7,714 research outputs found

    Smart driving assistance systems : designing and evaluating ecological and conventional displays

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    In-vehicle information systems have been shown to increase driver workload and cause distraction; both are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid and scenario complexity has on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Important differences were also highlighted between conventional and ecologically designed smart driving interfaces with respect to subjective workload and peripheral detection

    Smart driving aids and their effects on driving performance and driver distraction

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    In-vehicle information systems have been shown to increase driver workload and cause distraction; both of which are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid, and scenario complexity have on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely effect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs

    Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving

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    Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving

    Ecological interface design for eco-driving

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    Eco-driving issues are of high priority at the moment. Research suggests that a change in driving style can reduce fuel consumption and emissions by around 15% in many cases. In response to this need, the UK Foot-LITE project developed an in-car feedback system to encourage safer and greener driving behaviours. In order to balance positive behaviour change against the potential negative effects of distraction, an Ecological Interface Design approach was adopted. The current paper presents an overview of the humancentred design process adopted in the Foot-LITE project, as well as a review of other similar systems on the market

    Improving driver behaviour by design: a cognitive work analysis methodology

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    Within the European Community both the environmental and safety costs of road transport are unacceptably high. ‘Foot-LITE’ is a UK project which aims to encourage drivers to adopt ‘greener’ and safer driving practices, with real-time and retrospective feedback being given both in-vehicle and off-line. This paper describes the early concept development of Foot-LITE, for which a Cognitive Work Analysis (CWA) was conducted. In this paper, we present the results of the first phase of CWA – the Work Domain Analysis, as well as some concept interface designs based on the WDA to illustrate its application. In summary, the CWA establishes a common framework for the project, and will ultimately contribute to the design of the in-vehicle interfac

    Landau Level Collapse in Gated Graphene Structures

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    We describe a new regime of magnetotransport in two dimensional electron systems in the presence of a narrow potential barrier imposed by external gates. In such systems, the Landau level states, confined to the barrier region in strong magnetic fields, undergo a deconfinement transition as the field is lowered. We present transport measurements showing Shubnikov-de Haas (SdH) oscillations which, in the unipolar regime, abruptly disappear when the strength of the magnetic field is reduced below a certain critical value. This behavior is explained by a semiclassical analysis of the transformation of closed cyclotron orbits into open, deconfined trajectories. Comparison to SdH-type resonances in the local density of states is presented.Comment: 4 pages, 2 figure

    Improving driver behaviour by design : a cognitive work analysis methodology

    Get PDF
    Within the European Community both the environmental and safety costs of road transport are unacceptably high. ‘Foot-LITE’ is a UK project which aims to encourage drivers to adopt ‘greener’ and safer driving practices, with real-time and retrospective feedback being given both in-vehicle and off-line. This paper describes the early concept development of Foot-LITE, for which a Cognitive Work Analysis (CWA) was conducted. In this paper, we present the results of the first phase of CWA – the Work Domain Analysis, as well as some concept interface designs based on the WDA to illustrate its application. In summary, the CWA establishes a common framework for the project, and will ultimately contribute to the design of the in-vehicle interface

    Performance and loads data from a hover test of a 0.658-scale V-22 rotor and wing

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    A hover test of a 0.658-scale model of a V-22 rotor and wing was conducted at the Outdoor Aerodynamic Research Facility at Ames Research Center. The primary objectives of the test were to obtain accurate measurements of the hover performance of the rotor system, and to measure the aerodynamic interactions between the rotor and wing. Data were acquired for rotor tip Mach numbers ranging from 0.1 to 0.73. This report presents data on rotor performance, rotor-wake downwash velocities, rotor system loads, wing forces and moments, and wing surface pressures

    The impact of smart driving aids on driving performance and driver distraction

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    In-vehicle information systems (IVIS) have been shown to increase driver workload and cause distraction, both of which are causal factors for accidents. This simulator study evaluates the impact that two prototype ergonomic designs for a smart driving aid have on workload, distraction and driving performance. Scenario complexity was also manipulated as an independent variable. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while also having the positive effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs. The findings are relevant to the development and implementation of smart driving interface designs in the future

    Bayesian multiscale deconvolution applied to gamma-ray spectroscopy

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    A common task in gamma-ray astronomy is to extract spectral information, such as model constraints and incident photon spectrum estimates, given the measured energy deposited in a detector and the detector response. This is the classic problem of spectral “deconvolution” or spectral inversion. The methods of forward folding (i.e., parameter fitting) and maximum entropy “deconvolution” (i.e., estimating independent input photon rates for each individual energy bin) have been used successfully for gamma-ray solar flares (e.g., Rank, 1997; Share and Murphy, 1995). These methods have worked well under certain conditions but there are situations were they don’t apply. These are: 1) when no reasonable model (e.g., fewer parameters than data bins) is yet known, for forward folding; 2) when one expects a mixture of broad and narrow features (e.g., solar flares), for the maximum entropy method; and 3) low count rates and low signal-to-noise, for both. Low count rates are a problem because these methods (as they have been implemented) assume Gaussian statistics but Poisson are applicable. Background subtraction techniques often lead to negative count rates. For Poisson data the Maximum Likelihood Estimator (MLE) with a Poisson likelihood is appropriate. Without a regularization term, trying to estimate the “true” individual input photon rates per bin can be an ill-posed problem, even without including both broad and narrow features in the spectrum (i.e., amultiscale approach). One way to implement this regularization is through the use of a suitable Bayesian prior. Nowak and Kolaczyk (1999) have developed a fast, robust, technique using a Bayesian multiscale framework that addresses these problems with added algorithmic advantages. We outline this new approach and demonstrate its use with time resolved solar flare gamma-ray spectroscopy
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