Design and Operation of Autonomous Underground Freight Transportation Systems
Bibliographic record
Abstract
Despite the increases in freight transportation demand, options for increasing capacity of the overground freight transportation infrastructure system are limited. This paper investigated the design and operation of an underground freight transportation (UFT) system that uses space below highways. Underground freight transportation is a class of automated transportation system in which individual vehicles carry freight through tunnels and pipelines between intermodal terminals. This paper presents attributes for schematic designs and operations for two UFT scenarios: a long-haul system which transports standard shipping containers between the Port of Houston and a terminal near Dallas, and a short-haul system which carries pallet-size freight between the Port of Houston and a satellite terminal near Houston. The appropriate design details were determined by the size of the freight, the types of vehicles and tunnels, and the propulsion system. In addition, operational attributes such as operating speed, headway, line capacity, and associated fleet sizes were addressed. Design sketches and operational equations presented in this paper are generally independent of the freight sizes and route lengths and this case study can be used as guidance for the design and operation of other freight tunnels and pipelines.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".