907 resultados para Vehicle frames.


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Personal and career development interventions aim to help people find answers to personal and career development issues that stem from the societal context in which they live. Societal definitions of these career issues have a double consequence. On the one hand, these issues differ from one culture to another; and, on the other, they evolve along with the contexts in which they are expressed. Implementation of rigorous career development interventions requires, first, a scientific reconstruction of these societal issues and, second, a clear definition of these interventions' goals and ends. Our current view of the societal issues relating to personal and career development interventions may be phrased thus--"How can we help individuals direct their lives, in the (human) society where they interact?" It may be turned into the following scientific question: "What are the factors and processes of life-long self-construction?" An articulation of three major propositions (sociological, cognitive and dynamic) seems to be needed to answer this question. Such a theoretical frame does not allow for a definition of personal and career development interventions ends. In the world of today, the adoption by everyone of a personal ethic of responsibility towards all life on Earth (H. Jonas) could well be a fundamental end to these interventions.

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Personal and career development interventions aim to help people find answers to personal and career development issues that stem from the societal context in which they live. Societal definitions of these career issues have a double consequence. On the one hand, these issues differ from one culture to another; and, on the other, they evolve along with the contexts in which they are expressed. Implementation of rigorous career development interventions requires, first, a scientific reconstruction of these societal issues and, second, a clear definition of these interventions' goals and ends. Our current view of the societal issues relating to personal and career development interventions may be phrased thus--"How can we help individuals direct their lives, in the (human) society where they interact?" It may be turned into the following scientific question: "What are the factors and processes of life-long self-construction?" An articulation of three major propositions (sociological, cognitive and dynamic) seems to be needed to answer this question. Such a theoretical frame does not allow for a definition of personal and career development interventions ends. In the world of today, the adoption by everyone of a personal ethic of responsibility towards all life on Earth (H. Jonas) could well be a fundamental end to these interventions.

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Personal and career development interventions aim to help people find answers to personal and career development issues that stem from the societal context in which they live. Societal definitions of these career issues have a double consequence. On the one hand, these issues differ from one culture to another; and, on the other, they evolve along with the contexts in which they are expressed. Implementation of rigorous career development interventions requires, first, a scientific reconstruction of these societal issues and, second, a clear definition of these interventions' goals and ends. Our current view of the societal issues relating to personal and career development interventions may be phrased thus--"How can we help individuals direct their lives, in the (human) society where they interact?" It may be turned into the following scientific question: "What are the factors and processes of life-long self-construction?" An articulation of three major propositions (sociological, cognitive and dynamic) seems to be needed to answer this question. Such a theoretical frame does not allow for a definition of personal and career development interventions ends. In the world of today, the adoption by everyone of a personal ethic of responsibility towards all life on Earth (H. Jonas) could well be a fundamental end to these interventions.

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Cold-water corals provide an important habitat for a rich fauna along the continental margins and slopes. Although these azooxanthellate corals are considered particularly sensitive to ocean acidification, their responses to natural variations in pH and aragonite saturation are largely unknown due to the difficulty of studying their ecology in deep waters. Previous SCUBA investigations have shown an exceptionally shallow population of the cold-water coral Desmophyllum dianthus in near-surface waters of Comau Fjord, a stratified 480 m deep basin in northern Chilean Patagonia with suboxic deep waters. Here, we use a remotely operated vehicle to quantitatively investigate the distribution of D. dianthus and its physico-chemical drivers in so far uncharted naturally acidified waters. Remarkably, D. dianthus was ubiquitous throughout the fjord, but particularly abundant between 20 and 280 m depth in a pH range of 8.4 to 7.4. The persistence of individuals in aragonite-undersaturated waters suggests that present-day D. dianthus in Comau Fjord may show pre-acclimation or pre-adaptation to conditions of ocean acidification predicted to reach over 70% of the known deep-sea coral locations by the end of the century.

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Esta tesis investiga cuales son los parámetros más críticos que condicionan los resultados que obtienen en los ensayos de protección de peatones la flota Europea de vehículos, según la reglamentación europea de protección de peatones de 2003 (Directiva CE 2003/102) y el posterior Reglamento de 2009 (Reglamento CE 2009/78). En primer lugar se ha analizado el contexto de la protección de peatones en Europa, viendo la historia de las diferentes propuestas de procedimientos de ensayo así como los cambios (y las razones de los mismos) que han sufrido a lo largo del proceso de definición de la normativa Europea. Con la información disponible de más de 400 de estos ensayos se han desarrollado corredores de rigidez para los frontales de los diferentes segmentos de la flota de vehículos europea, siendo este uno de los resultados más relevantes de esta tesis. Posteriormente, esta tesis ha realizado un estudio accidentológico en detalle de los escenarios de atropello de peatones, identificando sus características más relevantes, los grupos de población con mayor riesgo y los tipos de lesiones más importantes que aparecen (en frecuencia y severidad), que han sentado las bases para analizar con modelos matemáticos hasta qué punto los métodos de ensayo propuestos realmente tienen estos factores en cuenta. Estos análisis no habrían sido posibles sin el desarrollo de las nuevas herramientas que se presentan en esta tesis, que permiten construir instantáneamente el modelo matemático de cualquier vehículo y cualquier peatón adulto para analizar su iteración. Así, esta tesis ha desarrollado una metodología rápida para desarrollar modelos matemáticos de vehículos a demanda, de cualquier marca y modelo y con las características geométricas y de rigidez deseados que permitan representarlo matemáticamente y del mismo modo, ha investigado cómo evoluciona el comportamiento del cuerpo humano durante el envejecimiento y ha implementado una funcionalidad de escalado en edad al modelo de peatón en multicuerpo de MADYMO (ya escalable en tamaño) para permitir modelar ad hoc cualquier peatón adulto (en género y edad). Finalmente, esta tesis también ha realizado, utilizando modelos de elementos finitos del cuerpo humano, diferentes estudios sobre la biomecánica de las lesiones más frecuentes de este tipo de accidentes, (en piernas y cabeza) con el objetivo de mejorar los procedimientos de ensayo para que predigan mejor el tipo de lesiones que se quieren evitar. Con el marco temporal y las condiciones de contorno de esta tesis se han centrado los esfuerzos en reforzar algunos aspectos críticos pero puntuales sobre cómo mejorar el ensayo de cabeza y, sobretodo, en proponer soluciones viables y con un valor añadido real al ensayo de pierna contra parachoques, sin cambiar la esencia del mismo pero proponiendo un nuevo impactador mejorado que incorpore una masa extra que representa a la parte superior del cuerpo y sea válido para toda la flota europea de vehículos independiente de la geometría de su frontal.

