4 resultados para Managed Lane

em Universidad Politécnica de Madrid


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Speed enforcement on public roadways is an important issue in order to guarantee road security and to reduce the number and seriousness of traffic accidents. Traditionally, this task has been partially solved using radar and/or laser technologies and, more recently, using video-camera based systems. All these systems have significant shortcomings that have yet to be overcome. The main drawback of classical Doppler radar technology is that the velocity measurement fails when several vehicles are in the radars beam. Modern radar systems are able to measure speed and range between vehicle and radar. However, this is not enough to discriminate the lane where the vehicle is driving on. The limitation of several vehicles in the beam is overcome using laser technology. However, laser systems have another important limitation: They cannot measure the speed of several vehicles simultaneously. Novel video-camera systems, based on license plate identification, solve the previous drawbacks, but they have the problem that they can only measure average speed but never top-speed. This paper studies the feasibility of using an interferometric linear frequency modulated continuous wave radar to improve top-speed enforcement on roadways. Two different systems based on down-the-road and across-the-road radar configurations are presented. The main advantage of the proposed solutions is they can simultaneously measure speed, range, and lane of several vehicles, allowing the univocal identification of the offenders. A detailed analysis about the operation and accuracy of these solutions is reported. In addition, the feasibility of the proposed techniques has been demonstrated with simulations and real experiments using a Ka-band interferometric radar developed by our research group.

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A research has been carried out in two-lanehighways in the Madrid Region to propose an alternativemodel for the speed-flowrelationship using regular loop data. The model is different in shape and, in some cases, slopes with respect to the contents of Highway Capacity Manual (HCM). A model is proposed for a mountainous area road, something for which the HCM does not provide explicitly a solution. The problem of a mountain road with high flows to access a popular recreational area is discussed, and some solutions are proposed. Up to 7 one-way sections of two-lanehighways have been selected, aiming at covering a significant number of different characteristics, to verify the proposed method the different classes of highways on which the Manual classifies them. In order to enunciate the model and to verify the basic variables of these types of roads a high number of data have been used. The counts were collected in the same way that the Madrid Region Highway Agency performs their counts. A total of 1.471 hours have been collected, in periods of 5 minutes. The models have been verified by means of specific statistical test (R2, T-Student, Durbin-Watson, ANOVA, etc.) and with the diagnostics of the contrast of assumptions (normality, linearity, homoscedasticity and independence). The model proposed for this type of highways with base conditions, can explain the different behaviors as traffic volumes increase, and follows a polynomial multiple regression model of order 3, S shaped. As secondary results of this research, the levels of service and the capacities of this road have been measured with the 2000 HCM methodology, and the results discussed. © 2011 Published by Elsevier Ltd.

