Why vehicle design matters: Exploring the link between line-of-sight, driving posture and risk factors for injury
Bibliographic record
Abstract
Load haul dump (LHD) vehicles have been involved in workplace accidents resulting in fatal injuries and LHD operators also report high rates of musculoskeletal injury. Poor line-of-sight (LOS) and awkward postures adopted by the LHD operator increase the risk of driving related accidents and musculoskeletal injury. The purpose of this case study was to simultaneously measure point of regard (POR), driving posture and sitting position during the operation of a LHD in an underground mining environment in order to further understand the link between these variables and the design of the LHD vehicle. A 5.35 m3 bucket LHD vehicle was used and several driving tasks were analysed. The case study results showed that despite the driving task, the operator looked to the left side of the vehicle 65% of the time. Postural implications include extreme neck rotation (> 40 degrees) for 85% of the work cycle and the average peak compression at L4/L5 was 1843N. Despite changes in driving posture the average center of pressure location for the seated operator moved very little; however changes in peak pressure were observed. The design of the LHD vehicle dictated what the operator could see, which had a direct influence on driving postures adopted by the operator and resulted in several risk factors for musculoskeletal injury.
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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 | 0.000 |
| 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".