Analysis of The Key Parameters in Pedestrian Safety Assessment for the European Vehicle Fleet Using Multibody and Finite Element Mathematical Models

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.

Video analysis based vehicle detection and tracking using an MCMC sampling framework

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.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

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.

Application of virtual certification techniques to vehicle design and track maintenance

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.

Dynamic analysis of road vehicle-bridge systems under turbulent wind by means of Finite Element Models

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

Non-linear Control of an Autonomous Ground Vehicle

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.

Environmental assessment of low speed policies for motor vehicle mobility in city centres

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.

Autonomous vehicle control systems for safe crossroads

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.

Contribution of the noise radiated by a single vehicle to the road traffic noise

El ruido del tráfico rodado supone aproximadamente la mitad del ruido global ambiental. Las técnicas de control de ruido habitual en emisión (límites de emisión de vehículos) e inmisión (barreras acústicas, doble acristalamiento) no han sido suficientes para disminuir significativamente las molestias por el tráfico rodado en las últimas tres décadas. El efecto positivo de estas técnicas de control ha sido contrarrestado por el aumento de la densidad del tráfico. Por otra parte, la molestia del ruido del tráfico está altamente correlacionada con los niveles máximos de ruido (MNL), producidos por lo general por conductores agresivos. Sin embargo, los sistemas actuales de medición de ruido de tráfico se basan en una valoración global, por lo que no son capaces de discriminar entre los conductores silenciosos y ruidosos. Por lo tanto, en esta tesis se propone un sistema de medida de ruido en el campo cercano, que es capaz de medir la contribución de cada vehículo individual al ruido del tráfico rodado, permitiendo la detección de los conductores ruidosos. Este trabajo describe también una combinación de investigaciones analíticas y experimentales para la identificación de los conductores responsables de la generación de niveles máximos de ruido. El sistema se basa en dos micrófonos embarcados, uno para el ruido del motor y otro para el ruido de rodadura. Con el fin de relacionar estas mediciones de campo cercano con el ruido de los vehículos radiado al campo lejano, se desarrolla un procedimiento completo para la extrapolación del ruido medido por los micrófonos de campo próximo a las posiciones de campo lejano, usando una combinación de predicción analítica y mediciones experimentales. Las correcciones para los niveles extrapolados se deben a factores atmosféricos, al término de divergencia esférica y a las condiciones de absorción de la superficie de propagación. Para el micrófono situado próximo al motor, es necesario también caracterizar las propiedades acústicas del capó del motor. Ambos niveles de ruido se extrapolan de forma independiente a la posición de campo lejano, donde se realiza una comparación entre la predicción y mediciones para confirmar que la metodología es fiable para estimar el impacto a distancia del ruido de tráfico

Employment rate impacts of charging the Heavy Good Vehicle corridor (Madrid-Sevilla) across Spanish regions: a Random Utility Based Multiregional Input-Output approach

The implementation of a charging policy for heavy goods vehicles in European Union (EU) member countries has been imposed to reflect costs of construction and maintenance of infrastructure as well as externalities such as congestion, accidents and environmental impact. In this context, EU countries approved the Eurovignette directive (1999/62/EC) and its amending directive (2006 /38/EC) which established a legal framework to regulate the system of tolls. Even if that regulation seek s to increase the efficien cy of freight, it will trigger direct and indirect effects on Spain’s regional economies by increasing transport costs. This paper presents the development of a multiregional Input-Output methodology (MRIO) with elastic trade coefficients to predict in terregional trade, using transport attributes integrated in multinomial logit models. This method is highly useful to carry out an ex-ante evaluation of transport policies because it involves road freight transport cost sensitivity, and determine regional distributive and substitution economic effect s of countries like Spain, characterized by socio-demographic and economic attributes, differentiated region by region. It will thus be possible to determine cost-effective strategies, given different policy scenarios. MRIO mode l would then be used to determine the impact on the employment rate of imposing a charge in the Madrid-Sevilla corridor in Spain. This methodology is important for measuring the impact on the employment rate since it is one of the main macroeconomic indicators of Spain’s regional and national economic situation. A previous research developed (DESTINO) using a MRIO method estimated employment impacts of road pricing policy across Spanish regions considering a fuel tax charge (€/liter) in the entire shortest cost path network for freight transport. Actually, it found that the variation in employment is expected to be substantial for some regions, and negligible for others. For example, in this Spanish case study of regional employment has showed reductions between 16.1% (Rioja) and 1.4% (Madrid region). This variation range seems to be related to either the intensity of freight transport in each region or dependency of regions to transport intensive economic sect ors. In fact, regions with freight transport intensive sectors will lose more jobs while regions with a predominantly service economy undergo a fairly insignificant loss of employment. This paper is focused on evaluating a freight transport vehicle-kilometer charge (€/km) in a non-tolled motorway corridor (A-4) between Madrid-Sevilla (517 Km.). The consequences of the road pricing policy implementation show s that the employment reductions are not as high as the diminution stated in the previous research because this corridor does not affect the whole freight transport system of Spain.

