A Study of the Performance of Automatic Emergency Braking Systems When Presented with Pedestrian Targets
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Automatic Emergency Braking (AEB) systems equipped on modern vehicles have grown increasingly sophisticated in recent years, with modern vehicles detecting and attempting to avoid collisions with pedestrian targets. While certain studies evaluated the performance of a few vehicle models, the overall development and progress of these systems has not been studied extensively. This paper presents an analysis of the performance of vehicles equipped with pedestrian automatic emergency braking systems (P-AEB) when presented with stationary and moving pedestrian targets. A total of 2374 tests were completed across 20 brands and 71 unique vehicle models. The success rates of the P-AEB systems will be presented. For test cases with moving pedestrians, the performance of the P-AEB systems will also be compared to that of typical drivers. This study will provide a valuable report of the current state of the P-AEB systems as they continually develop and improve.</div></div>
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".