998 resultados para Traffic


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Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.

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The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.

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Properly designed decision support environments encourage proactive and objective decision making. The work presented in this paper inquires into developing a decision support environment and a tool to facilitate objective decision making in dealing with road traffic noise. The decision support methodology incorporates traffic amelioration strategies both within and outside the road reserve. The project is funded by the CRC for Construction Innovation and conducted jointly by the RMIT University and the Queensland Department of Main Roads (MR) in collaboration with the Queensland Department of Public Works, Arup Pty Ltd., and the Queensland University of Technology. In this paper, the proposed decision support framework is presented in the way of a flowchart which enabled the development of the decision support tool (DST). The underpinning concept is to establish and retain an information warehouse for each critical road segment (noise corridor) for a given planning horizon. It is understood that, in current practice, some components of the approach described are already in place but not fully integrated and supported. It provides an integrated user-friendly interface between traffic noise modeling software, noise management criteria and cost databases.

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Community awareness and the perception on the traffic noise related health impacts have increased significantly over the last decade resulting in a large volume of public inquiries flowing to Road Authorities for planning advice. Traffic noise management in the urban environment is therefore becoming a “social obligation”, essentially due to noise related health concerns. Although various aspects of urban noise pollution and mitigation have been researched independently, an integrated approach by stakeholders has not been attempted. Although the current treatment and mitigation strategies are predominantly handled by the Road Agencies, a concerted effort by all stakeholders is becoming mandatory for effective and tangible outcomes in the future. A research project is underway a RMIT University, Australia, led by the second author to consider the use of “hedonic pricing” for alternative noise amelioration treatments within the road reserve and outside the road reserve. The project aims to foster a full range noise abatement strategy encompassing source, path and noise receiver. The benefit of such a study would be to mitigate the problem where it is most effective and would defuse traditional “authority” boundaries to produce the optimum outcome. The project is conducted in collaboration with the Department of Main Roads Queensland, Australia and funded by the CRC for Construction Innovation. As part of this study, a comprehensive literature search is currently underway to investigate the advancements in community health research, related to environmental noise pollution, and the advancements in technical and engineering research in mitigating the issue. This paper presents the outcomes of this work outlining state of the art, national and international good practices and gap analysis to identify major anomalies and developments.

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We assess the increase in particle number emissions from motor vehicles driving at steady speed when forced to stop and accelerate from rest. Considering the example of a signalized pedestrian crossing on a two-way single-lane urban road, we use a complex line source method to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses and show that the total emissions during a red light is significantly higher than during the time when the light remains green. Replacing two cars with one bus increased the emissions by over an order of magnitude. Considering these large differences, we conclude that the importance attached to particle number emissions in traffic management policies be reassessed in the future.

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Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

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Traffic congestion is an increasing problem with high costs in financial, social and personal terms. These costs include psychological and physiological stress, aggressivity and fatigue caused by lengthy delays, and increased likelihood of road crashes. Reliable and accurate traffic information is essential for the development of traffic control and management strategies. Traffic information is mostly gathered from in-road vehicle detectors such as induction loops. Traffic Message Chanel (TMC) service is popular service which wirelessly send traffic information to drivers. Traffic probes have been used in many cities to increase traffic information accuracy. A simulation to estimate the number of probe vehicles required to increase the accuracy of traffic information in Brisbane is proposed. A meso level traffic simulator has been developed to facilitate the identification of the optimal number of probe vehicles required to achieve an acceptable level of traffic reporting accuracy. Our approach to determine the optimal number of probe vehicles required to meet quality of service requirements, is to simulate runs with varying numbers of traffic probes. The simulated traffic represents Brisbane’s typical morning traffic. The road maps used in simulation are Brisbane’s TMC maps complete with speed limits and traffic lights. Experimental results show that that the optimal number of probe vehicles required for providing a useful supplement to TMC (induction loop) data lies between 0.5% and 2.5% of vehicles on the road. With less probes than 0.25%, little additional information is provided, while for more probes than 5%, there is only a negligible affect on accuracy for increasingly many probes on the road. Our findings are consistent with on-going research work on traffic probes, and show the effectiveness of using probe vehicles to supplement induction loops for accurate and timely traffic information.

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Purpose: To determine (a) the effect of different sunglass tint colorations on traffic signal detection and recognition for color normal and color deficient observers, and (b) the adequacy of coloration requirements in current sunglass standards. Methods: Twenty color-normals and 49 color-deficient males performed a tracking task while wearing sunglasses of different colorations (clear, gray, green, yellow-green, yellow-brown, red-brown). At random intervals, simulated traffic light signals were presented against a white background at 5° to the right or left and observers were instructed to identify signal color (red/yellow/green) by pressing a response button as quickly as possible; response times and response errors were recorded. Results: Signal color and sunglass tint had significant effects on response times and error rates (p < 0.05), with significant between-color group differences and interaction effects. Response times for color deficient people were considerably slower than color normals for both red and yellow signals for all sunglass tints, but for green signals they were only noticeably slower with the green and yellow-green lenses. For most of the color deficient groups, there were recognition errors for yellow signals combined with the yellow-green and green tints. In addition, deuteranopes had problems for red signals combined with red-brown and yellow-brown tints, and protanopes had problems for green signals combined with the green tint and for red signals combined with the red-brown tint. Conclusions: Many sunglass tints currently permitted for drivers and riders cause a measurable decrement in the ability of color deficient observers to detect and recognize traffic signals. In general, combinations of signals and sunglasses of similar colors are of particular concern. This is prima facie evidence of a risk in the use of these tints for driving and cautions against the relaxation of coloration limits in sunglasses beyond those represented in the study.