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This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

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En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

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Virtual certification partially substitutes by computer simulations the experimental techniques required for rail vehicle certification. In this paper, several works were these techniques were used in the vehicle design and track maintenance processes are presented. Dynamic simulation of multibody systems was used to virtually apply the EN14363 standard to certify the dynamic behaviour of vehicles. The works described are: assessment of a freight bogie design adapted to meter-gauge, assessment of a railway track layout for a subway network, freight bogie design with higher speed and axle load, and processing of the data acquired by a track recording vehicle for track maintenance.

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When an automobile passes over a bridge dynamic effects are produced in vehicle and structure. In addition, the bridge itself moves when exposed to the wind inducing dynamic effects on the vehicle that have to be considered. The main objective of this work is to understand the influence of the different parameters concerning the vehicle, the bridge, the road roughness or the wind in the comfort and safety of the vehicles when crossing bridges. Non linear finite element models are used for structures and multibody dynamic models are employed for vehicles. The interaction between the vehicle and the bridge is considered by contact methods. Road roughness is described by the power spectral density (PSD) proposed by the ISO 8608. To consider that the profiles under right and left wheels are different but not independent, the hypotheses of homogeneity and isotropy are assumed. To generate the wind velocity history along the road the Sandia method is employed. The global problem is solved by means of the finite element method. First the methodology for modelling the interaction is verified in a benchmark. Following, the case of a vehicle running along a rigid road and subjected to the action of the turbulent wind is analyzed and the road roughness is incorporated in a following step. Finally the flexibility of the bridge is added to the model by making the vehicle run over the structure. The application of this methodology will allow to understand the influence of the different parameters in the comfort and safety of road vehicles crossing wind exposed bridges. Those results will help to recommend measures to make the traffic over bridges more reliable without affecting the structural integrity of the viaduct

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In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi-Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles' state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle's state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle's state for more than one minute, at real-time frame rates based, only on visual information.

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In this paper, in order to select a speed controller for a specific non-linear autonomous ground vehicle, proportional-integral-derivative (PID), Fuzzy, and linear quadratic regulator (LQR) controllers were designed. Here, in order to carry out the tuning of the above controllers, a multicomputer genetic algorithm (MGA) was designed. Then, the results of the MGA were used to parameterize the PID, Fuzzy and LQR controllers and to test them under laboratory conditions. Finally, a comparative analysis of the performance of the three controllers was conducted.

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streets in local residential areas in large cities, real traffic tests for pollutant emissions and fuel consumption have been carried out in Madrid city centre. Emission concentration and car activity were simultaneously measured by a Portable Emissions Measurement System. Real life tests carried out at different times and on different days were performed with a turbo-diesel engine light vehicle equipped with an oxidizer catalyst and using different driving styles with a previously trained driver. The results show that by reducing the speed limit from 50 km h-1 to 30 km h-1, using a normal driving style, the time taken for a given trip does not increase, but fuel consumption and NOx, CO and PM emissions are clearly reduced. Therefore, the main conclusion of this work is that reducing the speed limit in some narrow streets in residential and commercial areas or in a city not only increases pedestrian safety, but also contributes to reducing the environmental impact of motor vehicles and reducing fuel consumption. In addition, there is also a reduction in the greenhouse gas emissions resulting from the combustion of the fuel.

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This article presents a cooperative manoeuvre among three dual mode cars – vehicles equipped with sensors and actuators, and that can be driven either manually or autonomously. One vehicle is driven autonomously and the other two are driven manually. The main objective is to test two decision algorithms for priority conflict resolution at intersections so that a vehicle autonomously driven can take their own decision about crossing an intersection mingling with manually driven cars without the need for infrastructure modifications. To do this, the system needs the position, speeds, and turning intentions of the rest of the cars involved in the manoeuvre. This information is acquired via communications, but other methods are also viable, such as artificial vision. The idea of the experiments was to adjust the speed of the manually driven vehicles to force a situation where all three vehicles arrive at an intersection at the same time.