Operation of multimodal transport system during mass evacuations
Bibliographic record
Abstract
Among the shortcomings identified in the aftermath of Hurricane Katrina in New Orleans was the need for improved disaster planning for persons without access to personal transportation. Inadequate advanced planning for limited mobility evacuees in New Orleans prior to 2005 left a significant portion of the local population unable to flee in advance of the storm. Since 2005, state and local officials in Louisiana have developed transit assisted mass evacuation plans that now seek to accommodate carless populations. Since this plan is relatively new and does not have a history of experience on which to base its performance, it is difficult to know how well, or even if, it will work. Recently, an effort was undertaken to apply microscopic scale traffic simulation to evaluate key aspects of the New Orleans assisted evacuation plan. This study is thought to be significant because it is among the first ever to model transit bus-based evacuation processes, including the loading and unloading and the movement of individual evacuees and vehicles. Although this was a simulation-based theoretical study, the routes, timing and movements of people and busses are based on the actual plan and the results of the model have been verified, validated, and calibrated to capture the essence of the Hurricane Katrina evacuation process of 2005. This paper describes the development of this model as well as the results gained from it. In the research, two sets of transit bus routing scenarios were developed and modeled for New Orleans. Measures such as evacuation time, average travel time, average evacuation speed, and queue length were used to evaluate the performance of the transit bus movements within the general evacuation. Additional measures such as the walking and waiting times of evacuees moving to bus pick-up points were also used to assess loading processes. Among the general findings of the research was that routing busses to alternate arterial routes reduced the overall travel time by as much as 53% and the total evacuation time by up to 10% in some cases. It was also found that the transit evacuation had quite small impacts on the overall movement of evacuation traffic, but did increase queue lengths on some segments of the evacuation network. Finally, it was found that the planned location of bus pick-up points limited average walking time for evacuees to a half hour or less.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".