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Purpose: To evaluate the on-road driving performance of persons with homonymous hemianopia or quadrantanopia in comparison to age-matched controls with normal visual fields. Methods: Participants were 22 hemianopes and eight quadrantanopes (mean age 53 years) and 30 persons with normal visual fields (mean age 52 years) and were either current drivers or aiming to resume driving. All participants completed a battery of tests of vision (ETDRS visual acuity, Pelli-Robson letter contrast sensitivity, Humphrey visual fields), cognitive tests (trials A and B, Mini Mental State Examination, Digit Symbol Substitution) and an on-road driving assessment. Driving performance was assessed in a dual-brake vehicle with safety monitored by a certified driving rehabilitation specialist. Backseat evaluators masked to the clinical characteristics of participants independently rated driving performance along a 22.7 kilometre route involving urban and interstate driving. Results: Seventy-three per cent of the hemianopes, 88 per cent of quadrantanopes and all of the drivers with normal fields received safe driving ratings. Those hemianopic and quadrantanopic drivers rated as unsafe tended to have problems with maintaining appropriate lane position, steering steadiness and gap judgment compared to controls. Unsafe driving was associated with slower visual processing speed and impairments in contrast sensitivity, visual field sensitivity and executive function. Conclusions: Our findings suggest that some drivers with hemianopia or quadrantanopia are capable of safe driving performance, when compared to those of the same age with normal visual fields. This finding has important implications for the assessment of fitness to drive in this population.

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Since 1986 Vietnam has been engaged in the transition from a centrally-controlled economy to a socialist-oriented market economy (the 'doi moi' renovation). The process for global economic integration has been slow given the magnitude of necessary reforms. Consequently technology entrepreneurs often discount Vietnam as a possible commercialization base which means that it is not realising its economic potential as a hub of technology transfer in the Asia-Pacific region. Three significant factors in the current uncertainty are Vietnam's laws on competition, intellectual property and technology transfer. Another problem is the lack of literature on these laws. This article first discusses the conceptual relationship between competition, intellectual property and technology transfer. Hopefully the article will provide some guidance for the technology entrepreneur considering foreign direct investment (FDI) in Vietnam. The bottom line is that these laws still need further reform to bolster entrepreneurial confidence.

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This literature review examines the relationship between traffic lane widths on the safety of road users. It focuses on the impacts of lane widths on motor vehicle behaviour and cyclists’ safety. The review commenced with a search of available databases. Peer reviewed articles and road authority reports were reviewed, as well as current engineering guidelines. Research shows that traffic lane width influences drivers’ perceived difficulty of the task, risk perception and possibly speed choices. Total roadway width, and the presence of onroad cycling facilities, influence cyclists’ positioning on the road. Lateral displacement between bicycles and vehicles is smallest when a marked bicycle facility is present. Reduced motor vehicle speeds can significantly improve the safety of vulnerable road users, particularly pedestrians and cyclists. It has been shown that if road lane widths on urban roads were reduced, through various mechanisms, it could result in a safety environment for all road users.

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Today’s evolving networks are experiencing a large number of different attacks ranging from system break-ins, infection from automatic attack tools such as worms, viruses, trojan horses and denial of service (DoS). One important aspect of such attacks is that they are often indiscriminate and target Internet addresses without regard to whether they are bona fide allocated or not. Due to the absence of any advertised host services the traffic observed on unused IP addresses is by definition unsolicited and likely to be either opportunistic or malicious. The analysis of large repositories of such traffic can be used to extract useful information about both ongoing and new attack patterns and unearth unusual attack behaviors. However, such an analysis is difficult due to the size and nature of the collected traffic on unused address spaces. In this dissertation, we present a network traffic analysis technique which uses traffic collected from unused address spaces and relies on the statistical properties of the collected traffic, in order to accurately and quickly detect new and ongoing network anomalies. Detection of network anomalies is based on the concept that an anomalous activity usually transforms the network parameters in such a way that their statistical properties no longer remain constant, resulting in abrupt changes. In this dissertation, we use sequential analysis techniques to identify changes in the behavior of network traffic targeting unused address spaces to unveil both ongoing and new attack patterns. Specifically, we have developed a dynamic sliding window based non-parametric cumulative sum change detection techniques for identification of changes in network traffic. Furthermore we have introduced dynamic thresholds to detect changes in network traffic behavior and also detect when a particular change has ended. Experimental results are presented that demonstrate the operational effectiveness and efficiency of the proposed approach, using both synthetically generated datasets and real network traces collected from a dedicated block of unused IP addresses.