Este trabalho trata do estudo de concepções de arquitetura do controle aplicadas aos robôs móveis autônomos e da proposição de um delas à instrumentação e controle em tempo real de um modelo de embarcação naval de alto desempenho. Tal veículo remotamente operado foi desenvolvido como parte das atividades do projeto temático "Comportamento em Ondas de Embarcações de Alto Desempenho" (proc.Fapesp 1997/13090-3). Realizou-se uma investigação dos diversos paradigmas de inteligência artificial que orientaram a evolução dos robôs móveis autônomos até o presente momento e, em particular, as concepções baseadas em modelos sócio-antropológicos e computacionais (teoria de agentes e orientação a objetos) através de sua aplicação à implementação de um sistema de aquisição e controle orientado a objetos, modelado através da UML (Unified Modeling Language), para o veículo mencionado. Testes de validação da arquitetura do controle foram realizados, sendo obtidos resultados experimentais que permitiram análises a respeito da dinâmica, manobrabilidade e navegação do veículo, as quais sugerem vários aperfeiçoamentos para o sistema de hardware e software em trabalhos futuros. / This work deals with the study of control architecture approaches applied to autonomous mobile robots, and proposes one of them for the control system of a self-propelled high speed ship model. Such unmanned vehicle was developed for the research project “Comportamento em Ondas de Embarcações de Alto Desempenho” (proc. FAPESP 1997/13090-3). A number of artificial intelligence paradigms, related to the autonomous robot evolution up to now, were investigated. Models based on the socio-anthropological paradigm and the corresponding computer science approaches, i.e. agent theory and object-oriented modeling, were emphasized. Object-oriented control software based on the UML (Unified Modeling Language) was designed for the real-time embedded system of the ship model. Validation tests of the control architecture were carried out. Experimental results, related to vehicle dynamics, maneuverability and navigation were acquired by the embedded system and analyzed in this work. These results suggest a number of improvements for future works on the software and hardware systems.

Este trabalho trata do estudo de concepções de arquitetura do controle aplicadas aos robôs móveis autônomos e da proposição de um delas à instrumentação e controle em tempo real de um modelo de embarcação naval de alto desempenho. Tal veículo remotamente operado foi desenvolvido como parte das atividades do projeto temático "Comportamento em Ondas de Embarcações de Alto Desempenho" (proc.Fapesp 1997/13090-3). Realizou-se uma investigação dos diversos paradigmas de inteligência artificial que orientaram a evolução dos robôs móveis autônomos até o presente momento e, em particular, as concepções baseadas em modelos sócio-antropológicos e computacionais (teoria de agentes e orientação a objetos) através de sua aplicação à implementação de um sistema de aquisição e controle orientado a objetos, modelado através da UML (Unified Modeling Language), para o veículo mencionado. Testes de validação da arquitetura do controle foram realizados, sendo obtidos resultados experimentais que permitiram análises a respeito da dinâmica, manobrabilidade e navegação do veículo, as quais sugerem vários aperfeiçoamentos para o sistema de hardware e software em trabalhos futuros. / This work deals with the study of control architecture approaches applied to autonomous mobile robots, and proposes one of them for the control system of a self-propelled high speed ship model. Such unmanned vehicle was developed for the research project “Comportamento em Ondas de Embarcações de Alto Desempenho" (proc. FAPESP 1997/13090-3). A number of artificial intelligence paradigms, related to the autonomous robot evolution up to now, were investigated. Models based on the socio-anthropological paradigm and the corresponding computer science approaches, i.e. agent theory and object-oriented modeling, were emphasized. Object-oriented control software based on the UML (Unified Modeling Language) was designed for the real-time embedded system of the ship model. Validation tests of the control architecture were carried out. Experimental results, related to vehicle dynamics, maneuverability and navigation were acquired by the embedded system and analyzed in this work. These results suggest a number of improvements for future works on the software and hardware systems.

