Dissertations / Theses on the topic 'Automotive mechatronics and autonomous systems'

The increasing usage of electronics and software in a modern automobile enables realization of many advanced features. One such feature is autonomous driving. Autonomous driving means that a human driver’s intervention is not required to drive the automobile; rather, theautomobile is capable of driving itself. Achieving automobile autonomyrequires research in several areas, one of which is the area of automotive electrical/electronics (E/E) architectures. These architectures deal with the design of the computer hardware and software present inside various subsystems of the vehicle, with particular attention to their interaction and modularization. The aim of this thesis is to investigate how automotive E/E architectures should be designed so that 1) it ispossible to realize autonomous features and 2) a smooth transition canbe made from existing E/E architectures, which have no explicit support for autonomy, to future E/E architectures that are explicitly designed for autonomy.The thesis begins its investigation by considering the specific problem of creating autonomous behavior under cooperative driving condi-tions. Cooperative driving conditions are those where continuous wireless communication exists between a vehicle and its surroundings, which consist of the local road infrastructure as well as the other vehicles in the vicinity. In this work, we define an original reference architecture for cooperative driving. The reference architecture demonstrates how a subsystem with specific autonomy features can be plugged into an existing E/E architecture, in order to realize autonomous driving capabilities. Two salient features of the reference architecture are that it isminimally invasive and that it does not dictate specific implementation technologies. The reference architecture has been instantiated on two separate occasions and is the main contribution of this thesis. Another contribution of this thesis is a novel approach to the design of general, autonomous, embedded systems architectures. The approach introduces an artificial consciousness within the architecture, that understands the overall purpose of the system and also how the different existing subsystems should work together in order to meet that purpose.This approach can enable progressive autonomy in existing embedded systems architectures, over successive design iterations.

QC 20130412

Integrated camera systems for increasing safety and maneuverability are becoming increasingly common for heavy vehicles. One problem with heavy vehicles today is that there are blind spots where the driver has no or very little view. There is a great demand on increasing the safety and helping the driver to get a better view of his surroundings. This can be achieved by a sophisticated camera system, using cameras with wide field of view, that could cover dangerous blind spots. This master thesis aims to investigate and develop a prototype solution for a camera system consisting of two fisheye cameras. The solution covers both hardware choices and software development including camera calibration and image stitching. Two different fisheye camera calibration toolboxes are compared and their results discussed, with the aim to find the most suitable for this application. The result from the two toolboxes differ in performance, and the result from only one of the toolboxes is sufficient for image stitching.

With all the advancements in autonomous and connected cars, there is a developing body of research around the security and robustness of driving automation systems. Attacks and mitigations for said attacks have been explored, but almost always solely in software simulations. For this thesis, I led a team to build the foundation for an open source platoon of scale semi-autonomous vehicles. This work will enable future research into implementing theoretical attacks and mitigations. Our 1/10 scale car leverages an Nvidia Jetson, embedded microcontroller, and sensors. The Jetson manages the computer vision, networking, control logic, and overall system control; the embedded microcontroller directly controls the car. A lidar module is responsible for recording distance to the preceding car, and an inertial measurement unit records the velocity of the car itself. I wrote the software for the networking, interprocess, and serial communications, as well as the control logic and system control.

Fully autonomous vehicles are expected to revolutionize transportation, reduce the cost of ownership, contribute to a cleaner environment, and prevent the majority of traffic accidents and related fatalities. Even though promising approaches for achieving full autonomy exist, developers and manufacturers have to overcome a multitude of challenged before these systems could find widespread adoption. This multiple case study explored the strategies some IT hardware and software developers of self-driving cars use to adapt traditional vehicle design frameworks to address consumer and regulatory requirements in autonomous vehicle designs. The population consisted of autonomous driving technology software and hardware developers who are currently working on fully autonomous driving technologies from or within the United States, regardless of their specialization. The theory of dynamic capabilities was the conceptual framework used for the study. Interviews from 7 autonomous vehicle hard and software engineers, together with 15 archival documents, provided the data points for the study. A thematic analysis was used to code and group results by themes. When looking at the results through the lens of dynamic capability theory, notable themes included regulatory uncertainty, functional safety, rapid iteration, and achieving a competitive advantage. Based on the findings of the study, implications for social change include the need for better regulatory frameworks to provide certainty, consumer education to manage expectations, and universal development standards that could integrate regulatory and design needs into a single approach.

