<p>Genom att fusionera (sammanföra) data från olika sensorer kan ett resultat uppnås som ger mer än de enskilda sensorerna var för sig. Här utreds vilka sensorer och sensorfusionsmetoder som kan vara aktuella att använda för Scanias adaptiva farthållare (ACC). Den adaptiva farthållaren anpassar det egna fordonets hastighet inte bara till en förinställd hastighet utan även till framförvarande fordons hastighet. Scanias ACC-system använder idag en radar för måldetektering.</p><p>Det finns ett antal algoritmer och arkitekturer som passar för sensorfusionssystem beroende på nivån hos sensordatan och användningsområdet. Minstakvadratmetoder kan användas då data ska matchas mot en fysisk modell, ofta med lågnivådata. När tillgänglig data är på den nivån att den används direkt för att fatta beslut kan sannolikhetsmetoder användas. Intelligent fusion består av kognitiva modeller som avser härma den mänskliga beslutsprocessen. Till detta passar data på hög nivå.</p><p>Två lösningar, för två olika sensoruppsättningar, har tagits fram. Båda lösningarna är uppbyggda av bayesiska nätverk. Det första nätverket fusionerar data från den befintliga radarenheten med data från en kamera som detekterar vägmarkeringar. Resultaten visar att filbyten kan upptäckas tidigare i och med fusionen. Det andra nätverket använder sig av två radarenheter, den ursprungliga samt en likadan enhet till, vilket resulterar i ett bredare synfält. Nätverket avgör vilka mål hos respektive radar som kan anses vara samma matchade mål. Informationen kan användas för att öka redundansen i systemet samt för att upptäcka mål tidigare än förut.</p> / <p>By fusing data from different sensors a result can be achieved that is worth more than the data from each sensor by itself. Which sensors and sensor fusion methods that could be used in Scania's adaptive cruise control system (ACC) is investigated. The ACC system adapts the vehicle's speed not only to a driver decided set speed but also to the speed of preceding vehicles. Scania's ACC system uses a radar for target detection.</p><p>There exists a number of algorithms and architectures fit for use in sensor fusion systems. Which one to use depends on the level of the data to be fused and on the field of application. Least square methods are used when matching data to a physical model, data to be used is often at a low level. When working with data at decision level, probability methods are favored. Another example is intelligent fusion, cognitive methods intending to mimic the human decision process. Suitable data is data at a high level.</p><p>Two solutions, for two different sensor sets, are proposed. Both solutions are made out of Bayesian networks. The first one fuses data from the existing radar unit with data from a camera which detects lane markings. The results show that lane changes can be detected earlier thanks to the fusion. The second network uses two radar sensors of the same kind as the first, resulting in a wider field of view. The network decides which ones of each radars targets that are the same matching targets. This information could be used to increase the redundancy of the system and to detect targets earlier.</p>

An Adaptive Cruise Controller (ACC) is an extension of an ordinary cruise controller. In addition to maintaining a desired set velocity, an ACC can also maintain a desired time gap to the vehicle ahead. For this end, both the engine andthe brakes are controlled. The purpose with this thesis has been to develop control strategies for an ACC used in heavy vehicles. The focus of the work has been the methods used for switching between the use of engine and brake. Two different methods have been studied, a hybrid controller and an MPC-controller. For the hybrid controller, the main contribution has been to use the influence of the surroundings on the acceleration of the truck. This consists of several parts such as wind drag, road slope and rolling resistance. The estimated influence of the surroundings is used as a switch point between the use of engine and brakes. Ideally, these switch points give bumpless actuator switches. The interest in the MPC-controller as an alternative solution was to achieve automatic actuator switching, thus with no explicitly defined switch points. The MPC-controller is based on a model of the system including bounds on the control signals. Using this knowledge, the MPC-controller will choose the correct actuator for the current driving situation. Results from simulations show that both methods solve the actuator switch problem. The advantages with the hybrid controller are that it is implementable in a truck with the hardware used today and that it is relatively simple to parameterise. A drawback is that explicit switch points between the uses of the different actuators have to be included. The advantages with the MPC-controller are that no explicit switch points have to be introduced and that constraints and time delays on signals in the system can be handled in a simple way. Among the drawbacks, it can be mentioned that the variant of MPC, used in this thesis, is too complex to implement in the control system currently used in trucks. One further important drawback is that MPC demands a mathematical model of the system.

