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Las marcas viales constituyen la única guía óptica que en muchas ocasiones tienen los usuarios de la vía, su correcta aplicación y conservación nos puede llegar a determinar la gravedad de un accidente hasta el punto de poder llegar a evitarlo. Por tanto, el correcto mantenimiento y repintado de la señalización vial horizontal en las carreteras convencionales a nivel mundial y de la red viaria española en particular, la investigación en nuevas combinaciones de materiales y el estudio de su durabilidad dependiendo del posicionamiento que ocupa la marca vial en carretera, nos aportan, sin duda, un apoyo útil para progresar en la lucha contra la accidentalidad vial. Por ese motivo, se ha investigado, no sólo la evolución temporal de las características fundamentales de la señalización vial horizontal como son: la visibilidad diurna, la visibilidad nocturna y la resistencia al deslizamiento de nuevas combinaciones de materiales de post-mezclado y materiales base, como es la pintura fosforescente; sino que, al mismo tiempo, se ha elaborado una relación y un estudio de la vida útil de la marca vial atendiendo a sus características fundamentales según la zona de la calzada que ocupa esa marca vial, estableciendo las pautas de comportamiento de las mismas y cuándo reemplazarlas por no cumplir con los criterios mínimos de aceptación, relacionando la sección de desgaste a cada una de las marcas viales que podemos encontrar en las carreteras convencionales de la red viaria española. Para ello, hemos elaborado un testing ground (TG1), en la carretera CV-904, con un total de 36 samples, teniendo para cada sentido de circulación 18 combinaciones de materiales atendiendo a material base y material de post-mezclado (microesferas de vidrio, cargas antideslizantes no transparentes y grano de vidrio transparente), y a su sistema de aplicación (monolayer o bilayer). Además, hemos ejecutado un segundo testing ground (TG2), en la ronda interna de la propia Universidad de Alicante, donde, partiendo de los conocimientos obtenidos en el primer estudio, se han fabricado nuevas combinaciones de materiales incluyendo el material base, diferentes tipos de microesferas de vidrio y cargas antideslizantes como parte del material de post-mezclado, se ha añadido pintura con pigmentos fosforescentes para mejorar la visibilidad nocturna y barniz de recubrimiento premezclado con agregados antideslizantes para prolongar la vida útil de la marca vial, fabricando un total de 40 samples analizadas en laboratorio. No sólo se han estudiado los resultados de los parámetros fundamentales de cada sample, sino que nos hemos apoyado en la toma de fotografías in situ analizándolas cualitativamente, lo que nos ha ayudado a comprender su evolución y los resultados. Al mismo tiempo hemos tomado muestras de todas ellas para su observación en laboratorio. Tras la comparativa entre la evolución de cada característica principal de las probetas y su análisis, hemos establecido los períodos de la vida útil de cada una de ellas según la zona de afección en la que están ubicadas atendiendo a la Norma 8.2-IC. Cabe destacar que se ha dejado la línea de investigación relacionada con la interconexión entre el vehículo autónomo, la infraestructura viaria y la señalización vial horizontal abierta como principal futura línea de investigación.