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La demanda de contenidos de vídeo ha aumentado rápidamente en los últimos años como resultado del gran despliegue de la TV sobre IP (IPTV) y la variedad de servicios ofrecidos por los operadores de red. Uno de los servicios que se ha vuelto especialmente atractivo para los clientes es el vídeo bajo demanda (VoD) en tiempo real, ya que ofrece una transmisión (streaming) inmediata de gran variedad de contenidos de vídeo. El precio que los operadores tienen que pagar por este servicio es el aumento del tráfico en las redes, que están cada vez más congestionadas debido a la mayor demanda de contenidos de VoD y al aumento de la calidad de los propios contenidos de vídeo. Así, uno de los principales objetivos de esta tesis es encontrar soluciones que reduzcan el tráfico en el núcleo de la red, manteniendo la calidad del servicio en el nivel adecuado y reduciendo el coste del tráfico. La tesis propone un sistema jerárquico de servidores de streaming en el que se ejecuta un algoritmo para la ubicación óptima de los contenidos de acuerdo con el comportamiento de los usuarios y el estado de la red. Debido a que cualquier algoritmo óptimo de distribución de contenidos alcanza un límite en el que no se puede llegar a nuevas mejoras, la inclusión de los propios clientes del servicio (los peers) en el proceso de streaming puede reducir aún más el tráfico de red. Este proceso se logra aprovechando el control que el operador tiene en las redes de gestión privada sobre los equipos receptores (Set-Top Box) ubicados en las instalaciones de los clientes. El operador se reserva cierta capacidad de almacenamiento y streaming de los peers para almacenar los contenidos de vídeo y para transmitirlos a otros clientes con el fin de aliviar a los servidores de streaming. Debido a la incapacidad de los peers para sustituir completamente a los servidores de streaming, la tesis propone un sistema de streaming asistido por peers. Algunas de las cuestiones importantes que se abordan en la tesis son saber cómo los parámetros del sistema y las distintas distribuciones de los contenidos de vídeo en los peers afectan al rendimiento general del sistema. Para dar respuesta a estas preguntas, la tesis propone un modelo estocástico preciso y flexible que tiene en cuenta parámetros como las capacidades de enlace de subida y de almacenamiento de los peers, el número de peers, el tamaño de la biblioteca de contenidos de vídeo, el tamaño de los contenidos y el esquema de distribución de contenidos para estimar los beneficios del streaming asistido por los peers. El trabajo también propone una versión extendida del modelo matemático mediante la inclusión de la probabilidad de fallo de los peers y su tiempo de recuperación en el conjunto de parámetros del modelo. Estos modelos se utilizan como una herramienta para la realización de exhaustivos análisis del sistema de streaming de VoD asistido por los peers para la amplia gama de parámetros definidos en los modelos. Abstract The demand of video contents has rapidly increased in the past years as a result of the wide deployment of IPTV and the variety of services offered by the network operators. One of the services that has especially become attractive to the customers is real-time Video on Demand (VoD) because it offers an immediate streaming of a large variety of video contents. The price that the operators have to pay for this convenience is the increased traffic in the networks, which are becoming more congested due to the higher demand for VoD contents and the increased quality of the videos. Therefore, one of the main objectives of this thesis is finding solutions that would reduce the traffic in the core of the network, keeping the quality of service on satisfactory level and reducing the traffic cost. The thesis proposes a system of hierarchical structure of streaming servers that runs an algorithm for optimal placement of the contents according to the users’ behavior and the state of the network. Since any algorithm for optimal content distribution reaches a limit upon which no further improvements can be made, including service customers themselves (the peers) in the streaming process can further reduce the network traffic. This process is achieved by taking advantage of the control that the operator has in the privately managed networks over the Set-Top Boxes placed at the clients’ premises. The operator reserves certain storage and streaming capacity on the peers to store the video contents and to stream them to the other clients in order to alleviate the streaming servers. Because of the inability of the peers to completely substitute the streaming servers, the thesis proposes a system for peer-assisted streaming. Some of the important questions addressed in the thesis are how the system parameters and the various distributions of the video contents on the peers would impact the overall system performance. In order to give answers to these questions, the thesis proposes a precise and flexible stochastic model that takes into consideration parameters like uplink and storage capacity of the peers, number of peers, size of the video content library, size of contents and content distribution scheme to estimate the benefits of the peer-assisted streaming. The work also proposes an extended version of the mathematical model by including the failure probability of the peers and their recovery time in the set of parameters. These models are used as tools for conducting thorough analyses of the peer-assisted system for VoD streaming for the wide range of defined parameters.

