Dealing with the Empty Vehicle Movements in Personal Rapid Transit System with Batteries Constraints in a Dynamic Context
Bibliographic record
Abstract
The Personal Rapid Transit is a new emergent transportation tool. It relies on using a set of small driverless electric vehicles to transport people on demand. Because of the specific on-demand characteristic of the Personal Rapid Transit system, many Personal Rapid Transit vehicles would move empty which results in a high level of wasted transportation capacity. This is enhanced while using Personal Rapid Transit vehicles with limited electric battery capacity. This paper deals with this problem in a real time context while minimizing the set of empty vehicle movements. First, a mathematical formulation to benchmark waiting time of passengers in Personal Rapid Transit systems is proposed. Then, a simulation model that captures the main features of the Personal Rapid Transit system is developed. A decision support system which integrates several real time solution strategies as well as a simulation module is proposed. Our dispatching strategies are evaluated and compared based on our simulation model. The efficiency of our method is tested through extensive test studies.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".