title: Human factors affecting the control and perception of motor vehicle dynamics

authors: Spackman, Kerry

abstract: Vehicle Dynamics Engineers (VDEs) responsible for developing passenger vehicles and Elite Race Drivers were analysed over a 5 year period using telemetry data. Investigations were undertaken in an attempt to identify the most important rate limiting factors for each profession and to develop effective training methods for them. 

In a preliminary investigation it was found that the VDEs were unable to reliably detect certain changes to a vehicle’s dynamic behaviour despite their high confidence that they were doing so. This result led to the main VDE study where the VDEs were assessed using a Rotary vestibular platform, the RAF Basic Attributes tests and telemetry analysis of their performance while they evaluated changes to a vehicle’s dynamic behaviour. It was found that there was no significant relation between either the Attributes scores or vestibular performance and the VDEs’ ability to discriminate changes to the dynamic behaviour of a vehicle, termed their Evaluation performance. 

After the VDE’s baseline Evaluation performance was established, they received individual training to improve both their performance at sensing dynamic motion (Perceptual performance) and their consistency and accuracy of controlling vehicle motion (Control performance). The VDEs were then retested to determine the effect of this training on their Evaluation performance. Whereas before training most VDEs scored in the worst Evaluation performance category, after training most scored in the highest Evaluation performance category. A new mathematical technique for analysing telemetry data was developed which allowed us to separately determine the effects of Perceptual performance and Control performance on Evaluation performance. It was found that improving the VDE’s Perceptual performance accounted for all improvements in their Evaluation performance whereas Control performance was unrelated to their Evaluation performance. This finding led to the development of a new Human Factors training program which will be instituted for all Ford’s professional VDEs from 1996 onward. 

In the Elite race driver study, a mathematical model was developed which allowed us to simulate the effect of altering a driver’s curvature control strategy, which is a key component of a driver’s style, on lap times. It was found that all drivers tested, with the notable exception of 3 times World Formula 1 Champion Jackie Stewart, had inadequate and / or faulty cognitive models for optimising curvature control when compared to our computer simulations. Training the subjects to improve their curvature control model produced substantial objective improvements in performance whereas additional unaided practice produced no improvement. For example a 19 year old N.Z. race driver was trained in one afternoon to lap faster than the current World Touring Car champion using the same vehicle.

text: Human factors affecting the control and perception of motor vehicle dynamics Vehicle Dynamics Engineers (VDEs) responsible for developing passenger vehicles and Elite Race Drivers were analysed over a 5 year period using telemetry data. Investigations were undertaken in an attempt to identify the most important rate limiting factors for each profession and to develop effective training methods for them. 

In a preliminary investigation it was found that the VDEs were unable to reliably detect certain changes to a vehicle’s dynamic behaviour despite their high confidence that they were doing so. This result led to the main VDE study where the VDEs were assessed using a Rotary vestibular platform, the RAF Basic Attributes tests and telemetry analysis of their performance while they evaluated changes to a vehicle’s dynamic behaviour. It was found that there was no significant relation between either the Attributes scores or vestibular performance and the VDEs’ ability to discriminate changes to the dynamic behaviour of a vehicle, termed their Evaluation performance. 

After the VDE’s baseline Evaluation performance was established, they received individual training to improve both their performance at sensing dynamic motion (Perceptual performance) and their consistency and accuracy of controlling vehicle motion (Control performance). The VDEs were then retested to determine the effect of this training on their Evaluation performance. Whereas before training most VDEs scored in the worst Evaluation performance category, after training most scored in the highest Evaluation performance category. A new mathematical technique for analysing telemetry data was developed which allowed us to separately determine the effects of Perceptual performance and Control performance on Evaluation performance. It was found that improving the VDE’s Perceptual performance accounted for all improvements in their Evaluation performance whereas Control performance was unrelated to their Evaluation performance. This finding led to the development of a new Human Factors training program which will be instituted for all Ford’s professional VDEs from 1996 onward. 

