987 resultados para traffic monitoring


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We proposed a connection admission control (CAC) to monitor the traffic in a multi-rate WDM optical network. The CAC searches for the shortest path connecting source and destination nodes, assigns wavelengths with enough bandwidth to serve the requests, supervises the traffic in the most required nodes, and if needed activates a reserved wavelength to release bandwidth according to traffic demand. We used a scale-free network topology, which includes highly connected nodes ( hubs), to enhance the monitoring procedure. Numerical results obtained from computational simulations show improved network performance evaluated in terms of blocking probability.

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This paper presents a novel moving target indicator which is selective with respect to a direction of interest. Preliminary results indicate that the obtained selectivity may have high interest in civil traffic monitoring using single channel SAR data.

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The objective of this project was to promote and facilitate analysis and evaluation of the impacts of road construction activities in Smart Work Zone Deployment Initiative (SWZDI) states. The two primary objectives of this project were to assess urban freeway work-zone impacts through use of remote monitoring devices, such as radar-based traffic sensors, traffic cameras, and traffic signal loop detectors, and evaluate the effectiveness of using these devices for such a purpose. Two high-volume suburban freeway work zones, located on Interstate 35/80 (I-35/I-80) through the Des Moines, Iowa metropolitan area, were evaluated at the request of the Iowa Department of Transportation (DOT).

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"Metric Training For The Highway Industry", HR-376 was designed to produce training materials for the various divisions of the Iowa DOT, local government and the highway construction industry. The project materials were to be used to introduce the highway industry in Iowa to metric measurements in their daily activities. Five modules were developed and used in training over 1,000 DOT, county, city, consultant and contractor staff in the use of metric measurements. The training modules developed deal with the planning through operation areas of highway transportation. The materials and selection of modules were developed with the aid of an advisory personnel from the highway industry. Each module is design as a four hour block of instruction and a stand along module for specific types of personnel. Each module is subdivided into four chapters with chapter one and four covering general topics common to all subjects. Chapters two and three are aimed at hands on experience for a specific group and subject. This module includes: Module 4 - Transportation Planning and Traffic Monitoring. Hands on examples of applications of metric measurements in the development of planning reports and traffic data collection are included in this module.

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The Federal Highway Administration mandates that states collect traffic count information at specified intervals to meet the needs of the Highway Performance Monitoring System (HPMS). A manual land use change detection method was employed to determine the effects of land use change on traffic for Black Hawk County, Iowa, from 1994 to 2002. Results from land use change detection could enable redirecting traffic count activities and related data management resources to areas that are experiencing the greatest changes in land use and related traffic volume. Including a manual land use change detection process in the Iowa Department of Transportation’s traffic count program has the potential to improve efficiency by focusing monitoring activities in areas more likely to experience significant increase in traffic.

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The Center for Transportation Research and Education (CTRE) issued a report in July 2003, based on a sample study of the application of remote sensed image land use change detection to the methodology of traffic monitoring in Blackhawk County, Iowa. In summary, the results indicated a strong correlation and a statistically significant regression coefficient between the identification of built-up land use change areas from remote sensed data and corresponding changes in traffic patterns, expressed as vehicle miles traveled (VMT). Based on these results, the Iowa Department of Transportation (Iowa DOT) requested that CTRE expand the study area to five counties in the southwest quadrant of the state. These counties are scheduled for traffic counts in 2004, and the Iowa DOT desired the data to 1) evaluate the current methodology used to place the devices; 2) potentially influence the placement of traffic counting devices in areas of high built-up land use change; and 3) determine if opportunities exist to reduce the frequency and/or density of monitoring activity in lower trafficked rural areas of the state. This project is focused on the practical application of built-up land use change data for placement of traffic count data recording devices in five southwest Iowa counties.

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"August 2010."

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Image processing offers unparalleled potential for traffic monitoring and control. For many years engineers have attempted to perfect the art of automatic data abstraction from sequences of video images. This paper outlines a research project undertaken at Napier University by the authors in the field of image processing for automatic traffic analysis. A software based system implementing TRIP algorithms to count cars and measure vehicle speed has been developed by members of the Transport Engineering Research Unit (TERU) at the University. The TRIP algorithm has been ported and evaluated on an IBM PC platform with a view to hardware implementation of the pre-processing routines required for vehicle detection. Results show that a software based traffic counting system is realisable for single window processing. Due to the high volume of data required to be processed for full frames or multiple lanes, system operations in real time are limited. Therefore specific hardware is required to be designed. The paper outlines a hardware design for implementation of inter-frame and background differencing, background updating and shadow removal techniques. Preliminary results showing the processing time and counting accuracy for the routines implemented in software are presented and a real time hardware pre-processing architecture is described.

