Exposure to Whole-Body Vibration in Commercial Heavy-Truck Driving in On- and Off-Road Conditions: Effect of Seat Choice
Bibliographic record
Abstract
Trucking is a key industry in Canada with around 180 000 professional drivers. As an industry it has a disproportionately high injury claim rate, particularly for back injuries. Whole-body vibration (WBV) can contribute to the onset and development of low back disorders, and is a well-documented exposure among driving professions. A widely adopted WBV mitigation measure focuses on hydraulic and/or pneumatic passive suspension systems both in the driver's seat and underneath the vehicle cab. Passive suspension 'air-ride' seats are the current industry standard but new technologies such as the electromagnetic active vibration cancelling (EAVC) seats offer potentially substantial improvements in WBV reduction. In this paper, we evaluate and compare four commonly used truck seats (three air-ride, one EAVC) for their vibration damping characteristics and WBV exposure attenuation in on- and off-road conditions. We recruited 24 professional truck drivers who drove 280 km (mixed on-road and off-road) in ore-haul trucks under four different seating conditions. Following the ISO 2631-1 WBV standard, vibration measurements were made on the cab floor and seat pad, and 8-h average weighted vibration (A(8)) and 8-h vibration dose values (VDV(8)) were calculated, as well as the Seat Effective Amplitude Transmissibility (SEAT), and daily vibration action limits (DVALs). These measures were compared between seat types, as well as road conditions. The EAVC seat gave best performance for both A(8) (0.27 m s-2) and VDV(8) (6.6 m s-1.75). The EVAC seat had the lowest SEAT tested (36.2%) and the longest DVAL. However, among the three passive air-suspension seats, two showed significantly reduced A(8) (0.43 and 0.44 m s-2) and VDV(8) (9.1 and 9.3 m s-1.75) exposures relative to the third passive air-suspension seats [A(8) (0.54 m s-2) and VDV(8) (11.1 m s-1.75)]. These differences in exposures among the three passive air-suspension seats resulted in varying DVAL times, with the worst performing seat reaching the DVAL after only 6.3 h of driving. There was also a seat by road type interaction; there were performance differences between the passive air-suspension seats on-road, but not off-road. The observed reduction of the WBV exposures measured from the EAVC seat was consistent with previous results. But we showed that there can also be substantive differences among seats that are the current industry standard. These differences were more evident on-road than off-road, which suggests that more work needs to be done to understand seat performance characteristics, and in matching the correct seat technology to the driving task. We demonstrated that WBV exposures in current industry conditions may exceed health-based exposure limits; this has policy relevance because WBV exposures are linked to prevalent and costly adverse health conditions in a working population that is ageing. Increased WBV measurement collection is recommended to ensure the anticipated exposure attenuations are achieved when seats are relied upon as an engineered control against WBV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".