Development of a fuel economy model for light-duty and heavy-duty vehicles is part of the Texas Department of Transportation’s “Estimating Texas Motor Vehicle Operating Costs” project. A literature review for models that could be used to predict the fuel economy of light-duty and heavy-duty vehicles resulted in selection of coastdown coefficients to simulate the combined effects of aerodynamic drag and tire rolling resistance. For light-duty vehicles, advantage can be taken of the modeling data provided by the United States Environmental Protection Agency (EPA) for adjusting chassis dynamometers to allow accurate determination of emissions and fuel economy so that compliance with emissions standards and Corporate Average Fuel Economy (CAFE) regulations can be assessed. Initially, EPA provided vehicle-specific data that were relevant to a physics-based model of the forces at the tire-road interface. Due to some limitations of these model parameters, EPA now provides three vehicle-specific coefficients obtained from vehicle coastdown data. These coefficients can be related back to the original physics-based model of the forces at the tire-road interface, but not in a manner that allows the original modeling parameters to be extracted from the coastdown coefficients. Nevertheless, as long as the operation of a light-duty vehicle does not involve extreme acceleration or deceleration transients, the coefficients available from the EPA can be used to accurately predict fuel economy. Manufacturers of heavy-duty vehicles are not required to meet any sort of CAFE standards, and the engines used in heavy-duty vehicles, rather than the vehicles themselves, are tested (using an engine dynamometer) to determine compliance with emissions standards. Therefore, EPA provides no data that could be useful for predicting the fuel economy of heavy-duty vehicles. Therefore, it is necessary to perform heavyduty coastdown tests in order to predict fuel economy, and use these tests to develop vehicle-specific coefficients for the force at the tire-road interface. Given these coefficients, the fuel economy of a heavy-duty vehicle can be calculated for any driving schedule. The heavy-duty vehicle model developed for this project is limited to pre-2007 calendar year heavy-duty vehicles due to the adverse effects of emissions components that were necessary to comply with emissions standards that went into effect January 2007. / text

abstract: Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses several critical modeling, design and control objectives for ground vehicles. One central objective was to show how off-the-shelf (low-cost) remote-control (RC) “toy” vehicles can be converted into intelligent multi-capability robotic-platforms for conducting FAME research. This is shown for two vehicle classes: (1) six differential-drive (DD) RC vehicles called Thunder Tumbler (DDTT) and (2) one rear-wheel drive (RWD) RC car called Ford F-150 (1:14 scale). Each DDTT-vehicle was augmented to provide a substantive suite of capabilities as summarized below (It should be noted, however, that only one DDTT-vehicle was augmented with an inertial measurement unit (IMU) and 2.4 GHz RC capability): (1) magnetic wheel-encoders/IMU for(dead-reckoning-based) inner-loop speed-control and outer-loop position-directional-control, (2) Arduino Uno microcontroller-board for encoder-based inner-loop speed-control and encoder-IMU-ultrasound-based outer-loop cruise-position-directional-separation-control, (3) Arduino motor-shield for inner-loop motor-speed-control, (4)Raspberry Pi II computer-board for demanding outer-loop vision-based cruise- position-directional-control, (5) Raspberry Pi 5MP camera for outer-loop cruise-position-directional-control (exploiting WiFi to send video back to laptop), (6) forward-pointing ultrasonic distance/rangefinder sensor for outer-loop separation-control, and (7) 2.4 GHz spread-spectrum RC capability to replace original 27/49 MHz RC. Each “enhanced”/ augmented DDTT-vehicle costs less than 􀀀175 but offers the capability of commercially available vehicles costing over 􀀀500. Both the Arduino and Raspberry are low-cost, well-supported (software wise) and easy-to-use. For the vehicle classes considered (i.e. DD, RWD), both kinematic and dynamical (planar xy) models are examined. Suitable nonlinear/linear-models are used to develop inner/outer-loopcontrol laws. All demonstrations presented involve enhanced DDTT-vehicles; one the F-150; one a quadrotor. The following summarizes key hardware demonstrations: (1) cruise-control along line, (2) position-control along line (3) position-control along curve (4) planar (xy) Cartesian stabilization, (5) cruise-control along jagged line/curve, (6) vehicle-target spacing-control, (7) multi-robot spacing-control along line/curve, (8) tracking slowly-moving remote-controlled quadrotor, (9) avoiding obstacle while moving toward target, (10) RC F-150 followed by DDTT-vehicle. Hardware data/video is compared with, and corroborated by, model-based simulations. In short, many capabilities that are critical for reaching the longer-term FAME goal are demonstrated. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2015

