237 resultados para motion-based driving simulator


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Objectives The UK Department for Transport recommends taking a break from driving every 2 h. This study investigated: (i) if a 2 h drive time on a monotonous road is appropriate for OSA patients treated with CPAP, compared with healthy age matched controls, (ii) the impact of a night’s sleep restriction (with CPAP) and (iii) what happens if these patients miss one nights’ CPAP treatment. Methods About 19 healthy men aged 52–74 y (m = 66.2 y) and 19 OSA participants aged 50–75 y (m = 64.4 y) drove an interactive car simulator under monotonous motorway conditions for 2 h on two afternoons, in a counterbalanced design; (1) following a normal night’s sleep (8 h). (2) following a restricted night’s sleep (5 h), with normal CPAP use (3) following a night without CPAP treatment. (n = 11) Lane drifting incidents, indicative of falling asleep, were recorded for up to 2 h depending on competence to continue driving. Results Normal sleep: Controls drove for an average of 95.9 min (s.d. 37 min) and treated OSA drivers for 89.6 min (s.d. 29 min) without incident. 63.2% of controls and 42.1% of OSA drivers successfully completed the drive without an incident. Sleep restriction: 47.4% of controls and 26.3% OSA drivers finished without incident. Overall: controls drove for an average of 89.5 min (s.d. 39 min) and treated OSA drivers 65 min (s.d. 42 min) without incident. The effect of condition was significant [F(1.36) = 9.237, P < 0.05, eta2 = 0.204]. Stopping CPAP: 18.2% of drivers successfully completed the drive. Overall, participants drove for an average of 50.1 min (s.d. 38 min) without incident. The effect of condition was significant [F(2) = 8.8, P < 0.05, eta2 = 0.468]. Conclusion 52.6% of all drivers were able to complete a 2 hour drive under monotonous conditions after a full night’s sleep. Sleep restriction significantly affected both control and OSA drivers. We find evidence that treated OSA drivers are more impaired by sleep restriction than healthy control, as they were less able to sustain safely the 2 h drive without incidents. OSA drivers should be aware that non-compliance with CPAP can significantly impair driving performance. It may be appropriate to recommend older drivers take a break from driving every 90 min especially when undertaking a monotonous drive, as was the case here.

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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

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A novel method of matching stiffness and continuous variable damping of an ECAS (electronically controlled air suspension) based on LQG (linear quadratic Gaussian) control was proposed to simultaneously improve the road-friendliness and ride comfort of a two-axle school bus. Taking account of the suspension nonlinearities and target-height-dependent variation in suspension characteristics, a stiffness model of the ECAS mounted on the drive axle of the bus was developed based on thermodynamics and the key parameters were obtained through field tests. By determining the proper range of the target height for the ECAS of the fully-loaded bus based on the design requirements of vehicle body bounce frequency, the control algorithm of the target suspension height (i.e., stiffness) was derived according to driving speed and road roughness. Taking account of the nonlinearities of a continuous variable semi-active damper, the damping force was obtained through the subtraction of the air spring force from the optimum integrated suspension force, which was calculated based on LQG control. Finally, a GA (genetic algorithm)-based matching method between stepped variable damping and stiffness was employed as a benchmark to evaluate the effectiveness of the LQG-based matching method. Simulation results indicate that compared with the GA-based matching method, both dynamic tire force and vehicle body vertical acceleration responses are markedly reduced around the vehicle body bounce frequency employing the LQG-based matching method, with peak values of the dynamic tire force PSD (power spectral density) decreased by 73.6%, 60.8% and 71.9% in the three cases, and corresponding reduction are 71.3%, 59.4% and 68.2% for the vehicle body vertical acceleration. A strong robustness to variation of driving speed and road roughness is also observed for the LQG-based matching method.

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BACKGROUND: The objective of this study was to determine whether it is possible to predict driving safety in individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuro-images that are routinely available in clinical practice. METHODS: Two experienced neuro-ophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which provided information regarding the site and extent of the lesion and made predictions regarding whether they would be safe/unsafe to drive. Driving safety was defined using two independent measures: (1) The potential for safe driving was defined based upon whether the participant was rated as having the potential for safe driving, determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist conducted just prior and (2) state recorded motor vehicle crashes (all crashes and at-fault). Driving safety was independently defined at the time of the study by state recorded motor vehicle crashes (all crashes and at-fault) recorded over the previous 5 years, as well as whether the participant was rated as having the potential for safe driving, determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. RESULTS: The ability to predict driving safety was highly variable regardless of the driving outcome measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuro-ophthalmologists was also only fair (kappa =0.28). CONCLUSIONS: The findings suggest that clinical evaluation of summary reports currently available neuro-images by neuro-ophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions.

