Analysis of On-Road Highway Testing for a Two Truck Cooperative Adaptive Cruise Control (CACC) Platoon
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">A Cooperative Adaptive Cruise Control (CACC) platooning system was developed and implemented on Class 8 heavy duty trucks. The system allows for longitudinal, or gap spacing, control of the vehicle, while lateral control is maintained by the driver. Many previous aerodynamic studies have shown a reduction in drag force from vehicles traveling in close proximity to each other. This “drafting” effect leads to potential fuel savings for all vehicles in the platoon. Several automated driving and CACC systems have been tested in simulation or closed track settings to evaluate these fuel savings. However, there are only a few examples of potential fuel savings in real on-road or highway environments. This paper provides control performance, fuel economy, lateral offset, and number of neighboring vehicle results of an on-road platoon. The CACC system was implemented on two Peterbilt 579 commercial trucks with unloaded 53’ box trailers. Testing occurred on highways around Montreal, Quebec with a total platooned distance of approximately 1090 km. Gap distances varied over a range of 18.3-91.4 m (60-300 ft) with speeds of 89-105 km/h (55-65 mph). Fuel economy analysis was calculated from the SAE J1939 CAN bus data. Overall, the results show the feasibility and realizable benefits of CACC systems. Future validation of this CACC platooning system through SAE type II fuel tests is also discussed.</div></div>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".