La qualité et la fiabilité des infrastructures routières jouent un rôle majeur dans la sécurité routière. Cela est d'autant plus vrai lorsque qu'on s'intéresse à la circulation de véhicules autonomes qui doivent être capables à terme de circuler seuls dans l'environnement routier. Les récents travaux menés au sein de VEDECOM montrent qu'une signalisation horizontale routière claire et visible est importante dans sa prise de décision. La détection des lignes de marquage sont en grande partie réalisée par des caméras. Afin d'optimiser cette approche et prévenir les situations de non détection, cette thèse propose des outils d'analyse de fiabilité et d'aide à la maintenance de la signalisation horizontale. Aujourd’hui, la fiabilité des marquages est basée le phénomène de rétro-réflexion : un véhicule éclaire avec ses feux de croisement un marquage qui renvoie la lumière vers le conducteur. Pour établir son niveau de dégradation, des campagnes d'inspection sont réalisées par des rétro-réflectomètres montés sur des véhicules traceurs. La littérature des trente dernières années présente essentiellement des modèles de dégradation basés sur des méthodes de régression. Ces derniers présentent de nombreuses difficultés à être déployés dans le cadre d'un plan de maintenance. Cette thèse propose d'aborder ces questions sous l'angle de la théorie de la fiabilité et de la maintenance tout en tenant compte des pratiques actuelles. Une ligne de marquage est ici interprétée comme un système multi-composants monté en parallèle. Cette thèse propose de l'analyser en quatre points. Premièrement, l'ensemble des inspections est formalisé en une base de suivi. Si des données sont manquantes et si l'historique de maintenance est indisponible, alors différentes approches basées sur une Classification Ascendante Hiérarchique (CAH) sont proposées afin de les estimer. Deuxièmement, l'entretien de la totalité d'une ligne est logistiquement délicat. Une CAH de la base de suivi a pour fonction d'établir les marquages suivant un même modèle de dégradation. Les clusters sont géographiquement localisés et corrélés à des situations précises comme un échangeur ou une agglomération. Pour ces raisons, ils sont interprétés comme des zones de maintenance stratégiques. Troisièmement, réaliser une analyse de Weibull des marquages. Les rétro-réflectomètres n'indiquent pas précisément les instants de défaillance. Ils sont statistiquement censurés à gauche, à droite ou par intervalle. En alternative à la méthode du Maximum de Vraisemblance, une approche basée sur un algorithme EM est proposé afin d'établir le modèle de Weibull et les censures estimées les plus vraisemblables. Dernièrement, deux stratégies de maintenance sont proposées : systématique par rapport à l'âge et conditionnée par la dégradation courante. Elles sont en adéquation avec les pratiques de maintenance. La première permet une gestion passive de l'entretien tandis que la seconde permet une connaissance avancée de la ligne de marquage dans le temps. A partir d'un système multi-composants non réparable et fortement censuré, les composants suivant un même modèle de dégradation sont classables, chaque groupe connait un modèle de durée de vie et finalement il est possible de déduire un plan de maintenance adapté / The quality and reliability of road infrastructure and its equipment play a major role in road safety. This is especially true if we are interested in autonomous car traffic. Recent papers from VEDECOM Institut proves that a clear and reliable road marking is important in it decison making. Marking lanes are detected by camera. These markings need an accurate maintenance strategy to guarantee that the markings remain perceptible. This report proposes different solutions based on the reliabilty and maintenance theory. Today, the markings reliability is based on the retroreflective illuminance. A retroreflective marking reflects light from a vehicle headlight back in the direction of the driver. Marking retroreflectivity can be dynamically inspected using a retroreflectometer. The litterature of the last thirty years proposes degradation models for retroreflective marking based on a regression model. All of them have a common weakness: they are difficult to apply directly to a given road network. This report presents maintenance models who math with current maintenance actions. A marking lane is interpreted as multi-unit systeme. All unit are laid in parallel. The global maintenance strategy is based on four points. First, the whole inspection data is formalized into one monitoring base. If inspection data is missing or if the maintenance historic is unavailable else an estimation process based on the Agglomerative Hierarchical Clustering (AHC) is proposed. Second, to replace a whole markings lane is logistically difficult to work. Again, an AHC of the monitoring proposed several clusters. Each cluster presents it own degradation model. Clusters are geographically tracked and correlated to specific situation (interchange, urban area, bypass...). That's why a cluster is interpreted as a maintenance strategic area. Thirdly, a Weibull analysis of each cluster is done. Current retroreflectometers cannot detects the exact faillure moment. this information is statistically censored. Three cases are identified : left, right and interval censored. To parameter a Weibull model, an EM Algorithm is propoased as an alternative to the Maximum Likelihood Estimator. This algorithm is also an estimator to censored markings life time. Lastly, two classic preventive maintenance strategies are proposed : systematic according to the age and conditionned to the current degradation. Each one is credible according the current maintenance practice. The first prposed a passsive managament of the markings maintenance. The second ensures an advanced knowledge of the road network over the time. On a multi-unit system no-repairable and strongly censored, units which admit the same degradation model are identified by a clustering approach. Each cluster present it own Weibull analysis. Finally, an adapted maintenance strategy is done

