Safety Comparison of Vehicular Platoons Under Different Bidirectional Communication Topologies: A Signal Analysis Method
Bibliographic record
Abstract
This paper conducts a comparative analysis of bidirectional communication topologies in vehicular platooning, emphasizing their impact on safety during travel. Introducing two novel metrics, the Accumulative Average Penalty of Minimum Time to Collision (AAPMTTC) and Accumulative Average Deceleration Rate to Avoid Collision (AADRAC), the study evaluates collision susceptibility between neighboring vehicles, taking into consideration their relative velocities and accelerations. Utilizing platoon dynamics based on intervehicle distances and their derivatives, the analysis captures the evolving vehicle behaviors over travel time. Results highlight the safety benefits of communication topologies where follower vehicles receive information from more preceding vehicles, particularly when incorporating the leader vehicle's state. This research underscores the significance of information exchange within vehicular platoons and offers insights for providing more safety through design of communication structure in automated driving scenarios in vehicular platooning.
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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 | 0.001 |
| 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) | 0.001 | 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".