634 resultados para Driving simulation


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Determining the condition as well as the remaining life of an insulation system is essential for the reliable operation of large oil-filled power transformers. Frequency-domain spectroscopy (FDS) is one of the diagnostic techniques used to identify the dielectric status of a transformer. Currently, this technique can only be implemented on a de-energized transformer. This paper presents an initial investigation into a novel online monitoring method based on FDS dielectric measurements for transformers. The proposed technique specifically aims to address the real operational constraints of online testing. This is achieved by designing an online testing model extending the basic “extended Debye” linear dielectric model and taking unique noise issues only experienced during online measurements into account via simulations. Approaches to signal denoising and potential problems expected to be encountered during online measurements will also be discussed. Using fixed-frequency sinusoidal excitation waveforms will result in a long measurement times. The use of alternatives such as a chirp has been investigated using simulations. The results presented in the paper predict that reliable measurements should be possible during online testing.

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Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving. This paper presents a theoretical understanding of boredom in the driving context and demonstrates convincing arguments to investigate the role of boredom further. Specifically, this paper calls for the design of innovative technologies and applications that make safe driving more pleasurable and stimulating for young males, e.g., by applying gamification techniques. We propose two design concepts through the following questions: A. Can the simulation of risky driving reduce actual risky driving? B. Can the replacement of risky driving stimuli with alternative stimuli reduce risky driving? We argue that considering these questions in the future design of automotive user-interfaces and personal ubiquitous computing devices could effectively reduce risky driving behaviours among young males.

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A field oriented control (FOC) algorithm is simulated and implemented for use with a permanent magnet synchronous motor (PMSM). Rotor position is sensed using Hall effect switches on the stator because other hardware position sensors attached to the rotor may not be desirable or cost effective for certain applications. This places a limit on the resolution of position sensing – only a few Hall effect switches can be placed. In this simulation, three sensors are used and the position information is obtained at higher resolution by estimating it from the rotor dynamics, as shown in literature previously. This study compares the performance of the method with an incremental encoder using simulations. The FOC algorithm is implemented using Digital Motor Control (DMC) and IQ Texas Instruments libraries from a Simulink toolbox called Embedded Coder, and downloaded into a TI microcontroller (TMS320F28335) known as the Piccolo via Code Composer Studio (CCS).

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This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

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Driver sleepiness is a major contributor to road crashes. The current study sought to examine the association between perceptions of effectiveness of six sleepiness countermeasures and their relationship with self-reports of continuing to drive while sleepy among 309 drivers after controlling for the influence of age, sex, motivation for driving sleepy, and risk perception of sleepy driving. The results demonstrate that the variables of age, sex, motivation, and risk perception were significantly associated with self-reports of continuing to drive while sleepy and only one countermeasure was associated with self-reports of continuing to drive while sleepy. Further, it was found that age differences in self-reports of continuing to drive while sleepy was mediated by participants’ motivation and risk perception. These findings highlight modifiable factors that could be focused on with interventions that seek to modify drivers’ attitudes and behaviours of driving while sleepy.

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Many intervention programs have been designed to decrease the rate of drink driving by altering the behavioural characteristics that may lead a person to drink and drive. However, most programs target high risk and repeat offenders. There is very little research on the feasibility and effectiveness of first offender programs. This project is part of a larger program of research that focuses on first time offenders, in order to reduce the rate of subsequent drink driving which may result in a repeat offence. A number of professional stakeholders were approached and interviewed with a view to capturing and reflecting current drink driving related concerns while developing an intervention in the context of Australian drink driving related legislation. The qualitative interviews involved open ended questioning which led to the themes discussed in the analysis. Included in the interviews were senior representatives from the Magistrates Court, Queensland Transport, Probation & Parole, Queensland Corrective Services, Royal Automobile Club Queensland (RACQ), Intraface Consulting (drug & alcohol EAP), Brisbane Police Prosecution Corps, Queensland Police Service and private practice psychology. Issues such as delivery of interventions, feasibility and cost-effectiveness were discussed, as were potential content and design. It was generally agreed that a tailored online intervention imposed as a sentencing option would be the most effective for first time offenders in terms of cost, ease of delivery and feasibility. The development of an online intervention program for first offenders is widely supported by professional stakeholders.

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This thesis developed a high preforming alternative numerical technique to investigate microscale morphological changes of plant food materials during drying. The technique is based on a novel meshfree method, and is more capable of modeling large deformations of multiphase problem domains, when compared with conventional grid-based numerical modeling techniques. The developed cellular model can effectively replicate dried tissue morphological changes such as shrinkage and cell wall wrinkling, as influenced by moisture reduction and turgor loss.

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This paper reports on a prospective study investigating the prevalence of maternal postpartum fatigue and sleepiness and highlights the potential increased crash risk faced by mothers when driving in the postpartum period. Twenty-four mothers from across Australia completed a sleep and driving diary for seven consecutive days at three time points; when their baby was 6, 12 and 18 weeks old. The results showed that the mothers’ sleep varied within the sample, however on average sleep disruption and lack of sleep consolidation was experienced. A high proportion of the mothers reported fatigue and sleepiness impacting their functioning early in the postpartum period, with sleepiness being more enduring throughout the period. Of concern, a high proportion of driving journeys undertaken by the mothers were during high levels of sleepiness, particularly early in the postpartum period and during late night and early hours of the day. These findings have highlighted the need to educate mothers about the potential increased safety risk of driving during the postpartum period and identified key information that should be conveyed.