O desenvolvimento tecnológico e o elevado investimento em tecnologias de veículos \"inteligentes\" vão, provavelmente, transformar veículos autônomos em realidade em alguns anos. A inserção de inteligência em veículos rodoviários visa obter uma redução nos acidentes de trânsito devido à mitigação de erros cometidos por motoristas humanos, graças à sua substituição por máquinas. Além disso, os veículos autônomos devem ser capazes de mitigar os perigos existentes nos sistemas de transporte rodoviário, sem criar novos riscos. Assim, é importante a pesquisa de como garantir a segurança crítica (safety) nesse novo cenário. Algumas pesquisas nesta área já vêm sendo desenvolvidas, porém elas não mostram como projetar um sistema veicular autônomo no qual se possa aplicar métodos já existentes para analisar e garantir níveis de segurança adequados em tais veículos. Frente a isso, este trabalho de mestrado desenvolve uma proposta que visa facilitar o desenvolvimento e a análise dessa nova classe de veículos, além de assegurar níveis de segurança crítica adequados aos veículos autônomos. A proposta é representada por um sistema denominado Controle Veicular Autônomo (CVA), o qual foi desenvolvido sob o conceito de Sistemas de Transporte Inteligentes (STI). O sistema CVA é formado por duas camadas, uma de operação (Operação Veicular Autônoma - OVA), responsável pela condução do veículo e outra de proteção (Proteção Veicular Autônoma - PVA). A ideia principal é que se utilize a camada PVA para a prevenção de acidentes. A camada PVA foi desenvolvida e testada em um ambiente de simulação, considerando um Estudo de Caso. Observou-se que, conforme previsto, o sistema CVA, por possuir uma camada voltada para a proteção veicular, conseguiu evitar diversas situações de colisões entre veículos. / Technological development and the massive investment in \'intelligent\' vehicle technologies are likely to turn autonomous vehicles into reality in a few years. The insertion intelligence in road vehicles aims to obtain a reduction in traffic accidents due to the mitigation of errors committed by human drivers, thanks to their replacement by machines. In addition, autonomous vehicles should be able to mitigate hazards in road transportation systems without creating new risks. Thus, It is important to study how to ensure safety in this new scenario. Some research in this area has already been developed, but they do not show how to design properly an autonomous vehicle system in which existing methods can be applied to analyze and guarantee adequate levels of safety in such vehicles. As a result, this master\'s work develops a proposal that aims to facilitate the development and analysis of this new class of vehicles, in addition to ensuring levels of critical safety appropriate to autonomous vehicles. The proposal is represented by a system called Autonomous Vehicle Control (CVA), which was developed under the concept of Intelligent Transport Systems (STI). The CVA system is formed by two layers, one of operation (Autonomous Vehicle Operation - OVA), responsible for the driving of the vehicle and another one of protection (Autonomous Vehicle Protection - PVA). The main idea is to use the PVA layer for the prevention of accidents. The PVA layer was developed and tested in a simulation environment, considering a Case Study. It was observed that, as predicted, the CVA system, because it has a layer aimed at vehicular protection, was able to avoid several collision situations between vehicles.

Model-based development is one of the most significant areas in recent research and development activities in the field of automotive industry. As the field of software engineering is evolving, model based development is gaining more and more importance in academia and industry. Therefore, it is desirable to have techniques that are able to identify anomalies in system models during the analysis and design phase instead of identifying them in development phase where it is difficult to detect them and a lot of time, effort and resources are required to fix them. Model checking is a formal verification technique that facilitates the identification of defects in system models during early stages of system development. There are a lot of tools in academia and industry that provide the automated support for model checking.  In this master thesis a vehicle control system of Scania the Fuel Level Display System is modeled in two different model checking tools; Simulink Design Verifier and UPPAAL. The requirements that are to be satisfied by the system model are verified by both tools. After verifying the requirements against the system model and checking the model against general design errors, it is established that the model checking can be effectively used for detecting the design errors in early development phases and can help developing better systems. Both the tools are analyzed depending upon the features supported. Moreover, relevance of model checking is studied with respect to ISO 26262 standard.

