Multicriteria Model for Shared Parking and Parking Route Recommender Systems
Bibliographic record
Abstract
In many congested areas, shared parking has gotten increasing attention because of its potential to alleviate parking resource shortages. However, managing parking resources remains a challenge when simultaneously considering multiple decision-making criteria of public travelers in allocating parking spaces and recommending optimal parking routes. To fill this gap, from four perspectives, i.e., driving, among shared parking lots, at a shared parking lot, between shared parking spaces and destinations, we proposed nine criteria for shared parking space allocations and parking route recommendations, and we also gave the quantitative models for different criteria. Furthermore, an analytic hierarchy process Entropy-TOPSIS grey relational analysis (AHP-Entropy-TOPSIS-GRA) method and an improved ant colony algorithm were proposed to solve the proposed allocation of parking spaces and recommend optimal parking routes, respectively. Finally, the validity of our proposed models and algorithms was tested by empirical parking data and road traffic data collected in Huai’an City, Jiangsu province, China. The research helps provide a theoretical foundation for implementing shared parking initiatives and improving public travelers’ parking satisfaction.
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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 | 0.001 | 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 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".