Aerial Ropeway Transportation Systems in the Urban Environment: State of the Art
Bibliographic record
Abstract
The evolution of public transit modes has been remarkable, fueled by the need for different transit modes to handle different demand levels, urban environment patterns, and natural constraints and barriers. One of these needs is the desire to overcome geographical and topographical barriers such as mountains, valleys, and bodies of water, which cannot be conquered by conventional transit modes without very large investments and changes made to the natural topography. Aerial ropeway transit (ART), a type of aerial transportation mode in which passengers are transported in a cabin that is suspended and pulled by cables, is one of the solutions to such cases. ART has its origins in aerial lifts that have been used for decades in Alpine ski resorts to transport skiers and tourists in cable-suspended cabins. The use of aerial transportation in the urban environment, which was once considered an unlikely possibility, has gained more attention worldwide, and it is now used as a public transit mode in several terrain-constrained urban areas around the world. This article describes the origins of aerial transportation and its advantages, components, service characteristics, available technologies, and applications around the world. The paper concludes with a fair assessment of the existing ART technologies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".