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Thesis (Master's)--University of Washington, 2016-06

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This paper begins with a short review of the current state of integrated traffic control. This is followed by a summary of the main components for the Integrated Road Transport Environment (IRTE) and the role of the DRIVE II project HERMES, which aims at providing some of these components. The paper concludes with an outline of some scenarios for integrated traffic control operation.

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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

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This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a learning based approach that uses a set of labeled training data from which an implicit model of an object class -- here, cars -- is learned. Instead of pixel representations that may be noisy and therefore not provide a compact representation for learning, our training images are transformed from pixel space to that of Haar wavelets that respond to local, oriented, multiscale intensity differences. These feature vectors are then used to train a support vector machine classifier. The detection of cars in images is an important step in applications such as traffic monitoring, driver assistance systems, and surveillance, among others. We show several examples of car detection on out-of-sample images and show an ROC curve that highlights the performance of our system.

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Für die Zukunft wird eine Zunahme an Verkehr prognostiziert, gleichzeitig herrscht ein Mangel an Raum und finanziellen Mitteln, um weitere Straßen zu bauen. Daher müssen die vorhandenen Kapazitäten durch eine bessere Verkehrssteuerung sinnvoller genutzt werden, z.B. durch Verkehrsleitsysteme. Dafür werden räumlich aufgelöste, d.h. den Verkehr in seiner flächenhaften Verteilung wiedergebende Daten benötigt, die jedoch fehlen. Bisher konnten Verkehrsdaten nur dort erhoben werden, wo sich örtlich feste Meßeinrichtungen befinden, jedoch können damit die fehlenden Daten nicht erhoben werden. Mit Fernerkundungssystemen ergibt sich die Möglichkeit, diese Daten flächendeckend mit einem Blick von oben zu erfassen. Nach jahrzehntelangen Erfahrungen mit Fernerkundungsmethoden zur Erfassung und Untersuchung der verschiedensten Phänomene auf der Erdoberfläche wird nun diese Methodik im Rahmen eines Pilotprojektes auf den Themenbereich Verkehr angewendet. Seit Ende der 1990er Jahre wurde mit flugzeuggetragenen optischen und Infrarot-Aufnahmesystemen Verkehr beobachtet. Doch bei schlechten Wetterbedingungen und insbesondere bei Bewölkung, sind keine brauchbaren Aufnahmen möglich. Mit einem abbildenden Radarverfahren werden Daten unabhängig von Wetter- und Tageslichtbedingungen oder Bewölkung erhoben. Im Rahmen dieser Arbeit wird untersucht, inwieweit mit Hilfe von flugzeuggetragenem synthetischem Apertur Radar (SAR) Verkehrsdaten aufgenommen, verarbeitet und sinnvoll angewendet werden können. Nicht nur wird die neue Technik der Along-Track Interferometrie (ATI) und die Prozessierung und Verarbeitung der aufgenommenen Verkehrsdaten ausführlich dargelegt, es wird darüberhinaus ein mit dieser Methodik erstellter Datensatz mit einer Verkehrssimulation verglichen und bewertet. Abschließend wird ein Ausblick auf zukünftige Entwicklungen der Radarfernerkundung zur Verkehrsdatenerfassung gegeben.

