Development of a microsimulation-based mass evacuation model for persons needing mobility assistance
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
This research proposes a framework for microsimulation modelling of traffic evacuation, considering persons needing mobility assistance (PMA). The study develops a hybrid approach to evaluate four designated evacuation routes under different network conditions. These routes are incorporated into a microsimulation model utilizing dynamic traffic assignment for regular vehicles and pre-defined assignment for emergency vehicles (EVs). The model executes three traffic conditions under two scenarios to evaluate the Average Evacuation Time (AET) for an EV exiting the Halifax peninsula. The first scenario, ‘Out of Danger Zone' (ODZ), determines AET to exit the peninsula, while the second, ‘To the Shelter Location’ (TSL), evaluates AET to reach designated shelters. The results show that routes 1 and 4 are the fastest under case 3 for both scenarios, while case 2 is the most realistic. Under case 2, route 2 is the fastest for ODZ, and route 1 for TSL. The suggested method supports policymakers in planning PMA evacuations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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