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For a decade, embedded driving assistance systems were mainly dedicated to the management of short time events (lane departure, collision avoidance, collision mitigation). Recently a great number of projects have been focused on cooperative embedded devices in order to extend environment perception. Handling an extended perception range is important in order to provide enough information for both path planning and co-pilot algorithms which need to anticipate events. To carry out such applications, simulation has been widely used. Simulation is efficient to estimate the benefits of Cooperative Systems (CS) based on Inter-Vehicular Communications (IVC). This paper presents a new and modular architecture built with the SiVIC simulator and the RTMaps™ multi-sensors prototyping platform. A set of improvements, implemented in SiVIC, are introduced in order to take into account IVC modelling and vehicles’ control. These 2 aspects have been tuned with on-road measurements to improve the realism of the scenarios. The results obtained from a freeway emergency braking scenario are discussed.

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This study examined the prevalence of co-morbid age-related eye disease and symptoms of depression and anxiety in late life, and the relative roles of visual function and disease in explaining symptoms of depression and anxiety. A community-based sample of 662 individuals aged over 70 years was recruited through the electoral roll. Vision was measured using a battery of tests including high and low contrast visual acuity, contrast sensitivity, motion sensitivity, stereoacuity, Useful Field of View, and visual fields. Depression and anxiety symptoms were measured using the Goldberg scales. The prevalence of self-reported eye disease [cataract, glaucoma, or age-related macular degeneration (AMD)] in the sample was 43.4%, with 7.7% reporting more than one form of ocular pathology. Of those with no eye disease, 3.7% had clinically significant depressive symptoms. This rate was 6.7% among cataract patients, 4.3% among those with glaucoma, and 10.5% for AMD. Generalized linear models adjusting for demographics, general health, treatment, and disability examined self-reported eye disease and visual function as correlates of depression and anxiety. Depressive symptoms were associated with cataract only, AMD, comorbid eye diseases and reduced low contrast visual acuity. Anxiety was significantly associated with self-reported cataract, and reduced low contrast visual acuity, motion sensitivity and contrast sensitivity. We found no evidence for elevated rates of depressive or anxiety symptoms associated with self-reported glaucoma. The results support previous findings of high rates of depression and anxiety in cataract and AMD, and in addition show that mood and anxiety are associated with objective measures of visual function independently of self-reported eye disease. The findings have implications for the assessment and treatment of mental health in the context of late-life visual impairment...

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My practice-led research explores and maps workflows for generating experimental creative work involving inertia based motion capture technology. Motion capture has often been used as a way to bridge animation and dance resulting in abstracted visuals outcomes. In early works this process was largely done by rotoscoping, reference footage and mechanical forms of motion capture. With the evolution of technology, optical and inertial forms of motion capture are now more accessible and able to accurately capture a larger range of complex movements. The creative work titled “Contours in Motion” was the first in a series of studies on captured motion data used to generating experimental visual forms that reverberate in space and time. With the source or ‘seed’ comes from using an Xsens MVN - Inertial Motion Capture system to capture spontaneous dance movements, with the visual generation conducted through a customised dynamics simulation. The aim of the creative work was to diverge way from a standard practice of using particle system and/or a simple re-targeting of the motion data to drive a 3d character as a means to produce abstracted visual forms. To facilitate this divergence a virtual dynamic object was tether to a selection of data points from a captured performance. The proprieties of the dynamic object were then adjusted to balance the influences from the human movement data with the influence of computer based randomization. The resulting outcome was a visual form that surpassed simple data visualization to project the intent of the performer’s movements into a visual shape itself. The reported outcomes from this investigation have contributed to a larger study on the use of motion capture in the generative arts, furthering the understanding of and generating theories on practice.

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In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

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Current military conflicts are characterized by the use of the improvised explosive device. Improvements in personal protection, medical care, and evacuation logistics have resulted in increasing numbers of casualties surviving with complex musculoskeletal injuries, often leading to lifelong disability. Thus, there exists an urgent requirement to investigate the mechanism of extremity injury caused by these devices in order to develop mitigation strategies. In addition, the wounds of war are no longer restricted to the battlefield; similar injuries can be witnessed in civilian centers following a terrorist attack. Key to understanding such mechanisms of injury is the ability to deconstruct the complexities of an explosive event into a controlled, laboratory-based environment. In this article, a traumatic injury simulator, designed to recreate in the laboratory the impulse that is transferred to the lower extremity from an anti-vehicle explosion, is presented and characterized experimentally and numerically. Tests with instrumented cadaveric limbs were then conducted to assess the simulator’s ability to interact with the human in two mounting conditions, simulating typical seated and standing vehicle passengers. This experimental device will now allow us to (a) gain comprehensive understanding of the load-transfer mechanisms through the lower limb, (b) characterize the dissipating capacity of mitigation technologies, and (c) assess the bio-fidelity of surrogates.