Le réseau routier subit des dégradations sous l’effet du trafic et des conditions climatiques. Le relevé dans les images de différents types de défauts de surface permet d’évaluer l’état du réseau et de programmer des opérations de maintenance nécessaires. Le but de cette thèse est ainsi de développer des méthodes non-supervisées dédiées à l'analyse des images 2D et 3D. Nous nous focalisons sur la détection de dégradations du marquage routier et la détection des fissures sur la chaussée. Dans le cadre de la signalisation horizontale, notre objectif est de réaliser un algorithme capable de détecter, reconnaitre, géolocaliser et quantifier l’état du marquage routier à l’aide d’un système d’imagerie panoramique. Le traitement d’images effectué utilise une méthode de segmentation couleur pour faciliter la phase d’extraction des zones de marquages routiers. Ensuite, une technique de perspective inverse est appliquée pour faciliter l’identification des objets détectés. L’état du marquage est établi à partir des variations des caractéristiques géométriques (longueur, largeur, etc.) et colorimétriques (niveau de couleur blanche) des objets identifiés dans l’image. Dans le cadre de la détection des fissures, notre aspiration consiste à extraire automatiquement les fissures en surface de chaussée, en supposant que celles-ci sont des structures fines et sombres dans l’image. Parmi les nombreuses méthodes existantes, nos approches retenues suivent un schéma classique composé de trois phases principales, à savoir une phase de pré-traitement pour réduire la quantité d’information à traiter, une phase de traitement pour extraire les points ayant une forte vraisemblance d’appartenir à une fissure et une phase de post-traitement pour estimer la gravité du matériel. Les performances de nos algorithmes sont évaluées sur des images réelles 2D et 3D issues de 3 capteurs différents (VIAPIX®, LCMS et Aigle-RN). / The road network is subject to degradations due to traffic and weather conditions. The detection of surface defects within pavement images is used to evaluate the road network and to schedule the necessary maintenance operations. The goal of this thesis is to develop unsupervised processing techniques for the analysis of 2D and 3D pavement images, which originate from imaging systems operating in the field of road engineering. We focus on the detection of road marking damage and the detection of cracks on the pavement. In the context of road marking, our objective is to realize an algorithm for detecting, recognizing, geo-locating and monitoring the wearing conditions of road marking using a panoramic imaging system. The performed image processing uses a color segmentation method to facilitate the extraction phase of the road marking zones. Then, an inverse perspective technique is applied to ease the identification of detected objects.The wearing conditions of road marking is established from the variations in the geometric (length, width, etc.) and colorimetric (white color level) characteristics of the objects identified in the image.In the context of road crack detection, our aspiration is the automatic segmentation of cracks within pavement images, assuming that they represent fine and dark features in the image. Among the many existing methods, our chosen approaches follow a classical scheme composed of three main phases, namely, a pre-processing phase to reduce the amount of information to be processed in the image, a processing phase to extract the points having a high likelihood of belonging to a crack on the road and a post-processing phase to estimate the severity and the damage level of the pavement. The performances of our proposed algorithms are evaluated on 2D and 3D real images, coming from 3 types of existing imaging devices for road engineering (VIAPIX®, LCMS and Aigle-RN).

Autonomous driving technology is now evolving at an unprecedented speed. HD maps, which are embedded with highly precise and detailed road spatial and object information, play an important role in supporting autonomous vehicles. This thesis presents the development of a semi-automated HD map creation and updating method that is capable of extracting basic road feature information to HD maps by employing raw MLS point cloud data. The proposed HD map creation method consists of four steps: Road edge extraction, road surface extraction, road marking extraction and driving line generation. First, an existing curb-based road edge detection method is applied to extract road edge candidate points according to the elevation difference and slope between points. This thesis develops an edge vectorization algorithm based on the point's distance-to-trajectory. Then, the road surface is extracted by filtering the points inside fitted edges on the XY plane within a range of the ground elevation. In the next step, instead of using intensity to detect road markings used by most studies, this thesis fuses point clouds and images to assign each point with an RGB value to segment marking points. Marking objects are extracted by conditional Euclidean clustering and classified according to a manually defined decision tree. Finally, driving lines are generated based on the vectorized road edge and lane markings. The HD map update method varies depending on which data source is updated for the road segments, including updating images only, updating point clouds only and updating both images and point clouds. The method is evaluated by six point clouds and image datasets collected from different types of roads. The extracted road edges are assessed by both length- and buffer-based assessment methods. The results indicate that the road edge extraction algorithm performs well in all three dimensions. The road surface extraction results confirm the high accuracy of extracted edges. In addition, the quantitative evaluations of road markings demonstrate that the proposed road marking extraction method achieves an average recall, precision, and F1-score of 94.50%, 81.65% and 87.09%.

