732 resultados para off-road vehicles (ORVs)


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Aims: This study determined whether the visibility benefits of positioning retroreflective strips in biological motion configurations were evident at real world road worker sites. ---------- Methods: 20 visually normal drivers (M=40.3 years) participated in this study that was conducted at two road work sites (one suburban and one freeway) on two separate nights. At each site, four road workers walked in place wearing one of four different clothing options: a) standard road worker night vest, b) standard night vest plus retroreflective strips on thighs, c) standard night vest plus retroreflective strips on ankles and knees, d) standard night vest plus retroreflective strips on eight moveable joints (full biomotion). Participants seated in stationary vehicles at three different distances (80m, 160m, 240m) rated the relative conspicuity of the four road workers using a series of a standardized visibility and ranking scales. ---------- Results: Adding retroreflective strips in the full biomotion configuration to the standard night vest significantly (p<0.001) enhanced perceptions of road worker visibility compared to the standard vest alone, or in combination with thigh retroreflective markings. These visibility benefits were evident at all distances and at both sites. Retroreflective markings at the ankles and knees also provided visibility benefits compared to the standard vest, however, the full biomotion configuration was significantly better than all of the other configurations. ---------- Conclusions: These data provide the first evidence that the benefits of biomotion retroreflective markings that have been previously demonstrated under laboratory and closed- and open-road conditions are also evident at real work sites.

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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

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In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

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Inter-Vehicular Communications (IVC) are considered a promising technological approach for enhancing transportation safety and improving highway efficiency. Previous theoretical work has demonstrated the benefits of IVC in vehicles strings. Simulations of partially IVC-equipped vehicles strings showed that only a small equipment ratio is sufficient to drastically reduce the number of head on collisions. However, these results are based on the assumptions that IVC exhibit lossless and instantaneous messages transmission. This paper presents the research design of an empirical measurement of a vehicles string, with the goal of highlighting the constraints introduced by the actual characteristics of communication devices. A warning message diffusion system based on IEEE 802.11 wireless technology was developed for an emergency breaking scenario. Preliminary results are presented as well, showing the latencies introduced by using 802.11a and discussing early findings and experimental limitations

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Urban traffic and climate change are two phenomena that have the potential to degrade urban water quality by influencing the build-up and wash-off of pollutants, respectively. However, limited knowledge has made it difficult to establish any link between pollutant buildup and wash-off under such dynamic conditions. In order to safeguard urban water quality, adaptive water quality mitigation measures are required. In this research, pollutant build-up and wash-off have been investigated from a dynamic point of view which incorporated the impacts of changed urban traffic as well as changes in the rainfall characteristics induced by climate change. The study has developed a dynamic object classification system and thereby, conceptualised the study of pollutant build-up and wash-off under future changes in urban traffic and rainfall characteristics. This study has also characterised the buildup and wash-off processes of traffic generated heavy metals, volatile, semi-volatile and non-volatile hydrocarbons under dynamic conditions which enables the development of adaptive mitigation measures for water quality. Additionally, predictive frameworks for the build-up and wash-off of some pollutants have also been developed.

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Aims: This study determined whether the visibility benefits of positioning retroreflective strips in biological motion configurations were evident at real world road worker sites. Methods: 20 visually normal drivers (M=40.3 years) participated in this study that was conducted at two road work sites (one suburban and one freeway) on two separate nights. At each site, four road workers walked in place wearing one of four different clothing options: a) standard road worker night vest, b) standard night vest plus retroreflective strips on thighs, c) standard night vest plus retroreflective strips on ankles and knees, d) standard night vest plus retroreflective strips on eight moveable joints (full biomotion). Participants seated in stationary vehicles at three different distances (80m, 160m, 240m) rated the relative conspicuity of the four road workers using a series of a standardized visibility and ranking scales. Results: Adding retroreflective strips in the full biomotion configuration to the standard night vest significantly (p<0.001) enhanced perceptions of road worker visibility compared to the standard vest alone, or in combination with thigh retroreflective markings. These visibility benefits were evident at all distances and at both sites. Retroreflective markings at the ankles and knees also provided visibility benefits compared to the standard vest, however, the full biomotion configuration was significantly better than all of the other configurations. Conclusions: These data provide the first evidence that the benefits of biomotion retroreflective markings that have been previously demonstrated under laboratory and closed- and open-road conditions are also evident at real work sites.