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Hoy en día, el desarrollo tecnológico en el campo de los sistemas inteligentes de transporte (ITS por sus siglas en inglés) ha permitido dotar a los vehículos con diversos sistemas de ayuda a la conducción (ADAS, del inglés advanced driver assistance system), mejorando la experiencia y seguridad de los pasajeros, en especial del conductor. La mayor parte de estos sistemas están pensados para advertir al conductor sobre ciertas situaciones de riesgo, como la salida involuntaria del carril o la proximidad de obstáculos en el camino. No obstante, también podemos encontrar sistemas que van un paso más allá y son capaces de cooperar con el conductor en el control del vehículo o incluso relegarlos de algunas tareas tediosas. Es en este último grupo donde se encuentran los sistemas de control electrónico de estabilidad (ESP - Electronic Stability Program), el antibloqueo de frenos (ABS - Anti-lock Braking System), el control de crucero (CC - Cruise Control) y los más recientes sistemas de aparcamiento asistido. Continuando con esta línea de desarrollo, el paso siguiente consiste en la supresión del conductor humano, desarrollando sistemas que sean capaces de conducir un vehículo de forma autónoma y con un rendimiento superior al del conductor. En este trabajo se presenta, en primer lugar, una arquitectura de control para la automatización de vehículos. Esta se compone de distintos componentes de hardware y software, agrupados de acuerdo a su función principal. El diseño de la arquitectura parte del trabajo previo desarrollado por el Programa AUTOPIA, aunque introduce notables aportaciones en cuanto a la eficiencia, robustez y escalabilidad del sistema. Ahondando un poco más en detalle, debemos resaltar el desarrollo de un algoritmo de localización basado en enjambres de partículas. Este está planteado como un método de filtrado y fusión de la información obtenida a partir de los distintos sensores embarcados en el vehículo, entre los que encontramos un receptor GPS (Global Positioning System), unidades de medición inercial (IMU – Inertial Measurement Unit) e información tomada directamente de los sensores embarcados por el fabricante, como la velocidad de las ruedas y posición del volante. Gracias a este método se ha conseguido resolver el problema de la localización, indispensable para el desarrollo de sistemas de conducción autónoma. Continuando con el trabajo de investigación, se ha estudiado la viabilidad de la aplicación de técnicas de aprendizaje y adaptación al diseño de controladores para el vehículo. Como punto de partida se emplea el método de Q-learning para la generación de un controlador borroso lateral sin ningún tipo de conocimiento previo. Posteriormente se presenta un método de ajuste on-line para la adaptación del control longitudinal ante perturbaciones impredecibles del entorno, como lo son los cambios en la inclinación del camino, fricción de las ruedas o peso de los ocupantes. Para finalizar, se presentan los resultados obtenidos durante un experimento de conducción autónoma en carreteras reales, el cual se llevó a cabo en el mes de Junio de 2012 desde la población de San Lorenzo de El Escorial hasta las instalaciones del Centro de Automática y Robótica (CAR) en Arganda del Rey. El principal objetivo tras esta demostración fue validar el funcionamiento, robustez y capacidad de la arquitectura propuesta para afrontar el problema de la conducción autónoma, bajo condiciones mucho más reales a las que se pueden alcanzar en las instalaciones de prueba. ABSTRACT Nowadays, the technological advances in the Intelligent Transportation Systems (ITS) field have led the development of several driving assistance systems (ADAS). These solutions are designed to improve the experience and security of all the passengers, especially the driver. For most of these systems, the main goal is to warn drivers about unexpected circumstances leading to risk situations such as involuntary lane departure or proximity to other vehicles. However, other ADAS go a step further, being able to cooperate with the driver in the control of the vehicle, or even overriding it on some tasks. Examples of this kind of systems are the anti-lock braking system (ABS), cruise control (CC) and the recently commercialised assisted parking systems. Within this research line, the next step is the development of systems able to replace the human drivers, improving the control and therefore, the safety and reliability of the vehicles. First of all, this dissertation presents a control architecture design for autonomous driving. It is made up of several hardware and software components, grouped according to their main function. The design of this architecture is based on the previous works carried out by the AUTOPIA Program, although notable improvements have been made regarding the efficiency, robustness and scalability of the system. It is also remarkable the work made on the development of a location algorithm for vehicles. The proposal is based on the emulation of the behaviour of biological swarms and its performance is similar to the well-known particle filters. The developed method combines information obtained from different sensors, including GPS, inertial measurement unit (IMU), and data from the original vehicle’s sensors on-board. Through this filtering algorithm the localization problem is properly managed, which is critical for the development of autonomous driving systems. The work deals also with the fuzzy control tuning system, a very time consuming task when done manually. An analysis of learning and adaptation techniques for the development of different controllers has been made. First, the Q-learning –a reinforcement learning method– has been applied to the generation of a lateral fuzzy controller from scratch. Subsequently, the development of an adaptation method for longitudinal control is presented. With this proposal, a final cruise control controller is able to deal with unpredictable environment disturbances, such as road slope, wheel’s friction or even occupants’ weight. As a testbed for the system, an autonomous driving experiment on real roads is presented. This experiment was carried out on June 2012, driving from San Lorenzo de El Escorial up to the Center for Automation and Robotics (CAR) facilities in Arganda del Rey. The main goal of the demonstration was validating the performance, robustness and viability of the proposed architecture to deal with the problem of autonomous driving under more demanding conditions than those achieved on closed test tracks.