Dans ce mémoire de thèse, nous avons étudié le problème de régulation du trafic en considérant les nouvelles technologies dans le cadre des Systèmes de Transport Intelligent (STI). Une nouvelle stratégie de contrôle est introduite afin d’exploiter le potentiel des infrastructures de la circulation à un niveau maximum. Plus précisément, basée sur la technologie VII « Intégration Véhicule-Infrastructure », l'infrastructure routière aux carrefours (considérée aussi comme contrôleur) peut communiquer avec les véhicules autonomes qui arrivent à un carrefour de manière continue. Les données importantes sur les véhicules telles que la vitesse, la position et la destination sont alors reçues par des capteurs avancés et envoyées au contrôleur en temps réel. Par conséquent, il est possible d'élaborer une stratégie de contrôle du trafic en considérant chaque véhicule comme une entité indépendante. En d'autres termes, le droit de passage est attribué à chaque véhicule en fonction de son état et en fonction de l'état global du trafic au carrefour. Seuls les véhicules qui ont reçu le droit de passage peuvent traverser le carrefour. Le contrôle du trafic au niveau d’un carrefour vise donc à déterminer les séquences de passage des véhicules, c’est-à-dire les séquences de distribution des droits de passage.Cependant, la plus grande difficulté pour appliquer cette nouvelle stratégie est la contradiction entre l'optimisation des séquences de passages des véhicules et la complexité temporelle. Pour résoudre cette contradiction, nous avons d’abord formulé mathématiquement la problématique de régulation et nous avons ensuite étudié sa complexité. Nous avons prouvé dans un premier temps que le problème de régulation du trafic formulé à l’intersection isolée est NP-hard sous certaines conditions (nombre arbitraire de groupes de flux compatibles GFC,…) et ceci en se basant sur la réduction au problème de 3-Partition. Dans un deuxième temps, nous avons appliqué les méthodes de résolutions exactes sur un carrefour isolé pour proposer des algorithmes exacts (Branch and Bound et Programmation dynamique) permettant de trouver une séquence de passage optimale. Plusieurs propriétés du problème ont été introduites et prouvées et ceci afin qu’elles soient exploitées par ces algorithmes. Ces propriétés ont pour objectif de réduire considérablement l’espace de recherche et par conséquent le temps d’exécution de ces algorithmes exacts.Par ailleurs, nous n’avons pas limité nos recherches sur des carrefours isolées mais nous avons appliqué l’approche de contrôle proposée sur un réseau de carrefours tout en considérant un seul contrôleur. Cependant, un algorithme exact appliqué sur plusieurs carrefours ne peut pas être assez rapide surtout lorsqu’on a besoin de communiquer presque instantanément des informations aux véhicules (en temps réel). Nous avons proposé donc des méthodes de résolutions approchées afin de trouver en un temps raisonnable une séquence de passage satisfaisante pour chaque carrefour. Ces algorithmes (Algorithmes génétiques) ont en effet, besoin de moins de temps de calcul tout en assurant une bonne qualité de solution.Enfin, nous illustrons la mise en œuvre des déférentes approches proposées à travers des résultats de simulation afin d’évaluer leurs performances. / In this thesis, we studied the problem of traffic control by considering the new technologies as part of Intelligent Transport Systems (ITS). A new control strategy is introduced to exploit the potential of infrastructure traffic at a maximum level. Specifically, based Technology VII "Vehicle-Infrastructure Integration", the road infrastructure at intersections (considered also as a controller) can communicate with autonomous vehicles that arrive at a crossroads on a continuous basis. Important data such as vehicle speed, position and destination are then received by advanced sensors and sent to the controller in real time. Therefore, it is possible to develop a strategy for traffic control by treating each vehicle as an independent entity. In other words, the right of way is assigned to each vehicle based on its status and function of the overall state of traffic at the intersection. Only vehicles that have received the right of way may cross the junction. Traffic control at an intersection is therefore to determine the sequence of passage of vehicles, that is to say the sequences distribution rights passage.Cependant, the greatest difficulty to implement this new strategy is the contradiction between the optimization of sequences of passes of vehicles and time complexity. To resolve this contradiction, we first mathematically formulated the problem of regulation and we then studied its complexity. We proved initially that the problem of traffic control at the intersection isolated formulated is NP-hard under certain conditions (arbitrary number of groups CFA compliant streams, ...) and this is based on reducing the problem of 3-Partition. In a second step, we applied the methods of accurate resolutions on an isolated intersection to propose exact algorithms (Branch and Bound and Dynamic Programming) for finding an optimal sequence of passage. Several properties of the problem have been introduced and this proved and so they are exploited by these algorithms. These properties are intended to significantly reduce the search space and consequently the execution time of these algorithms exacts.Par Moreover, we have not limited our research on isolated intersections but we applied the approach control proposed a network of nodes while considering a single controller. However, an exact algorithm applied to several intersections can not be fast enough especially when you need to communicate information almost instantaneously to vehicles (real time). So we proposed methods to find approximate resolutions in a reasonable time a sequence of way satisfactory to each intersection. These algorithms (Genetic Algorithms) have indeed require less computation time while maintaining a good quality of solution.Enfin, we illustrate the implementation of deferential proposed approaches through simulation results to evaluate their performance .