The presence of electrical and electronic circuits in commercial trucks has increased at a very fast rate during recent decades. With advancements in embedded systems and the introduction of electric controls in the automotive industry, the design of complex electric systems for the vehicles has become one of the major design challenges. In the commercial truck industry, the development cycles are almost a decade long. Therefore, it is a big challenge to introduce a new architecture to accommodate the modern automotive technologies in the upcoming generation of trucks. Currently, the commercial truck industry relies highly on a federated electrical/electronic (E/E) architecture. In this architecture, Electronic Control Units (ECU) are responsible for computation and Input/Output operations. These ECUs are clustered into different domains based on their respective functions. However, these domains are not isolated from each other. These modules communicate with each other using a vehicular network, which is typically a controller area network in the current trucks. In the automotive industry, automation is increasing at a fast pace. As the level of automation increases, the need for high computation also increases, which increases the overall costs. This study aims to address this problem by introducing an integrated E/E architecture where all the computational power is concentrated at one place (or perhaps two or three places to allow for redundancy). This study proposes to introduce a lowcost replacement for the current ECUs with more limited computational power but with generic input/output interfaces. This thesis provides the reader with some background of the current E/E architecture of commercial trucks and introduces the reader to ECUs. Additionally, the relevant network architectures and protocols are explained. A potential solution, based upon the centralized computation based E/E architecture and its implementation are discussed followed by a detailed analysis of the replacements for ECUs. The result of this analysis, if adopted, should result in a reduction of manufacturing and design costs, as well as make the production and maintenance process easier. Moreover, this should also have environmental benefits by reducing fuel consumption.
Förekomsten av elektronik och elektriska kretsar I kommersiella lastbilar has ökat i en väldigt snabb takt under de senaste decennierna. Med framsteg inom inbyggda system och introduktionen av elektroniska styrsystem i fordonsindustrin så har komplexa elektroniska system blivit en av de största designutmaningarna. I den kommersiella lastbilsindustrin där utvecklingscyklerna är nästan ett decennium, är det en stor utmaning att introducera ny arkitektur som tillgodoser all den nya teknologin som införlivas i fordonet. För närvarande så förlitar sig den kommersiella lastbilsindustrin mycket på en federated elektrisk/elektronisk (E/E) arkitektur. I denna arkitektur är elektroniska styrenheter (ECU) ansvariga för beräkningar och I/O (Input/Output) operationer. Dessa ECU:er är samlade i olika domäner baserade på dess funktioner. Domänerna är dock inte isolerade från varandra. De här modulerna kommunicerar därför med varandra med hjälp av ett fordonsnätverk, typiskt en CAN (Controller Area Network) i nuvarande lastbilar. I fordonsindustrin ökar automatiseringen i en snabb fart. I takt med att automatiseringen ökar så ökar även behovet av snabba och energiintensiva beräkningar, vilket i sin tur ökar den totala kostnaden. Denna studie har som mål att adressera det här problemet genom att introducera en integrated E/E arkitektur där all beräkningskraft är koncentrerad till en plats (eller två eller tre platser för att tillåta överskott). Den här studien föreslår att introducera en ersättning av nuvarande ECU:er till en låg kostnad, med lägre beräkningskraft och generiska I/O gränssnitt. Studien föreslår också ersättningar av nuvarande fordonsnätverk. Den här uppsatsen förser läsaren med viss bakgrund till den nuvarande E/E arkitekturen för kommersiella lastbilar och introducerar läsaren till ECU:er. Dessutom förklaras de relevanta nätverksarkitekturerna och protokollen. En potentiell lösning som baseras på den integrated E/E arkitekturen och dess implementering diskuteras med fokus på en detaljerad analys av ersättningarna till ECU:er. Resultatet av den här analysen skulle, om den adopteras, medföra minskning av tillverknings- och designkostnader samt leda till en förenkling av produktion och underhåll. Utöver det så bör det även ha miljöfördelar genom minskad bränsleförbrukning.

