Professional truck drivers are highly exposed to fatigue and work related injuries. Truck drivers are common victims of musculoskeletal disorders, frequently suffering from pain symptoms particularly in the neck, shoulder and lower back. This situation is believed to be a contributor to the high absenteeism in this job category. A high percentage of this problem is due to the adoption of an unhealthy driving posture resulting from inappropriate seat design. This incorrect and poor design is owing to the insufficient and obsolete anthropometrical data which has been used for decades for arranging and positioning components in the driver environment. The main objective of the present study was to create and construct a mathematical model which clarifies and predicts the drivers’ comfortable sitting posture and position. It was hypothesized that the length and height characteristics of some body segments as well as the body weight and waist circumference of the driver have a great impact on the selection of a specific sitting posture. The steering wheel positions as well as the pedal/floor locations were hypothesized to be highly correlated to the driver’s selected posture and the corresponding comfort. The effect of the seat position on posture selection and related comfort assessments constituted the other hypothesis of the study which received extra attention. A laboratory experiment on a Scania truck cab mock-up was conducted. The seat track travel along a vertical as well as horizontal forward-backward path was obtained by mounting the seat on the motorized rigid frame which allowed unrestricted vertical and fore-aft travel. The seat cushion angle and backrest angle were adjusted by pivoting the entire seat and backrest around a lateral axis and independently. The pedal components were mounted on a motorized platform, thus allowing unrestricted fore-aft and height travel without any changes in the pedal angles. The steering wheel was mounted on the instrument panel by two independent pneumatic axes which allowed a wide range of adjustments including tilting and moving along the sagittal plane for adjusting the height and distance. The test plan called for 55 international highly experienced heavy truck drivers. The drivers were recruited to span a large range of body weight and stature, in particular to ensure adequate representation of both the extreme as well as the normal group of drivers. The drivers filled in a general information questionnaire before undergoing the anthropometrical measurements and thereafter the test trials. The experiment contained a subset of test conditions with five different trials using random selection sampling procedure. Drivers were asked to adjust the components in a wide range of trajectory according to a written protocol. A sparse set of threedimensional body landmark locations and the corresponding comfort assessments were recorded. As the main part of the result, the mathematical models using multiple regression analyses on selected body landmarks as well as anthropometrical measures were developed which proposed a linear correlation between parameters. The differences between the observed data and the corresponding predicted data using the model were found to be minimal and almost dispensable. Additionally, the drivers preferred to sit in the rearmost position and at a rather high level relative to the rest of the available and adjustable area. Considering the normal adjustable seat area of the cab, only a very small part of the observed Hpoint data lies within this area while a large remaining amount of data lies outside of it. Moreover, the difference between the observation (plotted H-point data) and the neutral H-point was found to be significant. Furthermore, and since some of the data lies almost on the border of the adjustable area, it may indicate a reasonable tendency for even more seat adjustment in the backward direction. A conceptual model consisting of four different parameters was developed and presented in the end. These parameters of the model suggest being as key factors which play a central role on process of decision making regarding the selection of a desirable sitting posture. Any eventual modifications and adjustments for elimination or minimizing discrepancies, biases or obscured factors affecting the quality of the mathematical model would be a case for future study. The investigation of a complete assessment of comfort should be supplemented with an analysis of how many truck drivers are satisfied with the comfort in the end. / QC 20100824