Pour répondre à l’augmentation du trafic aérien mondial et à l’amélioration de la sécurité sur les plateformes aéroportuaires, le secteur aéronautique développe de nouveaux systèmes permettant de tendre vers l’autonomie complète de l’avion pendant les phases de roulage au sol. Le thème de ce travail de thèse concerne l’automatisation du pilotage de l’avion au sol et le développement d’une architecture de commande multivariable permettant de superviser l’ensemble des systèmes impliqués dans ce mode de déplacement : les systèmes de motorisation et de freinage des roues principales et le système d’orientation du train avant. Après une modélisation détaillée de la dynamique du système et une analyse des problématiques induites par ses non-linéarités, une architecture de commande globale est proposée. L’asservissement de la dynamique angulaire des roues, pendant les phases d’accélération et de freinage, est assuré par une loi de commande linéaire robuste aux incertitudes, synthétisée à l’aide de la technique Q.F.T. Le pilotage de la dynamique latérale du véhicule est réalisé au moyen d’un correcteur hybride feedforward-feedback. Une commande modale au premier ordre est alors mise en oeuvre afin de synthétiser un régulateur non-linéaire par planification de gains (gain-scheduling). L’ensemble des boucles d’asservissement de l’architecture est finalement validé en réalisant un suivi automatique de trajectoire à l’aide d’une commande géométrique nommée follow the carrot. Les simulations représentatives de l’utilisation réelle de l’avion démontrent des performances satisfaisantes et permettent de valider l’ensemble des solutions proposées. / In the context of worldwide air traffic growth and airport security improvement, the main aeronautics actors are currently investigating new systems, strived for autonomously piloting the aircraft while taxiing ground-borne. The present thesis deals with aircraft taxiing control and the design of a multivariable control architecture aimed at supervising all the ground acting systems: driving and braking systems of main wheels and the nose landing gear steering system. A global control architecture is introduced after a detailed modelling of the system dynamics and an analysis of the issues induced by the nonlinearities. A linear Q.F.T controller is synthesised to ensure robust control against uncertainties of the wheel angular dynamics, in both driving and braking operations. The vehicle lateral dynamics is controlled by means of a feedforward-feedback hybrid controller. The latter includes a nonlinear gain-scheduled controller designed by a modal approach. All the architecture control loops are finally validated in a high level path following control, achieved with the “follow the carrot” geometric method. A set of representative simulations show the overall good performances and validate the whole proposed solution.

No description available.

The development of autonomous vehicles is progressing rapidly through extensive efforts by the automotive industry and researchers. One of the key factors for the adoption of autonomous driving technology is motion comfort and the ability to engage in non-driving tasks such as reading, socialising, and relaxing without experiencing motion sickness while travelling. Therefore, for the full success of autonomous vehicles, it is necessary to learn how to design and control the vehicles to mitigate motion sickness for the passengers.  This thesis aims to investigate methods for prediction of motion sickness in autonomous vehicles and how to mitigate it using vehicle dynamics based solutions, with an emphasis on trajectory planning. As a first step, a review and evaluation of existing motion sickness prediction methods were performed. The review highlighted the importance of accurate motion sickness assessment in the early phases of autonomous vehicle design. Two chosen methods (ISO 2631-based and sensory conflict theory-based) were evaluated to estimate individual motion sickness feelings using measured data and subjective assessment ratings from field tests. It can be concluded that the methods can be adjusted to predict individual motion sickness feelings, as shown by the comparison with the experimental data. To continue the work, a review of vehicle dynamics based motion sickness mitigation methods for autonomous vehicles was performed. Several chassis control strategies in literature like active suspension, rear-wheel steering and torque distribution have demonstrated the potential help to reduce motion sickness. Another effective approach to mitigate motion sickness in autonomous vehicles is to regulate vehicle speed and path using trajectory planning which was chosen to be further investigated. The trajectory planning was constructed as an optimisation problem where there is a trade-off between motion sickness and manoeuvre time. The impact of the trajectory planning algorithm to reduce motion sickness was analysed by simulating two different vehicle models in specific test manoeuvres. The results indicate that driving style has a significant influence on motion sickness and trajectory planning algorithms should be carefully designed to find a good balance between journey time and motion sickness. The research presented in this thesis contributes to the development of methodologies for predicting and mitigating motion sickness in autonomous vehicles, helping to achieve the goal of ensuring their overall success. / Utvecklingen av autonoma fordon går snabbt framåt tack vare omfattande insatser från fordonsindustrin och forskare. En av de viktigaste faktorerna för införandet av teknik för autonom körning är åkkomfort och möjligheten att ägna sig åt andra saker än körning, som att läsa, umgås och koppla av, utan att drabbas av åksjuka under resan. För att autonoma fordon ska lyckas fullt ut är det därför nödvändigt att förstå hur man utformar och styr fordonen för att minska risken för att passagerarna drabbas av åksjuka.  Denna licentiatuppsats syftar till att undersöka hur åksjuka kan förutsägas i vägfordon och hur den kan reduceras med hjälp av fordonsdynamikbaserade lösningar, med tonvikt på trajektorieplanering. Som ett första steg genomfördes en granskning och utvärdering av befintliga metoder för åksjukeprediktion. Granskningen belyste vikten av en korrekt bedömning av åksjuka i de tidiga faserna av autonom fordonsdesign. Två valda metoder (ISO 2631-baserad och sensorisk konfliktbaserad) utvärderades för att uppskatta individuell åksjuka med hjälp av uppmätta data och subjektiva bedömningar från fälttester. Slutsatsen är att metoderna kan justeras för att förutsäga individuell åksjuka, vilket framgår av jämförelsen med experimentella data. För att fortsätta arbetet gjordes en genomgång av fordonsdynamikbaserade metoder för att minska åksjuka i autonoma fordon. Flera chassireglerstrategier i litteraturen, såsom aktiv fjädring, bakhjulsstyrning och drivmomentfördelning, har visat sig kunna bidra till att minska åksjuka. En annan effektiv metod för att minska åksjuka i autonoma fordon är att reglera fordonets hastighet och bana med hjälp av trajektorieplanering, vilket valdes att undersökas ytterligare. Trajektorieplaneringen konstruerades som ett optimeringsproblem där det finns en avvägning mellan åksjuka och manövertid. Effekten av trajektorieplaneringsalgoritmen för att minska åksjuka analyserades genom att simulera två olika fordonsmodeller i specifika testmanövrar. Resultaten indikerar att körstil har en betydande inverkan på åksjuka och att algoritmer för trajektorieplanering bör utformas noggrant för att hitta en bra balans mellan restid och åksjuka. Forskningen som presenteras i denna uppsats bidrar till utvecklingen av metoder för att förutsäga och mildra åksjuka i autonoma fordon, vilket hjälper till att uppnå målet att säkerställa deras framgång.