The traffic engineering community currently faces the advent of a new generation of Intelligent Transportation Systems (ITS), known as cooperative systems. More specifically, the recent developments of connected and autonomous vehicles, i.e. cooperative vehicles, are expected to cause a societal shift, changing the way people commute on a daily basis and relate to transport in general. The research presented in this dissertation is motivated by the need for proper understanding of the possible inputs of cooperative vehicles in a traffic stream. Beyond legal aspects regarding the introduction of such vehicles and considerations on standardization and harmonization of the communication norms, the research focuses on the use of communication for highway traffic flow homogenization. In particular, the selected approach for the introduction of cooperation inherits from the theory of traffic flow and the recent developments of microscopic traffic models. Cooperation can first be introduced as a form of multi-anticipation, which can either come from drivers' behaviors or from communication. A mathematical framework for investigating the impact of perturbations into a steady-state traffic is proposed for the class of time continuous car-following models. Linear stability analyses are refined for forward and backward multi-anticipation, exploring the underlying importance of considering upstream information. The linear stability analyses for all wavelengths can be deepened by the mean of the graphical root locus analysis, which enables comparisons and design of strategies of cooperation. The positive influence of bilateral cooperation and of added linear control terms are highlighted. Weakly non-linear analyses are also performed, and the equations of solitary waves appearing at the frontier of the instability domain are obtained. A simple condition over the partial derivatives of the dynamical system is found to determine the acceleration regime of the leading edge of the travelling wave. Following these analytical results, one aim is to simulate a realistic traffic thereby reproducing the driving behavior variability. A Next Generation Simulation trajectory dataset is used to calibrate three continuous car-following models. A methodology involving data filtering, robust calibration, parameters estimation and sampling of realistic parameters is detailed, and allows realistic traffic with stop-and-go waves appearances to be replicated. Based on these simulated trajectories, previous analytical results are confirmed, and the growing perturbations are removed for various coverage rates of cooperative vehicles and adequately tuned cooperative strategies. Finally the issue of information reliability is assessed for a mixed fleet of cooperative and non-cooperative vehicles. The modeling choice consists in building a three layers multi-agent framework that enables the following properties to be defined: the physical behavior of vehicles, the communication possibilities, and the trust each vehicle -or agent- has in another vehicle information or in itself. The investigation of trust and communication rules allow the model to deal with high rates of disturbed cooperative vehicles sensors and to learn in real time the quality of the sent and received information. It is demonstrated that appropriate communication and trust rules sensibly increase the robustness of the network to perturbations coming from exchanges of unreliable information.

The localization of autonomous ground vehicles in dense urban environments poses a challenge. Applications in classical outdoor robotics rely on the availability of GPS systems in order to estimate the position. However, the presence of complex building structures in dense urban environments hampers a reliable localization based on GPS. Alternative approaches have to be applied In order to tackle this problem. This thesis proposes an approach which combines observations of a single perspective camera and odometry in a probabilistic framework. In particular, the localization in the space of appearance is addressed. First, a topological map of reference places in the environment is built. Each reference place is associated with a set of visual features. A feature selection is carried out in order to obtain distinctive reference places. The topological map is extended to a hybrid representation by the use of metric information from Geographic Information Systems (GIS) and satellite images. The localization is solved in terms of the recognition of reference places. A particle lter implementation incorporating this and the vehicle's odometry is presented. The proposed system is evaluated based on multiple experiments in exemplary urban environments characterized by high building structures and a multitude of dynamic objects.

