Reducing Vehicle Submersions and Consequent Fatalities on Highway I-75 in Florida (Alligator Alley): Effectiveness of a Cable Safety Barrier System
Bibliographic record
Abstract
Objective: We evaluated the effectiveness of a Cable Safety Barrier (CSB) system in preventing Run-Off-Road (ROR) Vehicle Immersions (VIs) and fatalities in canals along the I-75 freeway (Alligator Alley) in Collier County, Florida. The CSB system, which runs along both sides of the 80-km stretch of freeway and was installed between 2003 and 2004. Methods: Data from the Fatal Analysis Reporting System (FARS) were used to compare annual VIs and VI fatalities between pre-installation of the CSB system (1995-2002) to post-installation (2005-2012). As well, post-installation data from the Florida Department of Transport (FDOT) (2007-2011) and police reports were reviewed to determine the number of, and manner in which, vehicles were either contained by, or crossed, the CSB by either penetrating or overriding the barriers. Results: Pre- to post-installation, total accidents increased from 81.4/y to 106.2/y, accidents resulting in VIs decreased from 13.8% to 2.4%, and accidents resulting in VI fatalities decreased from 3.4% to 0.4% (FDOT). Fatal vehicle immersions decreased from 2.4/y to 0.9/y (P<0.01) and vehicle immersion fatalities decreased from 3.3/y to 1.4/y (P<0.05) (FARS). Post-installation, 531 accidents occurred with 110 ROR vehicles travelling towards the canals; 91 vehicles contacted the CSB with only 14 vehicles (15.4%) penetrating the barrier, and 7 (7.7%) overriding the barrier (FDOT). Conclusion: The CSB system along I-75 in Collier County dramatically decreased ROR vehicles from reaching the parallel canals, and consequent vehicle immersion fatalities. Results support the installation of lateral CSB systems on other high-risk roadways to reduce ROR crashes into water, or with other secondary hazards.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".