Design, production and development of individual mini/micro robots and then formation of their cooperative colony are the main topics of this thesis. The produced mini/micro robots are as small and light as possible. In addition, they are multifunctional (programmable), flexible and intelligent while maintaining a very low production cost. Mini/micro robots, called MinT-DB series are able to communicate with each other to work cooperatively. Moreover, these robots can be the basis for the future studies considering the application of artificial intelligence and modeling of live colonies in the nature. Traditional design, production and assembly techniques have been used widely up to now. However, none of them were related with the mini/micro scale. Therefore, this thesis can help people in understanding the difficulties of the design, production, and assembly of the mini/micro systems under the light of the reported science. In this thesis, instead of examining a specific application field of mini/micro robotic systems, a technology demonstrative work is carried out. Therefore, this thesis contributes to the mini/micro robotic technology, which is also very new and popular in today&
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s world, with the robots having the dimensions of 7.5x6x6 cm.

This master’s thesis deals with the design of systems for data collection which describe the driver’s behaviour in a car. This data is used to detect risky behaviour that the driver may commit due to inattention caused by the use of either lower or higher levels of driving automation. The thesis first describes the existing safety systems, especially in relation to the driver. Then it deals with the design of the necessary measuring scenes and the implementation of new systems based on the processing of input images which are obtained via the Intel RealSense D415 stereo camera. Every system is tested in a real vehicle environment. In the end the thesis contains an evaluation regarding the detection reliability of the created algorithms, it considers their shortcomings and possible improvements.

