An on-road study to investigate fatigue in local/short haul trucking

Virginia Tech Transportation Institute, 3500 Transportation Research Plaza, Blacksburg, VA 24061, USA.
Accident Analysis & Prevention (Impact Factor: 1.87). 04/2003; 35(2):153-60. DOI: 10.1016/S0001-4575(01)00098-7
Source: PubMed


As a precursor to the present research, Hanowski et al. [FHWA Report no. FHWA-MC-98-029. Office of Motor Carriers, Federal Highway Administration, Washington, DC, 1998] conducted a series of focus groups in which local/short haul (L/SH) drivers provided their perspective on safety issues, including fatigue, in their industry. As a follow-up to the Hanowski et al. work, the effort presented here consisted of an on-road field study where in-service L/SH trucks were instrumented with data collection equipment. Two L/SH trucking companies and 42 L/SH drivers participated in this research. The analyses focused on determining if fatigue is an issue in L/SH operations. Of primary interest were critical incidents (near-crashes) where L/SH drivers were judged to be at fault. The results of the analyses indicated that fatigue was present immediately prior to driver involvement in at-fault critical incidents. Though it is difficult to determine with certainty why fatigue was present, the results suggest that drivers' off-hours behavior likely played a significant role in the fatigue experienced on the job. Another key finding of this research is that a small percentage of drivers were responsible for a majority of the critical incidents. This finding suggests that driver selection and monitoring could potentially improve safety in L/SH operations.

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    • "A recent trend in studies of sleepy driving is to carry out large-scale naturalistic data collections with instrumented cars [10]. The advantages with this type of field operational tests is the possibility to study to what extent signs of sleepiness contribute to safety-critical incidents [11], [12]. However, this estimation is depending on the possibility to assess sleepiness in a real life context, if this is possible or not is not clear. "
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    ABSTRACT: The aim of the present study was to explore if observer rated sleepiness (ORS) is a feasible method for quantification of driver sleepiness in field studies. Two measures of ORS were used: (1) one for behavioural signs based on facial expression, body gestures and body movements labelled B-ORS, and (2) one based on driving performance e.g. if swerving and other indicators of impaired driving occurs, labelled D-ORS. A limited number of observers sitting in the back of an experimental vehicle on a motorway about 2 hours repeatedly 3 times per day (before lunch, after lunch, at night) observed 24 participant's sleepiness level with help of the two observer scales. At the same time the participant reported subjective sleepiness (KSS), EOG was recorded (for calculation of blink duration) and several driving measure were taken and synchronized with the reporting. Based on mixed model Anova and correlation analysis the result showed that observer ratings of sleepiness based on drivers' impaired performance and behavioural signs are sensitive to extend the general pattern of time awake, circadian phase and time of driving. The detailed analysis of the subjective sleepiness and ORS showed weak correspondence on an individual level. Only 16% of the changes in KSS were predicted by the observer. The correlation between the observer ratings based on performance (D-ORS) and behavioural signs (B-ORS) are high (r = .588), and the B-ORS shows a moderately strong association (r = .360) with blink duration. Both ORS measures show an association (r>0.45) with KSS, whereas the association with driving performance is weak. The results show that the ORS-method detects the expected general variations in sleepy driving in field studies, however, sudden changes in driver sleepiness on a detailed level as 5 minutes is usually not detected; this holds true both when taking into account driving behaviour or driver behavioural signs.
    PLoS ONE 05/2013; 8(5):e64782. DOI:10.1371/journal.pone.0064782 · 3.23 Impact Factor
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    • "Morbidity risks for truckers respiratory strains such as asthma and reductions in pulmonary function and allergic inflammation (Steenland et al., 1998); psychological distress and psychiatric disorders (I ˙ s¸sever et al., 2002); hypertension, stroke, and ischemic heart morbidity and mortality (Kurosaka et al., 2000); fatal vehicle crashes due to disrupted sleep patterns (Hanowski et al., 2003); substance misuse, risk-laden sexual activity, and gambling (Apostolopoulos et al., 2007); and assaults, robberies, and other forms of violence (Ouellet, 1994). "
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    ABSTRACT: Purpose – The purpose of this paper is to examine how the transportation environment triggers, exacerbates and sustains truckers’ risks for obesity and associated morbidities. Design/methodology/approach – An extensive literature review of PubMed Central and TRANSPORT databases was conducted on truckers’ obesity risks and 120 journal articles were identified for closer evaluation. From these, populations, exposures, and relevant outcomes were evaluated within the framework of the broad transportation environment. Findings – Connections between the transportation environment and truckers’ risks for obesity-associated comorbidities were delineated, and an original conceptual framework was developed to illustrate links between the two. This framework addresses links not only between the transportation environment and trucker obesity risks but also with other health strains – applicable to other transport occupational segments. Moreover, it provides direction for preliminary environmental-scale interventions to curb trucker obesity. The utilization of this framework further underscores the need for: an appraisal of the health parameters of trucking worksites; assessment of truckers’ obesity-risk trajectories, and examination of potential causality between the transportation environment, inactivity and diet-related morbidities; and the development, implementation and evaluation of interventions to mitigate trucker obesity. While there is a geographic emphasis on North America, data and assertions of this paper are applicable to trucking sectors of many industrialized nations. Originality/value – The paper brings to light the influences of the transportation environment on trucker obesity-associated morbidity risks.
    International Journal of Workplace Health Management 06/2012; 5(2):120-138. DOI:10.1108/17538351211239162
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    • "Driver individuality has a unique impact on driving skills in which health and lifestyle issues such as fitness, poor diet, poor sleep habits and disorders have a strong positive effect on the correlation between performance and fatigue (Mabbott and Lloyd, 2005). According to Hanowski et al. (2003), the worst drivers (up to 25 per cent) are responsible for over 85 percent of haul road accidents. Compounding this problem is the fact that many mines have annual turnover rates of 40% necessitating expensive training programs and leading to poor-quality drivers during the training period -quality being measured both in terms of production and safety. "
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    ABSTRACT: Driverless haulage trucks have recently been developed for open pit mines. To predict the benefits of an Autonomous Haulage System (AHS), a deterministic/stochastic model has been created to compare AHS to a manual system by estimating benchmarked Key Performance Indicators (KPIs) such as productivity, safety, breakdown frequencies, maintenance and labor costs, fuel consumption, tire wear, and cycle times. The goal of this paper is to describe the driver/autonomous sub-models that function within a virtual 24/7 open pit mine operating with 9 trucks and 2 shovels to move ore to a crusher and waste rock to a dump.
    Procedia Computer Science 12/2011; 6:118-123. DOI:10.1016/j.procs.2011.08.023
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