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Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

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Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

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The National Road Safety Strategy 2011-2020 outlines plans to reduce the burden of road trauma via improvements and interventions relating to safe roads, safe speeds, safe vehicles, and safe people. It also highlights that a key aspect in achieving these goals is the availability of comprehensive data on the issue. The use of data is essential so that more in-depth epidemiologic studies of risk can be conducted as well as to allow effective evaluation of road safety interventions and programs. Before utilising data to evaluate the efficacy of prevention programs it is important for a systematic evaluation of the quality of underlying data sources to be undertaken to ensure any trends which are identified reflect true estimates rather than spurious data effects. However, there has been little scientific work specifically focused on establishing core data quality characteristics pertinent to the road safety field and limited work undertaken to develop methods for evaluating data sources according to these core characteristics. There are a variety of data sources in which traffic-related incidents and resulting injuries are recorded, which are collected for a variety of defined purposes. These include police reports, transport safety databases, emergency department data, hospital morbidity data and mortality data to name a few. However, as these data are collected for specific purposes, each of these data sources suffers from some limitations when seeking to gain a complete picture of the problem. Limitations of current data sources include: delays in data being available, lack of accurate and/or specific location information, and an underreporting of crashes involving particular road user groups such as cyclists. This paper proposes core data quality characteristics that could be used to systematically assess road crash data sources to provide a standardised approach for evaluating data quality in the road safety field. The potential for data linkage to qualitatively and quantitatively improve the quality and comprehensiveness of road crash data is also discussed.

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Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.

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Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

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Understanding the impacts of traffic and climate change on water quality helps decision makers to develop better policy and plans for dealing with unsustainable urban and transport development. This chapter presents detailed methodologies developed for sample collection and testing for heavy metals and total petroleum hydrocarbons, as part of a research study to investigate the impacts of climate change and changes to urban traffic characteristics on pollutant build-up and wash-off from urban road surfaces. Cadmium, chromium, nickel, copper, lead, iron, aluminium, manganese and zinc were the target heavy metals, and selected gasoline and diesel range organics were the target total petroleum hydrocarbons for this study. The study sites were selected to encompass the urban traffic characteristics of the Gold Coast region, Australia. An improved sample collection method referred to as ‘the wet and dry vacuum system’ for the pollutant build-up, and an effective wash-off plan to incorporate predicted changes to rainfall characteristics due to climate change, were implemented. The novel approach to sample collection for pollutant build-up helped to maintain the integrity of collection efficiency. The wash-off plan helped to incorporate the predicted impacts of climate change in the Gold Coast region. The robust experimental methods developed will help in field sample collection and chemical testing of different stormwater pollutants in build-up and wash-off.