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En esta tesis doctoral se aborda el desarrollo de técnicas interferométricas para radares de alta resolución en milimétricas. Específicamente, se centra en el desarrollo de técnicas para radares terrestres y en concreto aquellas relacionadas con el seguimiento, clasificación y generación de imágenes de blancos móviles. Aparte del desarrollo teórico y simulación de las diferentes técnicas, uno de los grandes retos de esta tesis es la verificación experimental de las mismas. Para este propósito, se empleará un prototipo de sensor radar interferométrico de muy alta resolución y de ondas milimétricas. El primer capítulo de la tesis realiza una pequeña introducción a las técnicas interferométricas y presenta los objetivos, motivación y organización del presente trabajo. El segundo capítulo hace una pequeña introducción a los radares interferométricos de alta resolución en milimétricas y presenta el sensor radar experimental con el que se llevarán a cabo la validación de las distintas técnicas presentadas. El tercer capítulo recoge las distintas técnicas interferométricas desarrolladas para el seguimiento y cálculo de la altura de blancos móviles en radares de alta resolución. Entre ellas se encuentran: el seguimiento de blancos móviles en sucesión de imágenes ISAR, el cálculo de altura de blancos en imágenes radar bidimensionales distancia-tiempo y su equivalente en imágenes distancia-Doppler. El cuarto capítulo presenta una aplicación de las técnicas interferométricas para la vigilancia de tráfico en carreteras. Se describirán dos configuraciones radar que permiten calcular la velocidad de todos los blancos iluminados por el radar identificando de manera unívoca a los blancos en función del carril por el que circulen. El quinto capítulo presenta técnicas interferométricas aplicadas a la vigilancia en entornos marítimos basadas en la generación de imágenes interferométricas. Para demostrar la viabilidad del uso de estas imágenes se ha desarrollado un simulador de blancos móviles extensos realistas. Abstract This Ph. D thesis deals with the development of radar interferometry techniques for high-resolution millimeter wave sensors. It focuses on the development of techniques for ground-based radars and specifically those related to monitoring, classification and imaging of moving targets. Apart from the theoretical development and simulation, another major technical challenge of this thesis is the experimental verification of the different techniques. For that purpuse, a very high resolution interferometric millimeter wave radar sensor is used. The first chapter of the thesis makes a brief introduction to the interferometric techniques and shows the goals, motivation and organization of this work. The second chapter provides a brief introduction to high resolution interferometric radars in millimeter waves and presents the experimental radar sensor which will be used for the validation of the various techniques presented. The third chapter presents the different interferometric techniques developed for monitoring and obtaining the height of moving targets in high resolution radars. Among them are: tracking of moving targets in a succession of ISAR images, targets height calculation using bidimensional range-time radar images and the equivalente technique using range-Doppler images. The fourth chapter presents the application of interferometric techniques for road traffic monitoring. Two radar configurations are described. Both of them are able to obtain the speed for simultaneuslly illuminated targets, and univocally identify each target based on the detected road lane. The fifth chapter presents the application of interferometric techniques to maritime surveillance based on interferometric imaging. To demonstrate the feasibility of the presented techniques a realistic simulator of extended moving targets has been developed.

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In the last decade, multi-sensor data fusion has become a broadly demanded discipline to achieve advanced solutions that can be applied in many real world situations, either civil or military. In Defence,accurate detection of all target objects is fundamental to maintaining situational awareness, to locating threats in the battlefield and to identifying and protecting strategically own forces. Civil applications, such as traffic monitoring, have similar requirements in terms of object detection and reliable identification of incidents in order to ensure safety of road users. Thanks to the appropriate data fusion technique, we can give these systems the power to exploit automatically all relevant information from multiple sources to face for instance mission needs or assess daily supervision operations. This paper focuses on its application to active vehicle monitoring in a particular area of high density traffic, and how it is redirecting the research activities being carried out in the computer vision, signal processing and machine learning fields for improving the effectiveness of detection and tracking in ground surveillance scenarios in general. Specifically, our system proposes fusion of data at a feature level which is extracted from a video camera and a laser scanner. In addition, a stochastic-based tracking which introduces some particle filters into the model to deal with uncertainty due to occlusions and improve the previous detection output is presented in this paper. It has been shown that this computer vision tracker contributes to detect objects even under poor visual information. Finally, in the same way that humans are able to analyze both temporal and spatial relations among items in the scene to associate them a meaning, once the targets objects have been correctly detected and tracked, it is desired that machines can provide a trustworthy description of what is happening in the scene under surveillance. Accomplishing so ambitious task requires a machine learning-based hierarchic architecture able to extract and analyse behaviours at different abstraction levels. A real experimental testbed has been implemented for the evaluation of the proposed modular system. Such scenario is a closed circuit where real traffic situations can be simulated. First results have shown the strength of the proposed system.