994 resultados para ELECTRICAL TRANSPORT


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Unlicensed driving is a serious problem in many countries, despite ongoing improvements in traffic law enforcement practices and technology. Unlike alcohol impairment and speeding, unlicensed driving does not play a direct causative role in road crashes. However it represents a major problem for road safety in two respects. Firstly, it undermines the effectiveness of driver licensing systems by preventing the allocation of demerit points and reducing the impact of licence loss (Watson, 2004b). Secondly, there is a growing body of evidence linking unlicensed driving to a cluster of high-risk behaviours including drink driving, speeding, failure to wear seat belts and motorcycle use (Griffin & DeLaZerda, 2000; Harrison, 1997; Watson, 1997, 2004b). Consistent with this, utilising the quasi-induced exposure method, Watson (2004a) estimated that in Queensland, unlicensed drivers were almost three times more likely to be involved in a reported crash than licensed drivers.

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Unlicensed driving remains a serious problem for road safety, despite ongoing improvements in traffic law enforcement practices and technology. This report examines de-identified traffic infringement and sanction histories for drivers in Queensland who had lost their licence between 1st January 2003 and 31st December 2008. A total of 546,117 Queensland drivers were identified. Key areas discussed include the prevalence of unlicensed driving and the extent to which particular offences were detected amongst drivers with a licence sanction or disqualified licence.

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There is a lack of definitive evidence available relating to the extent and nature of unlicensed driving. Analysis of the crash involvement of unlicensed drivers provides an opportunity to better understand the behaviours of this group. This paper reviews the available literature relating to crash involvement patterns of unlicensed drivers. Key areas discussed include the prevalence of unlicensed driving as indicated by studies of crashes involving this group and associations between unlicensed driving and higher levels of risk-taking on the road. This paper also notes differences found in the characteristics and on-road behaviour of unlicensed drivers and the degree to which these factors, in particular alcohol and drug misuse, may influence crash involvement patterns. Drawing on Australian and international studies, this paper consolidates the available research evidence and identifies gaps in current knowledge relating to crash involvement patterns of unlicensed drivers.

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Unlicensed driving remains a serious problem for road safety, despite ongoing improvements in traffic law enforcement practices and technology. While it does not play a direct causative role in road crashes, unlicensed driving undermines the integrity of the driver licensing system and is associated with a range of high-risk behaviours. The Queensland Transport and Main Roads (TMR) commissioned a program of research with separate components relating to different aspects of unlicensed driving. Drawing on Australian and international studies, the Unlicensed and Unregistered Vehicle (UUV) project explores the nature of unlicensed driving in Queensland, consolidates the available research evidence and identifies gaps in current knowledge relating to the driving behaviours of unlicensed drivers.

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There is a current lack of understanding regarding the use of unregistered vehicles on public roads and road-related areas, and the links between the driving of unregistered vehicles and a range of dangerous driving behaviours. This report documents the findings of data analysis conducted to investigate the links between unlicensed driving and the driving of unregistered vehicles, and is an important initial undertaking into understanding these behaviours. This report examines de-identified data from two sources: crash data; and offence data. The data was extracted from the Queensland Department of Transport and Main Roads (TMR) databases and covered the period from 2003 to 2008.

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Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safety. New types of Intelligent Transport System (ITS) interventions are now emerging due to the availability and the affordability of technology. These interventions target both actively and passively protected railway level crossings and attempt to address drivers’ errors at railway crossings, which are mainly a failure to detect the crossing or the train and misjudgement of the train approach speed and distance. This study aims to assess the effectiveness of three emerging ITS that the rail industry considers implementing in Australia: a visual in-vehicle ITS, an audio in-vehicle ITS, as well as an on-road flashing beacons intervention. The evaluation was conducted on an advanced driving simulator with 20 participants per trialled technology, each participant driving once without any technology and once with one of the ITS interventions. Every participant drove through a range of active and passive crossings with and without trains approaching. Their speed approach of the crossing, head movements and stopping compliance were measured. Results showed that driver behaviour was changed with the three ITS interventions at passive crossings, while limited effects were found at active crossings, even with reduced visibility. The on-road intervention trialled was unsuccessful in improving driver behaviour; the audio and visual ITS improved driver behaviour when a train was approaching. A trend toward worsening driver behaviour with the visual ITS was observed when no trains were approaching. This trend was not observed for the audio ITS intervention, which appears to be the ITS intervention with the highest potential for improving safety at passive crossings.

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The expectation to integrate sustainability aspects (social, environmental, and economic success) into the design, delivery, and operation of infrastructure assets is growing rapidly and globally. There are now several tools and frameworks available to benchmark and measure sustainable performance of infrastructure projects and assets. This paper briefly describes the infrastructure sustainability (IS) rating tool developed by the Australian Green Infrastructure Council (AGIC) that was launched in February 2012. This tool evaluates sustainability initiatives and potential environmental, social, and economic impacts of infrastructure projects and assets. The rating tool provides the following benefits to industry: a common national language for sustainability; a vehicle for consistent application and evaluation of sustainability in tendering processes; assists in scoping whole-of-life sustainability risks, enabling smarter solutions that reduce risks and costs; fosters resource efficiency and waste reduction, reducing costs; fosters innovation and continuous improvement in sustainability outcomes; and builds an organization’s credentials and reputation in its approach to sustainability. The infrastructure types covered by this tool include transport, energy, water, and communication. The key themes of sustainability evaluation will be briefly presented in this paper, and they include management and governance; use of resources; emissions, pollution, and waste; ecology; people and place; and innovation.