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Road traffic crashes have emerged as a major health problem around the world. Road crash fatalities and injuries have been reduced significantly in developed countries, but they are still an issue in low and middle-income countries. The World Health Organization (WHO, 2009) estimates that the death toll from road crashes in low- and middle-income nations is more than 1 million people per year, or about 90% of the global road toll, even though these countries only account for 48% of the world's vehicles. Furthermore, it is estimated that approximately 265,000 people die every year in road crashes in South Asian countries and Pakistan stands out with 41,494 approximately deaths per year. Pakistan has the highest rate of fatalities per 100,000 population in the region and its road crash fatality rate of 25.3 per 100,000 population is more than three times that of Australia's. High numbers of road crashes not only cause pain and suffering to the population at large, but are also a serious drain on the country's economy, which Pakistan can ill-afford. Most studies identify human factors as the main set of contributing factors to road crashes, well ahead of road environment and vehicle factors. In developing countries especially, attention and resources are required in order to improve things such as vehicle roadworthiness and poor road infrastructure. However, attention to human factors is also critical. Human factors which contribute to crashes include high risk behaviours like speeding and drink driving, and neglect of protective behaviours such as helmet wearing and seat belt wearing. Much research has been devoted to the attitudes, beliefs and perceptions which contribute to these behaviours and omissions, in order to develop interventions aimed at increasing safer road use behaviours and thereby reducing crashes. However, less progress has been made in addressing human factors contributing to crashes in developing countries as compared to the many improvements in road environments and vehicle standards, and this is especially true of fatalistic beliefs and behaviours. This is a significant omission, since in different cultures in developing countries there are strong worldviews in which predestination persists as a central idea, i.e. that one's life (and death) and other events have been mapped out and are predetermined. Fatalism refers to a particular way in which people regard the events that occur in their lives, usually expressed as a belief that an individual does not have personal control over circumstances and that their lives are determined through a divine or powerful external agency (Hazen & Ehiri, 2006). These views are at odds with the dominant themes of modern health promotion movements, and present significant challenges for health advocates who aim to avert road crashes and diminish their consequences. The limited literature on fatalism reveals that it is not a simple concept, with religion, culture, superstition, experience, education and degree of perceived control of one's life all being implicated in accounts of fatalism. One distinction in the literature that seems promising is the distinction between empirical and theological fatalism, although there are areas of uncertainty about how well-defined the distinction between these types of fatalism is. Research into road safety in Pakistan is scarce, as is the case for other South Asian countries. From the review of the literature conducted, it is clear that the descriptions given of the different belief systems in developing countries including Pakistan are not entirely helpful for health promotion purposes and that further research is warranted on the influence of fatalism, superstition and other related beliefs in road safety. Based on the information available, a conceptual framework is developed as a means of structuring and focusing the research and analysis. The framework is focused on the influence of fatalism, superstition, religion and culture on beliefs about crashes and road user behaviour. Accordingly, this research aims to provide an understanding of the operation of fatalism and related beliefs in Pakistan to assist in the development and implementation of effective and culturally appropriate interventions. The research examines the influence of fatalism, superstition, religious and cultural beliefs on risky road use in Pakistan and is guided by three research questions: 1. What are the perceptions of road crash causation in Pakistan, in particular the role of fatalism, superstition, religious and cultural beliefs? 2. How does fatalism, superstition, and religious and cultural beliefs influence road user behaviour in Pakistan? 3. Do fatalism, superstition, and religious and cultural beliefs work as obstacles to road safety interventions in Pakistan? To address these questions, a qualitative research methodology was developed. The research focused on gathering data through individual in-depth interviewing using a semi-structured interview format. A sample of 30 participants was interviewed in Pakistan in the cities of Lahore, Rawalpindi and Islamabad. The participants included policy makers (with responsibility for traffic law), experienced police officers, religious orators, professional drivers (truck, bus and taxi) and general drivers selected through a combination of purposive, criterion and snowball sampling. The transcripts were translated from Urdu and analysed using a thematic analysis approach guided by the conceptual framework. The findings were divided into four areas: attribution of crash causation to fatalism; attribution of road crashes to beliefs about superstition and malicious acts; beliefs about road crash causation linked to popular concepts of religion; and implications for behaviour, safety and enforcement. Fatalism was almost universally evident, and expressed in a number of ways. Fate was used to rationalise fatal crashes using the argument that the people killed were destined to die that day, one way or another. Related to this was the sense of either not being fully in control of the vehicle, or not needing to take safety precautions, because crashes were predestined anyway. A variety of superstitious-based crash attributions and coping methods to deal with road crashes were also found, such as belief in the role of the evil eye in contributing to road crashes and the use of black magic by rivals or enemies as a crash cause. There were also beliefs related to popular conceptions of religion, such as the role of crashes as a test of life or a source of martyrdom. However, superstitions did not appear to be an alternative to religious beliefs. Fate appeared as the 'default attribution' for a crash when all other explanations failed to account for the incident. This pervasive belief was utilised to justify risky road use behaviour and to resist messages about preventive measures. There was a strong religious underpinning to the statement of fatalistic beliefs (this reflects popular conceptions of Islam rather than scholarly interpretations), but also an overlap with superstitious and other culturally and religious-based beliefs which have longer-standing roots in Pakistani culture. A particular issue which is explored in more detail is the way in which these beliefs and their interpretation within Pakistani society contributed to poor police reporting of crashes. The pervasive nature of fatalistic beliefs in Pakistan affects road user behaviour by supporting continued risk taking behaviour on the road, and by interfering with public health messages about behaviours which would reduce the risk of traffic crashes. The widespread influence of these beliefs on the ways that people respond to traffic crashes and the death of family members contribute to low crash reporting rates and to a system which appears difficult to change. Fate also appeared to be a major contributing factor to non-reporting of road crashes. There also appeared to be a relationship between police enforcement and (lack of) awareness of road rules. It also appears likely that beliefs can influence police work, especially in the case of road crash investigation and the development of strategies. It is anticipated that the findings could be used as a blueprint for the design of interventions aimed at influencing broad-spectrum health attitudes and practices among the communities where fatalism is prevalent. The findings have also identified aspects of beliefs that have complex social implications when designing and piloting driver intervention strategies. By understanding attitudes and behaviours related to fatalism, superstition and other related concepts, it should be possible to improve the education of general road users, such that they are less likely to attribute road crashes to chance, fate, or superstition. This study also underscores the understanding of this issue in high echelons of society (e.g., policy makers, senior police officers) as their role is vital in dispelling road users' misconceptions about the risks of road crashes. The promotion of an evidence or scientifically-based approach to road user behaviour and road safety is recommended, along with improved professional education for police and policy makers.

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A range of risk management initiatives have been introduced in organisations in attempt to reduce occupational road incidents. However a discrepancy exists between the initiatives that are frequently implemented in organisations and the initiatives that have demonstrated scientific merit in improving occupational road safety. Given that employees’ beliefs may facilitate or act as a barrier to implementing initiatives, it is important to understand whether initiatives with scientific merit are perceived to be effective by employees. To explore employee perceptions pertaining to occupational road safety initiatives, a questionnaire was administered to 679 employees sourced from four Australian organisations. Participants ranged in age from 18 years to 65 years (M = 42, SD = 11). Participants rated 35 initiatives based on how effective they thought they would be in improving road safety in their organisation. The initiatives perceived by employees to be most effective in managing occupational road risks comprised: making vehicle safety features standard e.g. passenger airbags; practical driver skills training; and investigation of serious vehicle incidents. The initiatives perceived to be least effective in managing occupational road risks comprised: signing a promise card commitment to drive safely; advertising the organisation’s phone number on vehicles for complaints and compliments; and consideration of driving competency in staff selection process. Employee perceptions were analysed at a factor level and at an initiative level. The mean scores for the three extracted factors revealed that employees believed occupational road risks could best be managed by the employer implementing engineering and human resource methods to enhance road safety. Initiatives relating to employer management of identified risk factors were perceived to be more effective than feedback or motivational methods that required employees to accept responsibility for their driving safety. Practitioners can use the findings from this study to make informed decisions about how they select, manage and market occupational safety initiatives.