two typical V2X protocols, in terms of vehicle speed, communication distance, and channel adaptability. Based on the critical practical test needs from the analytical study, a function and performance test system of V2X specifically for the closed test field is proposed. The performance and typical application effectiveness in intersection environment of DSRC and LTE-V are evaluated. The limitation and proposed improvement strategies of these V2X protocols are analytically discussed.
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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".