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For future planetary robot missions, multi-robot-systems can be considered as a suitable platform to perform space mission faster and more reliable. In heterogeneous robot teams, each robot can have different abilities and sensor equipment. In this paper we describe a lunar demonstration scenario where a team of mobile robots explores an unknown area and identifies a set of objects belonging to a lunar infrastructure. Our robot team consists of two exploring scout robots and a mobile manipulator. The mission goal is to locate the objects within a certain area, to identify the objects, and to transport the objects to a base station. The robots have a different sensor setup and different capabilities. In order to classify parts of the lunar infrastructure, the robots have to share the knowledge about the objects. Based on the different sensing capabilities, several information modalities have to be shared and combined by the robots. In this work we propose an approach using spatial features and a fuzzy logic based reasoning for distributed object classification.

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In contrast to single robotic agent, multi-robot systems are highly dependent on reliable communication. Robots have to synchronize tasks or to share poses and sensor readings with other agents, especially for co-operative mapping task where local sensor readings are incorporated into a global map. The drawback of existing communication frameworks is that most are based on a central component which has to be constantly within reach. Additionally, they do not prevent data loss between robots if a failure occurs in the communication link. During a distributed mapping task, loss of data is critical because it will corrupt the global map. In this work, we propose a cloud-based publish/subscribe mechanism which enables reliable communication between agents during a cooperative mission using the Data Distribution Service (DDS) as a transport layer. The usability of our approach is verified by several experiments taking into account complete temporary communication loss.

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Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.

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This work addresses fundamental issues in the mathematical modelling of the diffusive motion of particles in biological and physiological settings. New mathematical results are proved and implemented in computer models for the colonisation of the embryonic gut by neural cells and the propagation of electrical waves in the heart, offering new insights into the relationships between structure and function. In particular, the thesis focuses on the use of non-local differential operators of non-integer order to capture the main features of diffusion processes occurring in complex spatial structures characterised by high levels of heterogeneity.

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The Air Pollution Model and Chemical Transport Model (TAPM-CTM) framework has been tested and applied originally in Sydney to quantify particle and gaseous concentration (Cope et al, 2014). However, the model performance had not been tested in the south-eastern Queensland region (SEQR), Australia.

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To deliver tangible sustainability outcomes, the infrastructure sector of the construction industry needs to build capacities for the creation, application and management of ever increasing knowledge. This paper intends to establish the importance and key issues of promoting sustainability through knowledge management (KM). It presents a new conceptual framework for managing sustainability knowledge to raise the awareness and direct future research in the field of transport infrastructure, one of the fast growing sectors in Australia. A holistic KM approach is adopted in this research to consider the potential to “deliver the right information to the right person at the right time” in the context of sustainable development of infrastructure. A questionnaire survey among practitioners across the nation confirmed the necessity and identified priority issues of managing knowledge for sustainability. During infrastructure development, KM can help build much needed industry consensus, develop capacity, communicate decisions, and promote specific measures for the pursuit of sustainability. Six essential elements of the KM approach and their priority issues informed the establishment of a conceptual KM framework. The transport infrastructure sector has come to realise that development must not come at the expense of environmental and social objectives. In practice however, it is facing extensive challenges to deliver what has been promised in the sustainability agenda. This research demonstrates the importance of managing sustainability knowledge, integration of various stakeholders, facilitation of plans and actions and delivery of tangible benefits in real projects, as a positive step towards meeting these challenges.

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Electrical impedance tomography is a novel technology capable of quantifying ventilation distribution in the lung in real time during various therapeutic manoeuvres. The technique requires changes to the patient’s position to place the electrical impedance tomography electrodes circumferentially around the thorax. The impact of these position changes on the time taken to stabilise the regional distribution of ventilation determined by electrical impedance tomography is unknown. This study aimed to determine the time taken for the regional distribution of ventilation determined by electrical impedance tomography to stabilise after changing position. Eight healthy, male volunteers were connected to electrical impedance tomography and a pneumotachometer. After 30 minutes stabilisation supine, participants were moved into 60 degrees Fowler’s position and then returned to supine. Thirty minutes was spent in each position. Concurrent readings of ventilation distribution and tidal volumes were taken every five minutes. A mixed regression model with a random intercept was used to compare the positions and changes over time. The anterior-posterior distribution stabilised after ten minutes in Fowler’s position and ten minutes after returning to supine. Left-right stabilisation was achieved after 15 minutes in Fowler’s position and supine. A minimum of 15 minutes of stabilisation should be allowed for spontaneously breathing individuals when assessing ventilation distribution. This time allows stabilisation to occur in the anterior-posterior direction as well as the left-right direction.

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In estuaries and natural water channels, the estimate of velocity and dispersion coefficients is critical to the knowledge of scalar transport and mixing. This estimate is rarely available experimentally at sub-tidal time scale in shallow water channels where high frequency is required to capture its spatio-temporal variation. This study estimates Lagrangian integral scales and autocorrelation curves, which are key parameters for obtaining velocity fluctuations and dispersion coefficients, and their spatio-temporal variability from deployments of Lagrangian drifters sampled at 10 Hz for a 4-hour period. The power spectral densities of the velocities between 0.0001 and 0.8 Hz were well fitted with a slope of 5/3 predicted by Kolmogorov’s similarity hypothesis within the inertial subrange, and were similar to the Eulerian power spectral previously observed within the estuary. The result showed that large velocity fluctuations determine the magnitude of the integral time scale, TL. Overlapping of short segments improved the stability of the estimate of TL by taking advantage of the redundant data included in the autocorrelation function. The integral time scales were about 20 s and varied by up to a factor of 8. These results are essential inputs for spatial binning of velocities, Lagrangian stochastic modelling and single particle analysis of the tidal estuary.