Variability in Vehicle and Dummy Responses in Rear-End Collisions
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to quantify the occupant response variability due to differences in vehicle and seat design in low-speed rear-end collisions. METHODS: Occupant response variability was quantified using a BioRID dummy exposed to rear-end collisions in 20 different vehicles. Vehicles were rolled rearward into a rigid barrier at 8 km/h and the dynamic responses of the vehicle and dummy were measured with the head restraint adjusted to the up most position. In vehicles not damaged by this collision, additional tests were conducted with the head restraint down and at different impact speeds. RESULTS: Despite a coefficient of variation (COV) of less than 2% for the impact speed of the initial 8 km/h tests, the vehicle response parameters (speed change, acceleration, restitution, bumper force) had COVs of 7 to 23% and the dummy response parameters (head and T1 kinematics, neck loads, NIC, N(ij) and N(km)) had COVs of 14 to 52%. In five vehicles tested multiple times, a head restraint in the down position significantly increased the peak magnitude of many dummy kinematic and kinetic response parameters. Peak head kinematics and neck kinetics generally varied linearly with head restraint back set and height, although the neck reaction moment reversed and increased considerably if the dummy's head wrapped onto the top of the head restraint. CONCLUSIONS: The results of this study support the proposition that the vehicle, seat, and head restraint are a safety system and that the design of vehicle bumpers and seats/head restraint should be considered together to maximize the potential reduction in whiplash injuries.
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 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 | 0.001 | 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 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".