Curbs and road markings were designed to provide a visual low-level spatial perception of road environments. In this sense, a perception system capable of detecting those road features is of utmost importance for an autonomous vehicle. In vision-based approaches, few works have been developed for curb detection, and most of the advances on road marking detection have aimed lane markings only. Therefore, to detect all these road features, multiple algorithms running simultaneously would be necessary. Alternatively, as the main contribution of this work, it was proposed to employ an architecture of Fully Convolutional Neural Network (FCNN), denominated as 3CSeg-Multinet, to detect curbs and road markings in a single inference. Since there was no labeled dataset available for training and validation, a new one was generated with Brazilian urban scenes, and they were manually labeled. By visually analyzing experimental results, the proposed approach has shown to be effective and robust against most of the clutter present on images, running at around 10 fps in a Graphics Processing Unit (GPU). Moreover, with the intention of granting spatial perception, stereo vision techniques were used to project the detected road features in a point cloud. Finally, as a way to validate the applicability of the proposed perception system on a vehicle, it was also introduced a vision-based metric localization model for the urban scenario. In an experiment, compared to the ground truth, this localization method has revealed consistency on its pose estimations in a map generated by LIDAR. / Guias e sinalizações horizontais foram projetados para fornecer a percepção visual de baixo nível do espaço das vias urbanas. Deste modo, seria de extrema importância para um veículo autônomo ter um sistema de percepção capaz de detectar tais características visuais. Em abordagens baseadas em visão, poucos trabalhos foram desenvolvidos para detecção de guias, e a maioria dos avanços em detecção de sinalizações horizontais foi focada na detecção de faixas apenas. Portanto, para que fosse possível detectar todas essas características visuais, seria necessário executar diversos algoritmos simultaneamente. Alternativamente, como sendo a principal contribuição deste trabalho, foi proposto a adoção de uma Rede Neural Totalmente Convolutiva, denominado 3CSeg-Multinet, para detectar guias e sinalizações horizontais em apenas uma inferência. Como não havia um conjunto de dados rotulados disponível para treinar e validar a rede, foi gerado um novo conjunto com imagens capturadas em ambiente urbano brasileiro, e foi realizado a rotulação manual. Através de uma análise visual dos resultados experimentais obtidos, o método proposto mostrou-se eficaz e robusto contra a maioria dos fatores que causam confusão nas imagens, executando a aproximadamente 10 fps em uma GPU. Ainda, com o intuito de garantir a percepção espacial, foram usados métodos de visão estéreo para projetar as características detectadas em núvem de pontos. Finalmente, foi apresentado também um modelo de localização métrica baseado em visão para validar a aplicabilidade do sistema de percepção proposto em um veículo. Em um experimento, este método de localização revelou-se capaz de manter as estimativas consistentes com a verdadeira pose do veículo em um mapa gerado a partir de um sensor LIDAR.

<p>A complete prototype system for measuring vehicle lateral position has been set up during the course of this master’s thesis project. In the development of the software, images acquired from a back-ward looking video camera mounted on the roof of the vehicle were used. </p><p>The problem of using computer vision to measure lateral position can be divided into road marking detection and lateral position extraction. Since the strongest characteristic of a road marking image are the edges of the road markings, the road marking detection step is based on edge detection. For the detection of the straight edge lines a Hough based method was chosen. Due to peak spreading in Hough space, the difficulty of detecting the correct peak in Hough space was encountered. A flexible Hough peak detection algorithm was developed based on an adaptive window that takes peak spreading into account. The road marking candidate found by the system is verified before the lateral position data is generated. A good performance of the road marking tracking algorithm was obtained by exploiting temporal correlation to update a search region within the image. A camera calibration made the extraction of real-world lateral position information and yaw angle data possible. </p><p>This vision-based method proved to be very accurate. The standard deviation of the error in the position detection is 0.012 m within an operating range of ±2 m from the image centre. During continuous road markings the rate of valid data is on average 96 %, whereas it drops to around 56 % for sections with intermittent road markings. The system performs well during lane change manoeuvres, which is an indication that the system tracks the correct road marking. This prototype system is a robust and automatic measurement system, which will benefit VTI in its many driving behaviour research programs.</p>

