942 resultados para Traffic signs and signals.


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Federal Highway Administration, Baton Rouge, Fla.

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The increasing nationwide interest in intelligent transportation systems (ITS) and the need for more efficient transportation have led to the expanding use of variable message sign (VMS) technology. VMS panels are substantially heavier than flat panel aluminum signs and have a larger depth (dimension parallel to the direction of traffic). The additional weight and depth can have a significant effect on the aerodynamic forces and inertial loads transmitted to the support structure. The wind induced drag forces and the response of VMS structures is not well understood. Minimum design requirements for VMS structures are contained in the American Association of State Highway Transportation Officials Standard Specification for Structural Support for Highway Signs, Luminaires, and Traffic Signals (AASHTO Specification). However the Specification does not take into account the prismatic geometry of VMS and the complex interaction of the applied aerodynamic forces to the support structure. In view of the lack of code guidance and the limited number research performed so far, targeted experimentation and large scale testing was conducted at the Florida International University (FIU) Wall of Wind (WOW) to provide reliable drag coefficients and investigate the aerodynamic instability of VMS. A comprehensive range of VMS geometries was tested in turbulence representative of the high frequency end of the spectrum in a simulated suburban atmospheric boundary layer. The mean normal, lateral and vertical lift force coefficients, in addition to the twisting moment coefficient and eccentricity ratio, were determined using the measured data for each model. Wind tunnel testing confirmed that drag on a prismatic VMS is smaller than the 1.7 suggested value in the current AASHTO Specification (2013). An alternative to the AASHTO Specification code value is presented in the form of a design matrix. Testing and analysis also indicated that vortex shedding oscillations and galloping instability could be significant for VMS signs with a large depth ratio attached to a structure with a low natural frequency. The effect of corner modification was investigated by testing models with chamfered and rounded corners. Results demonstrated an additional decrease in the drag coefficient but a possible Reynolds number dependency for the rounded corner configuration.

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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.

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A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

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Flood-besieged Brisbane residents were forced to watch the monster river consume their homes and livelihoods then see the receding water leave behind a putrid, tar-like sludge. The rains formed by multiple low pressure systems over Central Queensland caused chaos over the Christmas and New Year break for many parts of Queensland.

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Reducing road crashes and associated trauma is a critical focus as the Decade of Action for Road Safety commences. China is one of many rapidly-motorizing nations to experience recent increases in private-vehicle ownership and an associated escalation in novice drivers. Unfortunately, however, China also experiences a high rate of death and injury from road crashes. Several key pieces of legislation have been introduced in recent decades in China to deal with these changes. While managing the legal aspects of road use is important, social influences on driver behaviour may offer additional avenues for promoting safe driving, particularly in a culture where such factors carry high importance. To date, there is limited research on the role of social influence factors on driver behaviour in China, yet we know that Chinese society is strongly based on social rules, customs, and relationships. There is reason to assume therefore, that road use and driving-related issues may also be strongly influenced by social relationships. One previous study that has investigated such issues highlighted the need to consider culturally-specific issues such as interpersonal networks and social hierarchy when examining driver behaviour in China (Xie & Parker, 2002). Those authors suggested that there are some concepts relating to Chinese driving culture that may not necessarily have been identified from research conducted in western contexts and that research conducted in China must be considered in light of such concepts. The current paper reports qualitative research conducted with Beijing drivers to investigate such social influence factors. Findings indicated that family members, friends, and driving instructors appear influential on driver behaviour and that some novice drivers seek additional assistance after obtaining their licence. The finding relating to the influence of driving instructors was not surprising, given the substantial number of new drivers in China. In Beijing, driving instruction is conducted off-road in purpose-specific driving facilities rather than on the road network. Once licensed, it is common for new drivers to have little or no experience driving in complex traffic situations. This learning situation is unlikely to provide all the skills necessary to successfully negotiate crowded city streets and assess the related risk associated with such driving. Therefore, it was not surprising to find that one reported strategy to assist new drivers was to employ the services of an ‘accompanying driver’ to provide ongoing driving instruction once licensed. In more highly motorised countries supervised practice is part of a graduated licensing system where it is compulsory for new drivers to be supervised by a more experienced driver for a requisite period of time before progressing to solo driving. However, as this system is not in place in China, it appears that some drivers seek out and pay for additional support once they commence on-road driving. Additionally, strategies to avoid detection and penalties for inappropriate road use were discussed, many of which involve the use of a third person. These findings indicate potential barriers to implementing effective traffic enforcement and highlight the importance of understanding culturally-specific social factors relating to driver behaviour.

