Comparison of two suspension control strategies for multi-axle heavy truck

Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver’s seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.

Prevalence of risk factors for undiagnosed obstructive sleep apnoea is high in truck drivers on UK roads

Objectives To determine the prevalence of symptoms and risk factors of obstructive sleep apnoea (OSA) in truck drivers at a UK large truck stop. Methods Over a 5 day period, truck drivers completed a short questionnaire at a major UK ‘truck stop’. The questionnaire asked about OSA rist factors and symptoms, and included the Epworth Sleepiness Scale (ESS). Additionally, measurements of height, weight and collar size were taken. 148 truck drivers participated and within this random group the risk factors of OSA that were looked for were:men age over 40 y, obesity, parge neck circumference, smoking, high ESS and bed partner reporting snoring with witnessed apnoeas. Results Our sample were all men, with 82% aged over 40 y. 47% were obese (compared with 23% for UK men in general) and average neck circumference was 42 cm (compared with 38 cm for UK men in general – Martin et al 1997). 31% smoked (vs 21% for general population), and ESS averaged 2.1 points higher than expected for a healthy population (Johns et al 1997). Snoring was quite evident at 57% (compared wth 40% for men in general) and witnessed apnoeas were almost double (7%) compared with 3.8% given by Ohayon et al (1997) generally for men. Conclusion 8 key symptoms and risk factors of OSA have been found to be prevalent in a sample of truck drivers on UK roads, and to greater extent that for estimates in the general male population. Bed partners of truck drivers reporting witnessed apnoeas strongly suggests this group has a high potential for undiagnosed OSA. OSA sufferers are known to be at high risk of causing road traffi c accidents. This, together with the large size of trucks, then the potential for serious road crashes is great. Truck drivers, especially those who are obese, ought to be a high priority population for OSA screening.

Automation of underground LHD and truck haulage

This paper reviews the state-of-the-art in the automation of underground mining vehicles and reports on the development of an autonomous navigation system under development through the CMTE with sponsorship arranged by AMIRA. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are discussed. The auto-guidance system being developed overcomes some of the limitations of state-of-the-art prototype æcommercialÆ systems. It can be retrofitted to existing remote controlled vehicles, uses minimum installed infrastructure and is flexible enough for rapid relocation to alternate routes. The navigation techniques use data fusion of two separate sets of sensors combining natural feature recognition, nodal maps and inertial navigation techniques. Collision detection is incorporated and people and other traffic are excluded from the tramming area. This paper describes the work being done by the group with regard to auto-tramming and also outlines the future goals.

Automation of underground truck haulage

This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

Automation of underground truck haulage

This paper reviews the state-of-the-art in the automation of underground truck haulage. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tramming systems currently being commercialised, that follow rail-type guides placed along the back, cannot match the performance, flexibility and reliability of systems based on modern mobile robotic principles. In addition, the lack of collision detection research in the underground environment is highlighted.

A workplace-based Participatory Action Research project to investigate the effectiveness of nutrition and physical activity interventions for truck drivers in six Queensland transport industry workplaces: 2012-2015

The Queensland Transport Industry Workplace Health Intervention project was a Participatory Action Research (PAR) project to investigate the effectiveness of workplace-based nutrition and physical activity health promotion interventions for truck drivers in transport industry workplaces in south-east Queensland. The project was conducted by a research team at the Queensland University of Technology (QUT), and was funded by the Queensland Government under the Healthier.Happier.Workplaces initiative.

Chronic disease risks and use of a smartphone application during a physical activity and dietary intervention in Australian truck drivers

- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.