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I have developed time-varying coefficient models for recurrent event data to evaluate the temporal profiles for recurrence rate and covariate effects. There are three major parts in this dissertation. The first two parts propose a mixed Poisson process model with gamma frailties for single type recurrent events. The third part proposes a Bayesian joint model based on multivariate log-normal frailties for multi-type recurrent events. In the first part, I propose an approach based on penalized B-splines to obtain smooth estimation for both time-varying coefficients and the log baseline intensity. An EM algorithm is developed for parameter estimation. One issue with this approach is that the estimating procedure is conditional on smoothing parameters, which have to be selected by cross-validation or optimizing certain performance criterion. The procedure can be computationally demanding with a large number of time-varying coefficients. To achieve objective estimation of smoothing parameters, I propose a mixed-model representation approach for penalized splines. Spline coefficients are treated as random effects and smoothing parameters are to be estimated as variance components. An EM algorithm embedded with penalized quasi-likelihood approximation is developed to estimate the model parameters. The third part proposes a Bayesian joint model with time-varying coefficients for multi-type recurrent events. Bayesian penalized splines are used to estimate time-varying coefficients and the log baseline intensity. One challenge in Bayesian penalized splines is that the smoothness of a spline fit is considerably sensitive to the subjective choice of hyperparameters. I establish a procedure to objectively determine the hyperparameters through a robust prior specification. A Markov chain Monte Carlo procedure based on Metropolis-adjusted Langevin algorithms is developed to sample from the high-dimensional distribution of spline coefficients. The procedure includes a joint sampling scheme to achieve better convergence and mixing properties. Simulation studies in the second and third part have confirmed satisfactory model performance in estimating time-varying coefficients under different curvature and event rate conditions. The models in the second and third part were applied to data from a commercial truck driver naturalistic driving study. The application results reveal that drivers with 7-hours-or-less sleep prior to a shift have a significantly higher intensity after 8 hours of on-duty driving and that their intensity remains higher after taking a break. In addition, the results also show drivers' self-selection on sleep time, total driving hours in a shift, and breaks. These applications provide crucial insight into the impact of sleep time on driving performance for commercial truck drivers and highlights the on-road safety implications of insufficient sleep and breaks while driving. This dissertation provides flexible and robust tools to evaluate the temporal profile of intensity for recurrent events. / PHD / The overall objective of this dissertation is to develop models to evaluate the time-varying profiles for event occurrences and the time-varying effects of risk factors upon event occurrences. There are three major parts in this dissertation. The first two parts are designed for single event type. They are based on approaches such that the whole model is conditional on a certain kind of tuning parameter. The value of this tuning parameter has to be pre-specified by users and is influential to the model results. Instead of pre-specifying the value, I develop an approach to achieve an objective estimate for the optimal value of tuning parameter and obtain model results simultaneously. The third part proposes a model for multi-type events. One challenge is that the model results are considerably sensitive to the subjective choice of hyperparameters. I establish a procedure to objectively determine the hyperparameters. Simulation studies have confirmed satisfactory model performance in estimating the temporal profiles for both event occurrences and effects of risk factors. The models were applied to data from a commercial truck driver naturalistic driving study. The results reveal that drivers with 7-hours-or-less sleep prior to a shift have a significantly higher intensity after 8 hours of on-duty driving and that their driving risk remains higher after taking a break. In addition, the results also show drivers’ self-selection on sleep time, total driving hours in a shift, and breaks. These applications provide crucial insight into the impact of sleep time on driving performance for commercial truck drivers and highlights the on-road safety implications of insufficient sleep and breaks while driving. This dissertation provides flexible and robust tools to evaluate the temporal profile of both event occurrences and effects of risk factors.

Thesis (M. Comm.)--University of South Africa, 2002.

Thesis (M. Comm.)--University of South Africa, 2002.

In the traffic domain it is commonly known that sleepiness is a highlycontributing factor in traffic accidents. Research has shown that sleepinessamong drivers is present in about 16-23 % of all car accidents. In the aviation andrailway industry a method or framework with some shared influences from theHuman Factors approach, called Fatigue Risk Management (FRM) has been usedto investigate how social and organisational factors affect the personnel’s level ofsleepiness. The overall aims of this study are to investigate how truck drivers’experience, fight and counteract sleepiness in their daily work environment. Theresults show that drivers face a wide variety of sleep contributing factors,stemming from both organisational factors and individual behaviour. Possibleways of counteracting truck driver sleepiness, concerning both the individual andthe organisation, are also suggested.

The Internet has become a very powerful tool in improving communication, making it easier, more convenient, and faster to access or exchange information. This project takes advantage of the strengths the Internet provides by improving communication by developing a web site for a transportation company.

The purpose of the present study was to determine the concurrent validity of learning potential and psychomotor ability measures for the prediction of haul truck operator (N=128) performance in an open-pit mine. Specific aims were to determine the nature of the relationship between learning potential and psychomotor ability; whether there are higher order cognitive or psychomotor factors present in the combined use of the TRAM 1 and Vienna Test System measures; and the relative contribution of learning potential and psychomotor ability in the prediction of haul truck operator performance. The validity of learning potential and psychomotor ability measures was partially supported. A positive correlation between general (cognitive) ability (g) and psychomotor ability was reported. Factor analysis provided relatively consistent evidence for a general (cognitive) ability factor (g) underlying performance on all measures. The relative contribution of learning potential and psychomotor ability in the prediction of performance could not be established. / Industrial and Organisational Psychology / M. Com. (Industrial and Organisational Psychology)