Advanced Driver Assistance Systems (ADAS) and Autonomous Ground Vehicles (AGV) have the potential to increase road transportation safety, environmental gains, and passenger comfort. The advent of Electric Vehicles has also facilitated greater flexibility in powertrain architectures and control capabilities. Path Tracking controllers that provide steering input are used to execute lateral maneuvers or model the response of a vehicle during cornering. Direct Yaw Control using Torque Vectoring has the potential to improve vehicle's transient cornering stability and modify its steady state handling characteristics during lateral maneuvers. In the first part of this thesis, the transient dynamics of an existing baseline Path Tracking controller is improved using a transient Torque Vectoring algorithm. The existing baseline Path Tracking controller is evaluated, using a linearized system, for a range of vehicle and controller parameters. The effect of implementing transient Torque Vectoring along with the baseline Path Tracking controller is then studied for the same parameter range. The linear analysis shows, in both time and frequency domain, that the transient Torque Vectoring improves vehicle response and stability during cornering. A Torque Vectoring controller is developed in Linear Adaptive Model Predictive Control framework and it's performance is verified in simulation using Simulink and CarSim. The second part of the thesis analyzes the tradeoff enabled by steady state Torque Vectoring between improved limit handling capability through optimal tire force allocation and drivability demonstrated by understeer gradient. Optimal tire force allocation prescribes equal usage in all four tires during maneuvers. This is enabled using steering and Torque Vectoring. An analytical proof is presented which demonstrates that implementation of this optimal tire force allocation results in neutralsteering handling characteristics for the vehicle. The optimal tire force allocation strategy is formulated as a minimax optimization problem. A two-track vehicle model is simulated for this strategy, and it verified the analytical proof by displaying neutralsteering behavior. / Master of Science / Advanced Driver Assistance Systems (ADAS) and Autonomous Ground Vehicles (AGVs) have the potential to increase road transportation safety, environmental gains, passenger comfort and passenger productivity. The advent of Electric Vehicles (EVs) has also facilitated greater flexibility in powertrain configurations and capabilities that facilitate the implementation of Torque Vectoring (TV), which is a method of applying differential torques to laterally opposite wheels to enhance the cornering performance of ground vehicles. Path Tracking (PT) controllers that provide steering input to the vehicles are traditionally used for lateral control in AGVs and ADAS features. The goal of this thesis is to develop Torque Vectoring algorithms to improve a vehicle's stability and shape its steady state behaviour through a corner during low lateral acceleration maneuvers. An existing baseline Path Tracking controller is selected and evaluated. The effect of implementing Torque Vectoring along with this Path Tracking controller is studied and it is found to improve the stability of the vehicle during cornering. This is verified in simulation by designing and implementing the Torque Vectoring algorithm. Finally, a Torque Vectoring strategy is proposed to manage the handling of the vehicle during low acceleration cornering.

