Ergonomic modeling and evaluation of automobile seat comfort
Bibliographic record
Abstract
This research work is geared toward proving that automobile seat comfort, which is a subjective construct, can be predicted from objective measures. This type of forecasting ability would effectively improve the efficiency with which seats are designed. Presently, seats are developed in an iterative manner because subjective feedback drives the design. Iteration requires time and costly prototypes. This could be justified if the process guaranteed a comfortable seat. Unfortunately, this is not the case. Even with numerous technologies available, the automotive seating industry has had limited success quantifying comfort. The problem stems from the lack of a scientific method. This deficiency was addressed through the creation of a repeatable data collection protocol for seat interface pressure measurement. Seat comfort cannot be quantified without an understanding of the consumers' likes and dislikes. The best way to obtain this information is to gauge perceptions of comfort through a survey. This research is significant in that it (1) provides a survey with acceptable levels of reliability and validity and (2) defines an overall comfort index. The overall comfort index was used as the dependent variable in a prediction model. This would not be a viable undertaking without a reliable and valid survey. Using a stepwise regression procedure, the link between objective measures and subjective perceptions was established and validated. From the model, human criteria for seat interface pressure parameters were established. The model also demonstrated that appearance was related to comfort. Due to the lack of emphasis on the educational side of automobile seat usage, drivers are not fully realizing the comfort-enhancing benefits of seat adjusters. This study, in addition to providing direction on how to adjust the seat for maximum comfort, presents and validates a model to predict driver selected track position as a function of occupant demographics and anthropometry. If this research is to affect design practices, direction on how to impact the objective measures of comfort is required. To this end, seat geometry and contour design guidelines were derived. These guidelines represent an important advancement in the body of knowledge dealing with automobile seat comfort.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .K65. Source: Dissertation Abstracts International, Volume: 62-10, Section: B, page: 4718. Adviser: S. M. Taboun. Thesis (Ph.D.)--University of Windsor (Canada), 2000.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".