Afin de naviguer en autonomie un véhicule doit être capable de se localiser précisément par rapport aux bords de voie pour ne pas sortir de celle-ci et par rapport aux véhicules et piétons pour ne pas causer d'accident. Cette thèse traite de l'intérêt de la communication dans l'amélioration de la localisation des véhicules autonomes. La navigation autonome sur route est souvent réalisée à partir de coordonnées cartésiennes. Afin de mieux représenter la pose d'un véhicule relativement à la voie dans laquelle il circule, nous étudions l'utilisation de coordonnées curvilignes le long de chemins enregistrés dans des cartes. Ces coordonnées généralisent l'abscisse curviligne en y ajoutant un écart latéral signé par rapport au centre de la voie et une orientation relative au centre de cette voie en prenant en compte le sens de circulation. Une première approche de localisation coopérative est réalisée à partir de ces coordonnées. Une fusion de données à une dimension permet de montrer l'intérêt de la localisation coopérative dans le cas simplifié où l'écart latéral, l'orientation curviligne et la pose relative entre deux véhicules sont connus avec précision. Les problèmes de corrélation des erreurs dus à l'échange d'information sont pris en compte grâce à un filtre par intersection de covariance. Nous présentons ensuite à une méthode de perception de type ICP (Iterative Closest Point) pour déterminer la pose relative entre les véhicules à partir de points LiDAR et d'un modèle polygonal 2D représentant la forme du véhicule. La propagation des erreurs de poses absolues des véhicules à l'aide de poses relatives estimées avec leurs incertitudes se fait via des équations non linéaires qui peuvent avoir un fort impact sur la consistance. Les poses des différents véhicules entourant l'égo-véhicule sont estimés dans une carte locale dynamique (CLD) permettant d'enrichir la carte statique haute définition décrivant le centre de la voie et les bords de celle-ci. La carte locale dynamique est composée de l'état de chaque véhicule communicant. Les états sont fusionnés en utilisant un algorithme asynchrone, à partir de données disponibles à des temps variables. L'algorithme est décentralisé, chaque véhicule calculant sa propre CLD et la partageant. Les erreurs de position des récepteurs GNSS étant biaisées, une détection de marquages est introduite pour obtenir la distance latérale par rapport au centre de la voie afin d'estimer ces biais. Des observations LiDAR avec la méthode ICP permettent de plus d'enrichir la fusion avec des contraintes entre les véhicules. Des résultats expérimentaux illustrent les performances de cette approche en termes de précision et de consistance
To be able to navigate autonomously, a vehicle must be accurately localized relatively to all obstacles, such as roadside for lane keeping and vehicles and pedestrians to avoid causing accidents. This PhD thesis deals with the interest of cooperation to improve the localization of cooperative vehicles that exchange information. Autonomous navigation on the road is often based on coordinates provided in a Cartesian frame. In order to better represent the pose of a vehicle with respect to the lane in which it travels, we study curvilinear coordinates with respect to a path stored in a map. These coordinates generalize the curvilinear abscissa by adding a signed lateral deviation from the center of the lane and an orientation relative to the center of the lane taking into account the direction of travel. These coordinates are studied with different track models and using different projections to make the map-matching. A first cooperative localization approach is based on these coordinates. The lateral deviation and the orientation relative to the lane can be known precisely from a perception of the lane borders, but for autonomous driving with other vehicles, it is important to maintain a good longitudinal accuracy. A one-dimensional data fusion method makes it possible to show the interest of the cooperative localization in this simplified case where the lateral deviation, the curvilinear orientation and the relative positioning between two vehicles are accurately known. This case study shows that, in some cases, lateral accuracy can be propagated to other vehicles to improve their longitudinal accuracy. The correlation issues of the errors are taken into account with a covariance intersection filter. An ICP (Iterative Closest Point) minimization algorithm is then used to determine the relative pose between the vehicles from LiDAR points and a 2D polygonal model representing the shape of the vehicle. Several correspondences of the LiDAR points with the model and different minimization approaches are compared. The propagation of absolute vehicle pose using relative poses with their uncertainties is done through non-linear equations that can have a strong impact on consistency. The different dynamic elements surrounding the ego-vehicle are estimated in a Local Dynamic Map (LDM) to enhance the static high definition map describing the center of the lane and its border. In our case, the agents are only communicating vehicles. The LDM is composed of the state of each vehicle. The states are merged using an asynchronous algorithm, fusing available data at variable times. The algorithm is decentralized, each vehicle computing its own LDM and sharing it. As the position errors of the GNSS receivers are biased, a marking detection is introduced to obtain the lateral deviation from the center of the lane in order to estimate these biases. LiDAR observations with the ICP method allow to enrich the fusion with the constraints between the vehicles. Experimental results of this fusion show that the vehicles are more accurately localized with respect to each other while maintaining consistent poses

Stringent regulatory requirements and modern diesel engine technologies have engaged automotive manufacturers and researchers in accurately predicting and controlling diesel engine-out emissions. As a result, engine control systems have become more complex and opaquer, increasing the development time and costs. To address this challenge, Model-based control methods are an effective way to deal with the criticality of the system study and controls. And physics-based combustion engine modeling is a key to achieve it. This thesis focuses on development and validation of a physics-based model for both engine and emissions using model-based design tools from MATLAB & Simulink. Engine model equipped with exhaust gas circulation and variable geometry turbine is adopted from the previously done work which was then integrated with the combustion and emission model that predicts the heat release rates and NO_x emission from engine. Combustion model is designed based on the mass fraction burnt from CA10 to CA90 and then NO_x predicted using the extended Zeldovich mechanism. The engine models are tuned for both steady state and dynamics test points to account for engine operating range from the performance data. Various engine and combustion parameters are estimated using parameter estimation toolbox from MATLAB and Simulink by applying least squared solver to minimize the error between measured and estimated variables. This model is validated against the virtual engine model developed in GT-power for Cummins 6.7L turbo diesel engine. To account the harmonization of the testing cycles to save engine development time globally, a world harmonized stationary cycle (WHSC) is used for the validation. Sub-systems are validated individually as well as in loop with a complete model for WHSC. Engine model validation showed promising accuracy of more than 88.4 percent in average for the desired parameters required for the NO_x prediction. NO_x estimation is accurate for the cycle except warm up and cool down phase. However, NO_x prediction during these phases is limited due to actual NO_x measured data for tuning the model for real time NO_x estimation. Results are summarized at the end to compare the trend of NO_x estimation from the developed combustion and emission model to show the accuracy of in-cylinder parameters and required for the NO_x estimation.

