Energy and environmental benefits of truck platooning for a busy freight corridor
Bibliographic record
Abstract
Cooperative Truck Platooning Systems (CTPS) have been demonstrated, in controlled testing environments, to yield significant energy savings, while real-world trials have shown much lower benefits. A simulation-based study was undertaken for a busy freight corridor in Canada, to examine the potential fuel savings and emissions reductions associated with the introduction of CTPS, while accounting for many of the variables previously neglected in feasibility and economic analyses. Results demonstrate lower benefits than previously predicted, closer to those observed in on-road trials. Upwards of 6.5 % savings are possible for platoons no longer than four trucks with a minimum 15 m separation distance, with only 3.7 % overall savings when a 60 % usage rate is assumed. This provides emissions reductions of about 100 kT of CO 2 per year (about 0.2 % of Canada’s current heavy-freight transportation emissions). Additionally, CTPS benefits are further reduced with precipitation- and location-based usage restrictions for the same simulation conditions.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".