In the Elite race driver study, a mathematical model was developed which allowed us to simulate the effect of altering a driver’s curvature control strategy, which is a key component of a driver’s style, on lap times. It was found that all drivers tested, with the notable exception of 3 times World Formula 1 Champion Jackie Stewart, had inadequate and / or faulty cognitive models for optimising curvature control when compared to our computer simulations. Training the subjects to improve their curvature control model produced substantial objective improvements in performance whereas additional unaided practice produced no improvement. For example a 19 year old N.Z. race driver was trained in one afternoon to lap faster than the current World Touring Car champion using the same vehicle.

year: 1996

title: A nested random effects model analysis of child survival in Malawi

authors: Manda, Samuel Osmond Makandi

abstract: This thesis investigates child survival in Malawi using a modified Cox proportional hazards model which includes family and community random effects in addition to the fixed effect of the covariates. The parameters of the model are estimated using the Gibbs sampler, a Bayesian Markov Chain Monte Carlo (MCMC) method. We believe this to be the first time the method has been used for this type of data. The parameters are also estimated using the expectation-maximisation (EM) algorithm, a method that has previously been used to analyse this type of data. Both approaches were implemented in Fortran using the NAG routines.

The child survival data used in this study were collected as part of the 1992 Demographic and Health Survey (DHS) of Malawi. The women respondents were obtained through a two-stage cluster sampling procedure. The respondents were systematically interviewed about biological, social and demographic factors relating to all live births that had occurred during the previous five years. 

The results show that the covariates first birth, birth spacing, breastfeeding duration, maternal age, hospital birth and father’s education are important determinants of infant and early childhood survival in Malawi. The family and community frailty effect variances are modest in magnitude. The study also shows that child mortality varies more considerably across families than over communities after controlling for the observed covariates. Neglecting frailty biases estimates of the observed covariates slightly downwards, although the subsequent substantive findings are not markedly affected. The strength of the family random effect is grossly overestimated when community random frailty is ignored while that of the community random effect shows stability whether family random frailty is controlled or not.

The Gibbs sampler is shown to be an important alternative to the EM algorithm and other existing methods for estimating parameters in a multilevel hazards model. It allows the full Bayesian inference without the need to evaluate high-dimensional integrals. We obtain a random sample from the complete posterior distribution of all the parameters and hyperparameters whose behaviour can be studied over their range rather than only around the mode. The Gibbs sampler is computational intensive, but this fact has decreasing relevance due to the availability of very powerful computing equipment.

text: A nested random effects model analysis of child survival in Malawi This thesis investigates child survival in Malawi using a modified Cox proportional hazards model which includes family and community random effects in addition to the fixed effect of the covariates. The parameters of the model are estimated using the Gibbs sampler, a Bayesian Markov Chain Monte Carlo (MCMC) method. We believe this to be the first time the method has been used for this type of data. The parameters are also estimated using the expectation-maximisation (EM) algorithm, a method that has previously been used to analyse this type of data. Both approaches were implemented in Fortran using the NAG routines.

The child survival data used in this study were collected as part of the 1992 Demographic and Health Survey (DHS) of Malawi. The women respondents were obtained through a two-stage cluster sampling procedure. The respondents were systematically interviewed about biological, social and demographic factors relating to all live births that had occurred during the previous five years. 

The results show that the covariates first birth, birth spacing, breastfeeding duration, maternal age, hospital birth and father’s education are important determinants of infant and early childhood survival in Malawi. The family and community frailty effect variances are modest in magnitude. The study also shows that child mortality varies more considerably across families than over communities after controlling for the observed covariates. Neglecting frailty biases estimates of the observed covariates slightly downwards, although the subsequent substantive findings are not markedly affected. The strength of the family random effect is grossly overestimated when community random frailty is ignored while that of the community random effect shows stability whether family random frailty is controlled or not.

The Gibbs sampler is shown to be an important alternative to the EM algorithm and other existing methods for estimating parameters in a multilevel hazards model. It allows the full Bayesian inference without the need to evaluate high-dimensional integrals. We obtain a random sample from the complete posterior distribution of all the parameters and hyperparameters whose behaviour can be studied over their range rather than only around the mode. The Gibbs sampler is computational intensive, but this fact has decreasing relevance due to the availability of very powerful computing equipment.

year: 1998

title: Early French views of the Waikato and its inhabitants (1840-54)

authors: Jennings, William

abstract: This paper will investigate how the cultural background of these Frenchmen informed their descriptions of Waikato Maori and the Waikato environment. It will use the newly-published ten-volume collected correspondence of the pioneer Marists in the Pacific,the Lettres refues d'Odanie, as its principal source.

text: Early French views of the Waikato and its inhabitants (1840-54) This paper will investigate how the cultural background of these Frenchmen informed their descriptions of Waikato Maori and the Waikato environment. It will use the newly-published ten-volume collected correspondence of the pioneer Marists in the Pacific,the Lettres refues d'Odanie, as its principal source.

year: 2011