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.

Increase in the awareness environmental conservation is leading the automotive industry into the adaptation of alternatively fueled vehicles. Electric, Fuel-Cell as well as Hybrid-Electric vehicles focus on this research area with aim to efficiently utilize vehicle powertrain as the first step. Energy and Power Management System control strategies play vital role in improving efficiency of any hybrid propulsion system. However, these control strategies are sensitive to the dynamics of the powertrain components used in the given system. A kinematic mathematical model for Plug-in Hybrid Electric Vehicle (PHEV) has been developed in this study and is further optimized by determining optimal power management strategy for minimal fuel consumption as well as NOx emissions while executing a set drive cycle. A multi-objective optimization using weighted sum formulation is needed in order to observe the trade-off between the optimized objectives. Particle Swarm Optimization (PSO) algorithm has been used in this research, to determine the trade-off curve between fuel and NOx. In performing these optimizations, the control signal consisting of engine speed and reference battery SOC trajectory for a 2-hour cycle is used as the controllable decision parameter input directly from the optimizer. Each element of the control signal was split into 50 distinct points representing the full 2 hours, giving slightly less than 2.5 minutes per point, noting that the values used in the model are interpolated between the points for each time step. With the control signal consisting of 2 distinct signals, speed and SOC trajectory, as 50 element time variant signals, a multidimensional problem was formulated for the optimizer. Novel approaches to balance the optimizer exploration and convergence, as well as seeding techniques are suggested to solve the optimal control problem. The optimization of each involved individual runs at 5 different weight levels with the resulting cost populations being compiled together to visually represent with the help of Pareto front development. The obtained results of simulations and optimization are presented involving performances of individual components of the PHEV powertrain as well as the optimized PMS strategy to follow for given drive cycle. Observations of the trade-off is discussed in the case of Multi-Objective Optimizations.

The miniaturization and thinning of wearable, soft robotics and medical devices are soon to require higher performance modeling as the physical flexibility causes direct impacts on the electrical characteristics of the circuit – changing its behavior. As a representative flexible electronic component, the organic field effect transistor (OFET) has attracted much attention in its manufacturing as well as applications. However, as the strain and stress effects are integrated into multiphysics modelers with deeper interactions, the computational complexity and accuracy of OFET modeling is resurfacing as a limiting bottleneck.

The dissertation was organized into three interrelated studies. In the first study, the Mass-Spring-Damper (MSD) model for an inverted staggered thin film transistor (TFT) was proposed to investigate the TFT’s internal stress/strain fields, and the strain effects on the overall characteristics of the TFT. A comparison study with the finite element analysis (FEA) model shows that the MSD model can reduce memory usage and raises the computational convergence speed for rendering the same results as the FEA. The second study developed the generalized solid-state model by incorporating the density of trap states in the band structure of organic semiconductors (OSCs). The introduction of trap states allows the generalized solid-state model to describe the electrical characteristics of both inorganic TFTs and organic field-effect transistors (OFETs). It is revealed through experimental verification that the generalized solid-state model can accurately characterize the bending induced electrical properties of an OFET in the linear and saturation regimes. The third study aims to model the transient and steady-state dynamics of an arbitrary organic semiconductor device under mechanical strain. In this study, the fractional drift-diffusion (Fr-DD) model and its computational scheme with high accuracy and high convergence rate were proposed. Based on simulation and experimental validation, the transconductance and output characteristics of a bendable OFET were found to be well determined by the Fr-DD model not only in the linear and saturation regimes, but also in the subthreshold regime.