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Some important issues related to the self-organization in the arrays of nanoparticles on solid surfaces exposed to the low-temperature plasma are analysed and discussed. The available tools for the characterization of the size and position uniformity in nanoarrays are examined. The technique capable of revealing the realistic adsorbed atom and adsorbed radical capture zone pattern based on the surface physics is indicated as the most promising characterization tool. The processes responsible for the self-organization are analysed, the main driving forces of the self-organization are discussed, and possible ways to control the self-organization by controlling the plasma parameters are introduced. A view on the possible ways to further improve the methods of nanoarray characterization and self-organization is presented as well.

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Nanoparticle manipulation by various plasma forces in near-substrate areas of the Integrated Plasma-Aided Nanofabrication Facility (IPANF) is investigated. In the IPANF, high-density plasmas of low-temperature rf glow discharges are sustained. The model near-substrate area includes a variable-length pre-sheath, where a negatively charged nanoparticle is accelerated, and a self-consistent collisionless sheath with a repulsive electrostatic potential. Conditions enabling the nanoparticle to overcome the repulsive barrier and deposit onto the substrate are investigated numerically and experimentally. Under certain conditions the momentum gained by the nanoparticle in the pre-sheath area appears to be sufficient for the driving ion drag force to outbalance the repulsive electrostatic and thermophoretic forces. Numerical results are applied for the explanation of size-selective nanoparticle deposition in the Ar+H2+CH4 plasma-assisted chemical vapor deposition of various carbon nanostructure patterns for electron field emitters and are cross-referenced by the field emission scanning electron microscopy. It is shown that the nanoparticles can be efficiently manipulated by the temperature gradient-controlled thermophoretic force. Experimentally, the temperature gradients in the near-substrate areas are measured in situ by means of the temperature gradient probe and related to the nanofilm fabrication conditions. The results are relevant to plasma-assisted synthesis of numerous nanofilms employing structural incorporation of the plasma-grown nanoparticles, including but not limited to nanofabrication of ordered single-crystalline carbon nanotip arrays for electron field emission applications.

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This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

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Objectives: Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness for driving ability. However, drivers might not appreciate the dangerousness of driving while sleepy and this could translate to their on-road driving behaviours. This study sought to determine drivers’ on-road experiences of sleepiness, their sleep habits, and personal awareness of the signs of sleepiness. Methods: Participants were a random selection of 92 drivers travelling on a major highway in the state of Queensland, Australia, who were stopped by Police as part of routine drink driving operations. Participants completed a brief questionnaire that included: demographic details, awareness and on-road experiences of sleepy driving, and sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness during the last 15 minutes of driving. Results: Participants rating of subjective sleepiness was quite low with 90% reporting at or below 3 on the KSS. Participants were reasonably aware of the signs of sleepiness; with a number of these correlated with on-road experiences. The participants sleep debt correlated with their alertness (r = -.30) and the hours spent driving (r = .38). Conclusions: These results suggest that drivers had moderate or substantial experience of driving when sleepy and many were aware of the signs of sleepiness. As many of the participants reported driving long distances after suboptimal sleep durations, it is possible that their risk perception of the dangerousness of sleepy driving maybe erroneous.

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We consider a discrete agent-based model on a one-dimensional lattice and a two-dimensional square lattice, where each agent is a dimer occupying two sites. Agents move by vacating one occupied site in favor of a nearest-neighbor site and obey either a strict simple exclusion rule or a weaker constraint that permits partial overlaps between dimers. Using indicator variables and careful probability arguments, a discrete-time master equation for these processes is derived systematically within a mean-field approximation. In the continuum limit, nonlinear diffusion equations that describe the average agent occupancy of the dimer population are obtained. In addition, we show that multiple species of interacting subpopulations give rise to advection-diffusion equations. Averaged discrete simulation data compares very well with the solution to the continuum partial differential equation models. Since many cell types are elongated rather than circular, this work offers insight into population-level behavior of collective cellular motion.

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A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.