The purpose of the present study was to determine the concurrent validity of learning potential and psychomotor ability measures for the prediction of haul truck operator (N=128) performance in an open-pit mine. Specific aims were to determine the nature of the relationship between learning potential and psychomotor ability; whether there are higher order cognitive or psychomotor factors present in the combined use of the TRAM 1 and Vienna Test System measures; and the relative contribution of learning potential and psychomotor ability in the prediction of haul truck operator performance. The validity of learning potential and psychomotor ability measures was partially supported. A positive correlation between general (cognitive) ability (g) and psychomotor ability was reported. Factor analysis provided relatively consistent evidence for a general (cognitive) ability factor (g) underlying performance on all measures. The relative contribution of learning potential and psychomotor ability in the prediction of performance could not be established. / Industrial and Organisational Psychology / M. Com. (Industrial and Organisational Psychology)

La conduite d’un véhicule industriel est une activité professionnelle complexe qui s’exerce dans un environnement dynamique en constante évolution. Elle nécessite un apprentissage spécifique et se situe dans un cadre réglementaire strict, qui relève aussi bien du code du travail que de la réglementation routière. A ces caractéristiques s’ajoutent de fortes contraintes spatio-temporelles qui imposent aux conducteurs le recours à des stratégies opératoires pour répondre à l’objectif principal de leur activité : le respect des délais de livraison dans des conditions optimales de sécurité, de sûreté et de productivité.Cette thèse traite de l'apport de la psychologie cognitive à la conception de systèmes d'assistance à la conduite de véhicules industriels. Les travaux sont destinés à intégrer, dès la conception des nouveaux systèmes, les contraintes du fonctionnement cognitif humain en situation réelle, ainsi que les besoins et attentes des conducteurs, afin que leur soient proposées des solutions technologiques adaptées et utilisables.La partie appliquée illustre deux dimensions majeures de l'activité de conduite d'un camion : la productivité, au travers de la problématique de l'assistance à l'éco-conduite (projet Conduite Economique Assistée, ADEME- RENAULT TRUCKS) ; la sécurité, au travers de la problématique de l'assistance à la détection et à la protection des usagers vulnérables de la route (projet VIVRE2, ANR-PREDIT05-LUTB).D’un point de vue scientifique, la thèse aboutit à la proposition d’un modèle du fonctionnement humain dans les activités finalisées, complété par un modèle adapté à l’activité de conduite d’un véhicule industriel. Les analyses effectuées en situations réelles enrichissent les connaissances, d’une part, sur les stratégies de conduite appliquées à la conduite rationnelle d’un poids lourd en environnement extra-urbain, et, d’autre part, sur les composantes de l’activité des conducteurs qui effectuent des livraisons en milieu urbain. De plus, les travaux effectués dans le cadre du projet VIVRE2 ont permis de préciser les représentations et les comportements à risque des usagers vulnérables vis-à-vis des camions en ville.D’un point de vue applicatif et ergonomique, les travaux sur simulateur dynamique de conduite ont permis l’évaluation d’une interface homme-machine innovante qui pourrait être adaptée à l’éco-conduite, ainsi que la proposition et l’évaluation de systèmes d’assistance pour garantir la sécurité des usagers vulnérables lors des manœuvres à basse vitesse en milieu urbain. / Driving a truck is a complex professional activity that takes place in a dynamic and constant changing environment. It needs a specific learning and it is set in a strict regulated framework including French labour code (Code du travail) as road regulation. Strong spatio-temporal pressure should be added to those characteristics. These constraints entail to drivers the use of operative strategies to achieve the main objective of their activity: respect of delivery time in optimal conditions of safety, security and productivity.This thesis deals with the contribution of cognitive psychology to the design of driving assistance systems for trucks. Works are intended to integrate, from the design of new systems, the demands of human cognitive functioning in real situation and the needs and expectations of drivers so that adapted and usable technological solutions could be proposed to them.Applied part shows two major dimensions of truck driving activity: productivity through the issue of the eco-driving assistance (“Conduite Economique Assistée, ADEME- RENAULT TRUCKS” project) and safety through the issue of the assistance to detection and protection of vulnerable road users (“VIVRE2, ANR-PREDIT05-LUTB” project).From a scientific point of view, the thesis ends with a proposal of a model of human functioning in finalized activities, of which is added an adapted model of the truck driving activity. The analysis performed in real environment enhance knowledge, on the one hand, on the applied driving strategies to the eco-driving of a truck in extra-urban environment and, on the other hand, on the components of the activity of drivers doing deliveries in urban environment. Moreover, works performed in VIVRE2 project allowed to specify representations and risky behaviours of vulnerable users with relation to trucks in town.From an applicative and ergonomic point of view, works on driving dynamic simulator allowed the evaluation of an innovative man-machine interface which could be adapted to eco-driving and the proposal as well as the evaluation of assistance systems to guarantee safety of vulnerable users during low speed manoeuvres in urban environment.