959 resultados para Denver Air Route Traffic Control Center.


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A traffic control device in the form of a humanoid character robot, doll or dummy is used to warn driver of danger ahead on the road. The device can be used on roads, streets and in other sites where there are moving vehicles. The robotic device informs drivers of impending danger by moving its arms and sounding an acoustic alarm. In this way the robot can simulate a policeman or road flagging operator. The device may also include speed detection and preferably speed indication means. The robot may make decisions based on the detected speed of a vehicle and the limit for the area in operating the arms and sound warning means. The robot may also be equipped with a camera or video. The robot may also be controlled wirelessly.

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This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

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The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

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The Connecticut Poison Control Center (CPCC) at the University of Connecticut Health Center (UCHC) was established in 1957 under Connecticut General Statute 10a- 132. The CPCC’s main responsibility is to provide 24-hour emergency toxicology management consultations for victims of poisoning, and serve as a source for pharmacology and toxicology-related information. The center monitors the epidemiology of human poisoning and provides surveillance for environmental and occupational chemical exposures, drug abuse, and pharmaceutical interactions and adverse effects. The CPCC performs toxicological research, and provides formal toxicology instruction for allied health professionals, as well as professional and consumer poison prevention education. The CPCC is one of 63 nationwide centers certified by the American Association of Poison Control Centers (AAPCC), and the only poison center in the state of Connecticut. The AAPCC establishes standards of care for poisoning and administers the Toxic Exposure Surveillance System (TESS), a national database of poisoning statistics, to which the CPCC is a contributor.

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For the past 49 years, the Connecticut Poison Control Center (CTPCC) based at the University of Connecticut Health Center (UCHC), has managed human exposures and poisonings throughout the state and continues to serve as a toxicologic center of excellence. A human exposure may be defined as contact by skin, eye, mouth or inhalation to any substance: animal, mineral or vegetable, including: bites, commercial products, chemicals, drugs, natural remedies and plants among others. A poisoning is any injury to the body resulting from an exposure. Toxicology is the scientific study of the adverse effects of any substance on the body.

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This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona.

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This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO2 emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes. The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO2 emissions than larger distances. On the environmental side, the distribution of CO2 emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO2 emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO2 emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO2 emissions. Finally, projections for future CO2 emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.

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Texas Department of Transportation, Research and Technology Transfer Office, Austin

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Transportation Department, Office of University Research, Washington, D.C.

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Federal Highway Administration, Office of Implementation, Washington, D.C.

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Federal Highway Administration, Office of Implementation, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Office of Research, Washington, D.C.