In 2004, students at the University of Guelph designed and constructed an all-wheel-drive Formula SAE vehicle for competition. It utilized an electronically-controlled, hydraulic-actuated limited slip center coupling from Haldex Traction Ltd, to transfer torque to the front wheels. The initial control system design was not comprehensively conceived, so there was a need for a thoroughly developed control system for the all-wheel-drive actuator augmented with commonly available sensors and a low cost controller. This thesis presents a novel all-wheel-drive active torque transfer controller using a neural network estimated slip angle velocity. This controller specifically targets a racing vehicle by allowing rapid direction changes for maneuverability but damping slip angle changes for increased controllability. The slip angle velocity estimate was able to track the actual simulated value it was trained against with excellent phase matching but with some offsets and phantom spikes. Using the estimated slip angle velocity for control realized smooth control output, excellent stability, and a fast turn-in yaw response on par with rear-wheel-drive configurations. A full vehicle simulation with software-in-the-loop testing for control software was also developed to aid the system design process and avoid vehicle run time for tuning. This design flow should significantly decrease development time for controls algorithm work and help increase innovation within the team.

Cette thèse est consacrée à la conception et au développement d’une plateforme multi-agent, en réalité virtuelle, de pilotage de véhicules intelligents pour la simulation du comportement microscopique du trafic. D’abord, un système de simulation intelligent des véhicules en réalité virtuelle (VR-ISSV), basé sur les multi-agents, est proposé : c’est un système modulaire hiérarchique de modélisation et de simulation, comprenant une couche matérielle, réseau et système d’exploitation ; une couche de gestion de la visualisation ; une couche de multi-agents et une couche d’interface homme-machine. Ensuite, pour le modèle d’agent du véhicule intelligent, un paradigme de conception décentralisée est utilisé basé sur l’approche multi-contrôleurs, où le comportement du suivi des véhicules et le comportement du dépassement des véhicules sont réalisées par coordination entre multi-contrôleurs. L’agent d’environnement est construit en tenant compte de l’interaction entre les véhicules et l’environnement naturel synthétique. Un système d’information géographique (GIS) est par ailleurs utilisé afin de définir l’agent d’environnement. Enfin, pour assurer la sécurité dans les manœuvres microscopiques du trafic, plusieurs contrôleurs du véhicule intelligent, adaptés à l’environnement complexe, sont considérés. Les contrôleurs, basés sur la logique floue, sont proposés pour envoyer les commandes appropriées aux actionneurs du véhicule - volant de direction, accélérateur, frein... Les modèles de comportement microscopique du trafic basé sur l’agent de véhicule intelligent sont étudiés considérant différents scénarios et l’environnement / This PhD thesis is dedicated to the modeling and simulation of microscopic traffic behavior in virtual reality system, with the intent of providing a new approach to effectively ensure traffic safety. At first, Virtual Reality Intelligent Simulation System of Vehicles (VR-ISSV), based on multi-agent, is proposed to simulate the intelligent microscopic traffic, which is a hierarchical modular modeling and simulation system consisting of hardware, network and operating system layers, visualization management layer, multi-agent layer, human-machine interface layer. The multi-agent layer includes entity agents (intelligent vehicle agents and around vehicle agents), service agent and environment agent. Second, for the intelligent vehicle agent model, a decentralized design paradigm is used for developing the multi-controller based intelligent vehicle, whereby the car following behavior and the overtaking behavior could be realized by the coordination of the multi-controller. The environment agent is constructed based on the conception of Synthetic Natural Environment (SNE), taking into account the interaction between the vehicles and the natural environment. Geographic Information System (GIS) is used to establish environment agent. Finally, to ensure the safety in microscopic traffic maneuver, the intelligent vehicle controllers adapting to complex environment are considered. Fuzzy logic based controllers are designed for sending the appropriate outputs to the vehicle’s actuators – the steering wheel and the throttle/brake pedals. Microscopic traffic behavior models based on the intelligent vehicle agent involving environment are studied

No description available.

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science