Autonomous land vehicles (ALVs) have received considerable attention after their introduction into military and commercial applications. ALVs still stand as a challenging research topic. One of the main problems arising in ALV operations is the navigation accuracy while the other is the dynamic effects of road irregularities which may prevent the vehicle and its cargo to function properly. In this thesis, we propose intelligent solutions to these two basic problems of ALV. First, an intelligent method is proposed to enhance the performance of a coupled global positioning/inertial navigation system (GPS/INS) for land navigation applications during the GPS signal loss. Our method is based on using an artificial neural network (ANN) to intelligently aid the GPS/INS coupled navigation system in the absence of GPS signals. The proposed enhanced GPS/INS is used in the dynamic environment of a tour of an autonomous van and we provide the results here. GPS/INS+ANN system performance is thus demonstrated with the land trials. Secondly, our work focuses on the identification and enlargement of the stability region of the ALV. In this thesis, the domain of attraction of the ALV is found to be patched by chaotic and regular regions with chaotic boundaries which are extracted using novel technique of cell mapping equipped with measures of fractal dimension and rough sets. All image cells in the cellular state space, with their individual fractal dimension are classified as being members of lower approximation (surely stable), upper approximation (possibly stable) or boundary region using rough set theory. The obtained rough set with fractal dimension as its attribute is used to model the uncertainty of the regular regions. This uncertainty is then smoothed by a reinforcement learning algorithm in order to enlarge regular regions that are used for chassis control, critical in ALV in preventing vibration damages that can harm the payload. Hence, we will make ALV work in the largest safe area in dynamical sense and prevent the vehicle and its cargo.

A significant body of research has focused on tracking behaviors of predators responding to prey odor plumes, yet little is known about the specific mechanisms by which predators make decisions during tracking that lead them to a source. This dissertation advances the current knowledge of plume tracking behavior by examining blue crab tracking behavior over a large range of bed-roughnesses (thereby manipulating ambient levels of turbulence), and interpreting these results with respect to chemical signal structure derived from separate examinations of plume characteristics as determined by planar laser induced fluorescence (PLIF). Foraging success and the speed of blue crabs attempting to locate the odorant source both decline consistently with increasing bed roughness. In contrast, steering (path linearity) appears unaffected by bed roughness induced turbulence. The spatial arrangement of blue crab chemosensors combined with the three-dimensional structure of odorant plumes accounts for the differential effects of turbulence on the speed and success of crab tracking behavior. Separate examinations of tracking behavior and plume properties cannot directly examine hypotheses concerning the utility of specific chemical signal properties. In order to make a direct link between cue and behavior, three-dimensional laser induced fluorescence (3DLIF) was used to analyze three-dimensional plume structure and concentration of odor filaments that reach blue crab sensory structures. The corresponding tracking behavior was simultaneously recorded and then analyzed with a motion analysis system. These data provide the most comprehensive examination of odor signal input-behavioral output functions for animals in turbulent plumes. Crabs do not react differentially in response to the absolute concentration of antennule spikes above threshold at their antennules but do show a state-dependent acceleration response to antennule spikes. Signals arriving at the leg sensors of blue crabs help mediate upstream motion and signal change across a single set of leg sensors is sufficient to induce turning during upstream motion. Blue crabs decrease the height of their antennules in correspondence with changing plume properties as they approach the source and the timing of signals arriving at the antennules appears to affect upstream motion.