This doctoral thesis deals primarily with condition assessment of road equipment. The road equipment concept is defined by five main groups, road lighting, fences and barriers, vertical signs, horizontal signs and traffic signals, respectively. Of these groups, road markings, street lighting and barriers of three-lane roads have been studied more in detail. A state-of-the-art, comprising information obtained by comprehensive literature studies on condition assessment of road equipment is presented. Comparably few fundamental studies were found, which, to some degree, can be explained by the lack of suitable physical measurement methods. However, in the case of road marking retroreflectivity, mobile instruments have been developed, and research published in this area is relatively comprehensive. Furthermore, although not based on mobile measurements, several studies on assessments on performance of road sign sheeting have been published. The experimental part of the thesis is divided into four studies, of which two are dealing with mobile measurement of wet road markings and street lighting, respectively. One of the studies concerns condition assessment of road marking performance accomplished in the Nordic countries. Finally, one study comprises risk analysis related to crashes into the barriers on three-lane roads. At road equipment condition assessment, mobile measurement methods are preferable compared to stationary methods. However, many relevant parameters are tricky to measure at speed. One example in this connection is characterization of performance of wet road markings, which has to be based on one or more parameters obtained by measurements on dry surfaces. Results presented in this thesis indicate that retroreflectivity and skid resistance of wet road markings can be predicted based on retroreflectivity and macro-texture of dry road marking. For traffic safety, street lighting is important. The performance of this type of road equipment is in most cases described in terms of luminance of the illuminated road surface. However, luminance measurements are tricky and time-consuming and not useful for condition assessment. On the contrary, measurement of illuminance is easy to carry out and can be performed at speed. One part of the thesis describes how road surface luminance in street lighting can be estimated based on illuminance and reflection properties of the road surface. With the purpose of comparing road marking performance in the Nordic countries, condition assessment using mobile measurement equipment was accomplished in 2002 and 2003. In each of the five Nordic countries, a number of roads were chosen for measuring retroreflectivity. The study showed that the retroreflectivity of edge, centre and lane lines was poor in some countries, but, at least regarding edge lines, this shortcoming could be compensated by use of wide, continuous lines. In other words, the visibility of longitudinal road markings was approximately equal in the different countries. The purpose of the risk analysis performed on three-lane road barriers was to estimate the influence of the time-period between initial crash and repair on the risk of a secondary accident. The result showed that, especially in winter-time, time-reduction means reduced risk of secondary accidents. / QC 20100824

A complete prototype system for measuring vehicle lateral position has been set up during the course of this master’s thesis project. In the development of the software, images acquired from a back-ward looking video camera mounted on the roof of the vehicle were used. The problem of using computer vision to measure lateral position can be divided into road marking detection and lateral position extraction. Since the strongest characteristic of a road marking image are the edges of the road markings, the road marking detection step is based on edge detection. For the detection of the straight edge lines a Hough based method was chosen. Due to peak spreading in Hough space, the difficulty of detecting the correct peak in Hough space was encountered. A flexible Hough peak detection algorithm was developed based on an adaptive window that takes peak spreading into account. The road marking candidate found by the system is verified before the lateral position data is generated. A good performance of the road marking tracking algorithm was obtained by exploiting temporal correlation to update a search region within the image. A camera calibration made the extraction of real-world lateral position information and yaw angle data possible. This vision-based method proved to be very accurate. The standard deviation of the error in the position detection is 0.012 m within an operating range of ±2 m from the image centre. During continuous road markings the rate of valid data is on average 96 %, whereas it drops to around 56 % for sections with intermittent road markings. The system performs well during lane change manoeuvres, which is an indication that the system tracks the correct road marking. This prototype system is a robust and automatic measurement system, which will benefit VTI in its many driving behaviour research programs.

This diploma thesis deals with the analysis of selected properties of horizontal road marking (HRM). In terms of anti-skid properties measurements are made to determine the longitudinal friction coefficient, the coefficient of adhesion under different conditions and skid resistance of HRM. Measurements of anti-skid properties are supplemented by measurement of retroreflection of HRM. The theoretical part describes the current state of the issue, general characteristics of horizontal road marking and quantities measured in this thesis (friction and adhesion). The practical part consists of description of used measuring devices, custom solution and results analysis. The solution consists of the description of the measured samples, their preparation, subsequent measurement and a detailed description of the method of measured data evaluation. Data analysis is based on comparison of results obtained from individual sample groups and on comparison of measured values among themselves. The thesis is supplemented with photo documentation and video footage.