Monitoring leafy vegetables through packaging films with

Fresh-cut or minimally processed fruit and vegetables have been physically modified from its original form (by peeling, trimming, washing and cutting) to obtain a 100% edible product that is subsequently packaged (usually under modified atmosphere packaging –MAP) and kept in refrigerated storage. In fresh-cut products, physiological activity and microbiological spoilage, determine their deterioration and shelf-life. The major preservation techniques applied to delay spoilage are chilling storage and MAP, combined with chemical treatments antimicrobial solutions antibrowning, acidulants, antioxidants, etc.). The industry looks for safer alternatives. Consequently, the sector is asking for innovative, fast, cheap and objective techniques to evaluate the overall quality and safety of fresh-cut products in order to obtain decision tools for implementing new packaging materials and procedures. In recent years, hyperspectral imaging technique has been regarded as a tool for analyses conducted for quality evaluation of food products in research, control and industries. The hyperspectral imaging system allows integrating spectroscopic and imaging techniques to enable direct identification of different components or quality characteristics and their spatial distribution in the tested sample. The objective of this work is to develop hyperspectral image processing methods for the supervision through plastic films of changes related to quality deterioration in packed readyto-use leafy vegetables during shelf life. The evolutions of ready-to-use spinach and watercress samples covered with three different common transparent plastic films were studied. Samples were stored at 4 ºC during the monitoring period (until 21 days). More than 60 hyperspectral images (from 400 to 1000 nm) per species were analyzed using ad hoc routines and commercial toolboxes of MatLab®. Besides common spectral treatments for removing additive and multiplicative effects, additional correction, previously to any other correction, was performed in the images of leaves in order to avoid the modification in their spectra due to the presence of the plastic transparent film. Findings from this study suggest that the developed images analysis system is able to deal with the effects caused in the images by the presence of plastic films in the supervision of shelf-life in leafy vegetables, in which different stages of quality has been identified.

Intelligent automatic overtaking system using vision for vehicle detection

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles – overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manœuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle’s actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles – a motorbike, car, and truck – with encouraging results.

Packaging and testing of fiber Bragg gratings for use as strain sensor for rock specimens

This paper reports a packaging and calibration procedure for surface mounting of fiber Bragg grating (FBG) sensors to measure strain in rocks. The packaging of FBG sensors is performed with glass fiber and polyester resin, and then subjected to tensile loads in order to obtain strength and deformability parameters, necessaries to assess the mechanical performance of the sensor packaging. For a specific package, an optimal curing condition has been found, showing good repeatability and adaptability for non-planar surfaces, such as occurs in rock engineering. The successfully packaged sensors and electrical strain gages were attached to standard rock specimens of gabbro. Longitudinal and transversal strains under compression loads were measured with both techniques, showing that response of FBG sensors is linear and reliable. An analytical model is used to characterize the influences of rock substrate and FBG packaging in strain transmission. As a result, we obtained a sensor packaging for non-planar and complex natural material under acceptable sensitivity suitable for very small strains as occurs in hard rocks.

A 2D computational parametric analysis of the sheltering effect of fences on a railway vehicle standing on a bridge and experiencing crosswinds

In a crosswind scenario, the risk of high-speed trains overturning increases when they run on viaducts since the aerodynamic loads are higher than on the ground. In order to increase safety, vehicles are sheltered by fences that are installed on the viaduct to reduce the loads experienced by the train. Windbreaks can be designed to have different heights, and with or without eaves on the top. In this paper, a parametric study with a total of 12 fence designs was carried out using a two-dimensional model of a train standing on a viaduct. To asses the relative effectiveness of sheltering devices, tests were done in a wind tunnel with a scaled model at a Reynolds number of 1 × 105, and the train’s aerodynamic coefficients were measured. Experimental results were compared with those predicted by Unsteady Reynolds-averaged Navier-Stokes (URANS) simulations of flow, showing that a computational model is able to satisfactorily predict the trend of the aerodynamic coefficients. In a second set of tests, the Reynolds number was increased to 12 × 106 (at a free flow air velocity of 30 m/s) in order to simulate strong wind conditions. The aerodynamic coefficients showed a similar trend for both Reynolds numbers; however, their numerical value changed enough to indicate that simulations at the lower Reynolds number do not provide all required information. Furthermore, the variation of coefficients in the simulations allowed an explanation of how fences modified the flow around the vehicle to be proposed. This made it clear why increasing fence height reduced all the coefficients but adding an eave had an effect mainly on the lift force coefficient. Finally, by analysing the time signals it was possible to clarify the influence of the Reynolds number on the peak-to-peak amplitude, the time period and the Strouhal number.