A shortest path algorithm with novel heuristics for dynamic transportation networks
Why this work is in the frame
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Bibliographic record
Abstract
Finding an optimal route in dynamic real‐time transportation networks is a critical problem for vehicle navigation. Existing approaches are either too complex or incapable of managing complex circumstances where both the location of a mobile object and traffic conditions change over time. In this paper, we propose an incremental search approach with novel heuristics based on a variation of the A* algorithm–Lifelong Planning A*. In addition, we suggest using an ellipse to prune the unnecessary nodes to be scanned in order to speed up the dynamic search process. The proposed algorithm determines the shortest‐cost path between a moving object and its destination by continually adapting to the dynamic traffic conditions, while making use of the previous search results. Experimental results evince that the proposed algorithm performs significantly better than the well‐known A* algorithm.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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