Efficiency of Semi-Autonomous and Fully Autonomous Bus Services in Trunk-and-Branches Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Automation technology is expected to change the public transport sector radically in the future. One rising issue is whether to embrace the intermediate stage of semi-autonomous buses or to wait until fully autonomous buses are available. This paper proposes a cost model of bus operations considering automation technology. The generalized cost, which is the sum of waiting, riding, operating, and capital cost, is modeled for conventional, semi-autonomous, and fully autonomous bus services on a generic trunk-and-branches network. Semi-autonomous buses achieve reduced unit operating cost through automated platooning on the corridor. The relative efficiency of the different services is studied under a range of scenarios for commercial speed, network structure, and demand distribution. Analytical and numerical results show that fully autonomous buses exhibit great potential through reduced operating and waiting costs even if the additional capital cost is high. The advantages of semi-autonomous buses are weaker and most prominent in networks with low demand along a long corridor such as interurban networks. For both automation levels a commercial speed comparable to conventional vehicles is crucial. The established criteria provide input to planners and operators for understanding the potential of automated bus services.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it