Characteristics of naturally formed semitruck platoons on interstate highways and their implications for truck platooning field deployment
Bibliographic record
Abstract
This paper presents an effort to address urgent issues associated with semitruck platooning. The weigh-in-motion data were first examined to determine the characteristics of naturally formed semitruck platoons. A safety-based two-vehicle platoon model was then utilized to determine the critical headways for assessing the safety of semitruck platooning in various driving scenarios. The possibilities for passenger vehicles to cut into semitruck platoons were assessed using actual vehicle headway data. Finally, the potential impacts of semitruck platooning on typical interstate highway pavements were assessed using finite element analysis. Most semitruck platoons consist of two to three vehicles. An optimal platoon gap of 0.94 s was identified for connected and automated semitruck platooning. The potential impacts of truck platooning on concrete pavement were negligible for a platoon gap greater than 0.2 s. The maximum possible impact was less than 4% in terms of the service life reduction for interstate asphalt pavement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".