Until now, car ownership has been a symbol of wealth and personal freedom. The high value of the car in society has been enforced by the powerful automotive industry with their well-funded marketing budgets. Currently, there are one billion cars worldwide, possibly increasing to 2,8 billion by 2050. However, the awareness of the negative consequences of car ownership on the environment, cities, and individuals in terms of reduced personal and financial freedom is increasing. The trend towards collaborative consumption involving activities like sharing and trading is leading to a shift from ownership to the access of goods and services. In this context, carsharing is receiving more and more attention and the number of users for B2C carsharing models is increasing exponentially. The least-developed business model with the biggest opportunities in terms of environmental benefits is peer-to-peer carsharing (P2P carsharing). Providers face daunting problems in reaching critical mass, due to a lack of consumer acceptance. Academic contributions on the topic are rare. The goal of this dissertation is to capture the acceptance factors, barriers and success factors for P2P carsharing. Additionally, the phenomenon is explored within the perspective of disruptive technologies, including the connected car and autonomous vehicles. A comprehensive literature review including collaborative consumption, carsharing, and in particular P2P carsharing, has been conducted. A mixed-method approach has been used. Qualitative interviews with leading academic and industry experts in the field of collaborative consumption and shared mobility, as well as a focus group discussion, have been executed. In the quantitative survey, the identified factors have been integrated into the Technological Acceptance Model (TAM), the theoretical foundation of the work. A representative survey was conducted in Austria with 801 respondents. The results were generated by applying a partial least squares analysis. Results show that the TAM model, including the extensions, appeared to be applicable. In particular, people with an innovative mindset are open to the usage of the business model. The main motivational factors for participating are economic, utility and enjoyment. The personal attachment towards one's own car remains one of the main barriers, next to fear of sharing and loss of convenience. Success factors in increasing acceptance are - among others - trust, value-added services and keyless car exchange. The preferred usage model for autonomous vehicles tends to be ownership. Even though the awareness of P2P carsharing is rather low among the Austrian population, 13,6% state that they would use the service. Sharing one's privately owned autonomous vehicle with others met with even higher levels of approval from the respondents. The extension of the TAM, as well as its application to a new field outside information system (IS) research, can be viewed as the major academic contribution of this work. Practical implications for P2P carsharing providers and the automotive industry include strategic recommendations regarding the current disruptive trends within the automotive industry. In particular, concrete measures have been identified to scale the business model by addressing new customers and reducing the identified barriers by providing extensive knowledge of relevant success factors.

In this thesis, a combined feedforward and feedback controller for improved path tracking on autonomous heavy-duty vehicles is designed and implemented. The steering wheel is controlled in order to follow a reference curvature, computed by a higher-level MPC, responsible for minimizing the distance to a planned path. The steering dynamics, from steering wheel via wheel angles, to a measurable vehicle curvature, is modeled, and a conversion from desired curvature gain to input angle to the steering wheel is derived. Tests with an autonomous Scania R580 show that the desired curvature can be followed with satisfactory small error, both in a designed slalom path and on a more generic test track. By utilizing future curvature values computed by the MPC, a non-causal feedforward controller can reduce the delay from input to the steering wheel to a measured response in curvature, by almost two thirds, compared to the currently implemented solution. Compared to an open-loop control design, tests in simulation show that a feedback controller can reduce errors in curvature gain. However, with the identified steering dynamics and the improved conversion from steering wheel angle to curvature, no further improvement in the curvature gain was seen when implementing the feedback controller in the test vehicle. Care must also be taken not to introduce instability in the system when the feedback controller is implemented in series with a high-level MPC. / Den här rapporten beskriver design och implementering av en regulator med kombinerad framkoppling och återkoppling för förbättrad banföljning av autonoma tunga fordon. Fordonets ratt styrs för att följa en kurvaturreferens beräknad av en överordnad MPC, ansvarig för att minimera avståndet till en planerad bana. Dynamiken i styrningen, från ratten via hjulvinklarna till en mätbar kurvatur för fordonet, är modellerad. En översättning från önskad förstärkning av kurvatur till insignal för rattvinkeln är också framtagen. Tester utförda med en autonom Scania R580 visar att den önskade kurvaturen kan följas med tillfredsställande litet fel, både i en egendesignad slalombana och i en mer generisk testbana. Genom att utnyttja framtida referensvärden för kurvatur beräknade av MPC:n, kan en icke-kausal framkopplande regulator minska fördröjningen från insignal till ratten till en mätbar respons i fordonets kurvatur. Jämfört med den nuvarande lösningen minskas fördröjningen med nästan två tredjedelar. Jämfört med en öppen styrning visar tester i simulering att en återkoppling i regulatorn kan minska stationära fel i kurvatur. Med implementeringen av den identifierade styrdynamiken och den förbättrade översättningen från rattvinkel till kurvatur, syntes dock med återkoppling ingen ytterliggare förbättring i testfordonet. Implementering av den återkopplande regulatorn i serie med den överordnade MPC:n behöver också göras med omsorg för att inte introducera instabilitet i systemet.

