Traffic and Safety Implication of Adaptive Cruise Control for Two-Lane Two-Way Highways Traffic Operation
Bibliographic record
Abstract
Potential impacts of the Adaptive Cruise Control (ACC) system on safety and traffic operation of two-lane/two-way highways have not been adequately researched. This mainly regards how ACC influences the overtaking maneuver when vehicles are equipped with an activated ACC. ACC is intended to keep safe headways between vehicles in the traffic stream; however, this can also affect the overtaking decision and the passing process due to larger initial headways between overtaking and overtaken vehicles at the beginning of the maneuver. In this paper, microscopic simulation model is used to investigate the potential impacts of ACC system on overtaking maneuvers for two-lane highways and its resultant safety and traffic effects. Traffic and safety measures - including average travel speed, percentage of time spent following, number of overtakes, overtaking time, and time to collision with oncoming vehicle(s) - are measured for different ACC scenarios, as well as for normal following conditions where no ACC is in effect. The results showed that ACC can significantly impact safety and traffic indices associated with overtaking maneuver on two-lane, two-way highways.
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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 | 0.000 | 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) | 0.001 | 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".