In-Vehicle Safety Features and Their Impacts on Fatal Crashes
Bibliographic record
Abstract
One of the most important safety metrics in transportation engineering is fatal crashes, and a major effect to improve safety is to reduce fatal crashes. Therefore, safety features are continuously tested and equipped in vehicles to reduce fatal crashes and provide safety to road users. This study was initiated to explore the relationship between two in-vehicle safety features and their impact on fatal crashes. These two in-vehicle safety features are the Lane Keep Assist System (LKAS) and the Forward Collision Warning System (FCWS). This thesis analyzed nine different General Motors (GM) vehicles’ make, model, and year to test which in-vehicle safety feature reduced fatal crashes. To test the LKAS safety feature, run-off-road fatal crashes were analyzed using the Fatality Analysis Reporting System (FARS) data for the Chevrolet Silverado, the Chevrolet Equinox, the GMC Yukon, the GMC Sierra, and the Cadillac Escalade model vehicles. To test the FCWS safety feature, rear-end fatal crashes were analyzed using FARS data for the Chevrolet Equinox, the Chevrolet Traverse, the Buick Enclave, the GMC Acadia, and the GMC Terrain. The odds ratios for the LKAS safety feature for the Chevrolet Silverado, the Chevrolet Equinox, the GMC Sierra, the GMC Yukon, and the Cadillac Escalade model vehicles were 0.704, 0.615, 0.601, 0.446, and 1.149, respectively. The odds ratio showed, when examining the LKAS safety feature for the Chevrolet Silverado, the Chevrolet Equinox, the GMC Yukon, the GMC Sierra, and the Cadillac Escalade model vehicles, that four of the five vehicle models examined resulted in reductions in run-off-road fatal crashes; the GMC Yukon was not statistically significant in reducing this type of crashes. Additionally, the odds ratios for the FCWS safety feature for the Chevrolet Equinox, the GMC Terrain, the Chevrolet Traverse, the GMC Acadia, and the Buick Enclave model vehicles were 0.814, 0.199, 0.873, 0.638, and 0.143, respectively. The odds ratio showed, when examining the FCWS safety feature for the Chevrolet Equinox, the Chevrolet Traverse, the Buick Enclave, the GMC Acadia, and the GMC Terrain model vehicles, that four of the five vehicles examined resulted in a reduction in rear-end crashes; the Chevrolet Equinox, the Chevrolet Traverse, and the GMC Acadia were not statistically significant in reducing run-off-road fatal crashes. In addition, the GMC Terrain results were undefined. Key Words: Lane Keep Assist System (LKAS), Forward Collision Warning (FCWS), fatal crashes, and General Motors (GM)
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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 | 0.000 | 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 | 0.001 |
| 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".