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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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Social harmony can manifest in many ways. In rapidly motorizing countries like China, a growing area of potential disharmony is road use. The increased ability to purchase a car for the first time and a subsequent increase in new drivers has seen several Chinese cities take unprecedented measures to manage congestion. There is a corresponding need to ensure effective traffic law enforcement in promoting a safe environment for all road users. This paper reports qualitative research conducted with Beijing car drivers to investigate perceptions of unsafe road use, penalties for traffic violations, and improvements for the current system. Overall, the findings suggest awareness among drivers of many of the key risk factors. A perceived lack of clarity in how penalties are determined was identified and drivers in-dicated a desire to know how revenue from traffic fines is used. Several suggestions for improving the current system included school/community education about road risks and traffic law. The rise of private car ownership in China may contribute to a more harmonious personal life, but at the same time, may contribute to a decrease in societal harmony. A major challenge for authorities in any country is to promote the idea of a collective responsibility for road safety (traffic harmony), especially to those who perceive that traffic rules do not apply to them. This is a potentially greater challenge for China as it strives to balance harmony on the road and harmony in the broader society.

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For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academies from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.

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Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

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The use of intelligent transport systems is proliferating across the Australian road network, particularly on major freeways. New technology allows a greater range of signs and messages to be displayed to drivers. While there has been a long history of human factors analyses of signage, no evaluation has been conducted on this novel, sometimes dynamic, signage or potential interactions when co-located. The purpose of this driving simulator study was to investigate drivers’ behavioural changes and comprehension resulting from the co-location of Lane Use Management Systems with static signs and (Enhanced) Variable Message Signs on Queensland motorways. A section of motorway was simulated, and nine scenarios were developed which presented a combination of signage cases across levels of driving task complexity. Two higher-risk road user groups were targeted for this research on an advanced driving simulator: older (65+ years, N=21) and younger (18-22 years, N=20) drivers. Changes in sign co-location and task complexity had small effect on driver comprehension of the signs and vehicle dynamics variables, including difference with the posted speed limit, headway, standard deviation of lane keeping and brake jerks. However, increasing the amount of information provided to drivers at a given location (by co-locating several signs) increased participants’ gaze duration on the signs. With co-location of signs and without added task complexity, a single gaze was over 2s for more than half of the population tested for both groups, and up to 6 seconds for some individuals.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

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Context Alcohol-related traffic offences and associated trauma have attracted attention in China in recent years, culminating in changes to national legislation in May 2011. Harsher penalties were introduced, particularly for offences where blood alcohol concentration (BAC) levels above 80mg/100mL are recorded. Deemed to be drunk under the law, this is now a criminal offence attracting penalties including large monetary fines, licence suspension for 5 years and imprisonment. Objective This paper outlines key statistics about alcohol-related road trauma in Zhejiang Province and strategies used to combat drink- and drunk-driving. Key Outcomes Zhejiang Province, in China’s south east, has a population of approximately 54, 426,000; 22.36% hold a driving licence. Rapid motorisation is occurring there. In 2011, 1,383,318 new licences were issued, representing a 16.78% increase from the previous year. In 2012, there were a total of 65,000 police officers throughout the Province, 12,307 of whom (18.9%) were traffic police. Responsibility for conducting alcohol testing is the responsibility of all traffic police. The number of alcohol breath tests conducted per year was not available. However, traffic police are actively enforcing alcohol-related laws. In 2011, 89,228 drivers were charged with drink-driving (DUI;20-80mg/100 mL) and 10,014 with the more serious drunk-driving offence (DWI;>80mg/100mL) (Zhejiang Traffic Management Department, 2012). These numbers decreased from the previous year (221,262 and 26,390 respectively). For all crashes recorded in 2011 (n=20,176), 2% involved alcohol-impaired road users. Information on the role of alcohol in crashes from previous years was not available. Discussion Various strategies are employed to detect alcohol-impaired drivers including: targeting vehicles from hotels/restaurants; using sense of smell to screen drivers for further testing; passive alcohol sensors to test drivers; and blood tests for crash-involved drivers where a fatality occurred. Although resources to promote road safety are limited, various government initiatives promote awareness of the dangers of alcohol-related driving and more are needed in future.