Les véhicules dits intelligents actuellement développés par la plupart des constructeurs automobiles, ainsi que les véhicules autonomes nécessitent des informations sur le contexte dans lequel ils évoluent. Certaines de ces informations (par exemple la courbure de la route, la forme des intersections, les limitations de vitesses) sont fournies en temps réel par le système de navigation qui exploite les données de cartes routières numériques. Des défauts résultant de l’évolution du réseau routier ou d’imprécisions lors de la collecte de données peuvent être contenus dans ces cartes numériques et entraîner le dysfonctionnement des systèmes d’aide à la conduite. Les recherches menées dans cette thèse visent à rendre le véhicule capable d’évaluer, de manière autonome et en temps réel, l’intégrité des informations fournies par son système de navigation. Les véhicules de série sont désormais équipés d’un grand nombre de capteurs qui transmettent leurs mesures sur le réseau central interne du véhicule. Ces données sont donc facilement accessibles mais de faible précision. Le défi de cette thèse réside donc dans l’évaluation de l’intégrité des informations cartographiques malgré un faible degré de redondance et l’absence de données fiables. On s’adresse à deux types de défauts cartographiques : les défauts structurels et les défauts géométriques. Les défauts structurels concernent les connections entre les routes (intersections). Un cas particulier de défaut structurel est traité : la détection de ronds-points qui n’apparaissent pas dans la carte numérique. Ce défaut est essentiel car il est fréquent (surtout en Europe) et perturbe le fonctionnement des aides à la conduite. Les ronds-points sont détectés à partir de la forme typique de la trajectoire du véhicule lorsqu’il les traverse, puis sont mémorisés pour avertir les aides à la conduite aux prochains passages du véhicule sur la zone. Les imprécisions de représentation du tracé des routes dans la carte numérique sont quant à elles désignées comme défauts géométriques. Un formalisme mathématique est développé pour détecter ces défauts en comparant l’estimation de la position du véhicule d’après la carte à une autre estimation indépendante de la carte. Cette seconde estimation pouvant elle aussi être affectée par un défaut, les anciens trajetsdu véhicule sur la même zone sont utilisés. Un test statistique est finalement utilisé pour améliorer la méthode de détection de défauts géométriques dans des conditions de mesures bruitées. Toutes les méthodes développées dans le cadre de cette thèse sont évaluées à l’aide de données réelles. / Several Intelligent Vehicles capabilities from Advanced Driving Assistance Systems (ADAS) to Autonomous Driving functions depend on a priori information provided by navigation maps. Whilst these were intended for driver guidance as they store road network information, today they are even used in applications that control vehicle motion. In general, the vehicle position is projected onto the map to relate with links in the stored road network. However, maps might contain faults, leading to navigation and situation understanding errors. Therefore, the integrity of the map-matched estimates must be monitored to avoid failures that can lead to hazardous situations. The main focus of this research is the real-time autonomous evaluation of faults in navigation maps used in intelligent vehicles. Current passenger vehicles are equipped with proprioceptive sensors that allow estimating accurately the vehicle state over short periods of time rather than long trajectories. They include receiver for Global Navigation Satellite System (GNSS) and are also increasingly equipped with exteroceptive sensors like radar or smart camera systems. The challenge resides on evaluating the integrity of the navigation maps using vehicle on board sensors. Two types of map faults are considered: Structural Faults, addressing connectivity (e.g., intersections). Geometric Faults, addressing geographic location and road geometry (i.e. shape). Initially, a particular structural navigation map fault is addressed: the detection of roundabouts absent in the navigation map. This structural fault is problematic for ADAS and Autonomous Driving. The roundabouts are detected by classifying the shape of the vehicle trajectory. This is stored for use in ADAS and Autonomous Driving functions on future vehicle trips on the same area. Next, the geometry of the map is addressed. The main difficulties to do the autonomous integrity monitoring are the lack of reliable information and the low level of redundancy. This thesis introduces a mathematical framework based on the use of repeated vehicle trips to assess the integrity of map information. A sequential test is then developed to make it robust to noisy sensor data. The mathematical framework is demonstrated theoretically including the derivation of definitions and associated properties. Experiments using data acquired in real traffic conditions illustrate the performance of the proposed approaches.