Este projeto apresenta o desenvolvimento de um controle longitudinal e lateral para um veículo terrestre de categoria pesada, usando o conceito de geração de curvas de Clothoids. O controle é em malha fechada, com realimentação de velocidade e posição global (X,Y) do veículo no plano bi-dimensional. Dentro de uma arquitetura de controle autônomo para um veículo, o controle longitudinal ajusta a velocidade de cruzeiro em função da trajetória e o lateral é responsável por regular a direção do volante e a sua correspondência para com os pneus, que por sua vez direcionam o veículo dentro da trajetória dada. Para este controle, para o modelo do veículo foi apenas considerado a estrutura do cavalo mecânico (conjunto monolítico formado pela cabine, motor e rodas de tração do caminhão), desprezando qualquer carga traseira engatado nele. Primeiramente será apresentada uma breve introdução abordando a história e projetos atuas de veículos autônomos, em seguida é feito uma revisão dos conceitos básicos usados no projeto. No capitulo seguinte é abordado o modelo matemático do veículo (cinemática e dinâmica) e logo em seguida teremos a secção que aborda sobre a estrutura de controle proposta. A seguir será apresentado a seção de discussão sobre a implementação e resultados práticos. Finalmente é apresentado a conclusão e uma breve descrição sobre trabalhos futuros. / This project presents the development of a longitudinal and lateral control for a Heavy Category Ground Vehicles, using the concept of generation of curves Clothoids. This control is closed loop with feedback speed and position (X,Y) ofvehicle in two-dimensional plane. Within an autonomous control architecture for a vehicle, the longitudinal control adjusts cruising speed on the path and the lateral control is responsible for regulating direction of steering wheel and its correspondence to the tires, which in turn drive the vehicle within the given path. For this control, the vehicle model we are only considering the horse (monolithic assembly formed by the cab, engine and truck drive wheels), disregarding any rear cargo engaged in it. First a brief introduction will be presented addressing the history and projects of autonomous vehicles, then it is made a review of the basic concepts used in the project. The next chapter is discussed the mathematical model of the vehicle (kinematics and dynamics) and soon we will have a section dealing on the proposed control structure.The following will show the discussion section on the implementation and practical results, then the conclusion and a brief description of future work.

Research is limited on the role game-based training has on the engagement of learners. The following study was conducted to further advance research on engagement and game-based training in businesses by studying the engagement of travel agents in the game. Engagement is the manner in which a learner's cognitive and motor skills are motivated when participating in a game. Engaged learners will often push through challenging tasks and will concentrate on improving their skills due to their excitement about playing. The present study examined the engagement of travel agents as they played a serious game. The serious game, Adventures Game, was designed to provide a fun and memorable format for learning for travel agents who sell cruise tickets for a cruise line. The focus of this study was to examine the relationship between engagement (as measured by total number of minutes playing the game) and knowledge attainment (as measured by total number of fun points) of travel agents while playing a serious game. In addition, to understand the relationship between engagement and total cruise sales (as measured by total number of cabins sold). Thus, this nonexperimental study investigated the relationship between engagement and knowledge attainment. A combination of linear regression analyses and correlations were used to examine this relationship. The sample consisted of travel agents (N = 309) who played the serious game. The study focused on data which ranged from January 1, 2012 until December 31, 2014. The regression results supported both hypotheses proposed in this study. A strong, positive and statistically significant relationship between engagement and knowledge attainment was found. In addition, a modest, positive and statistically significant relationship between engagement and total cabin sales was found. Based on these results, further analysis was conducted, leading to finding a statistically significant relationship between knowledge attainment and total cabin sales as well. Future research should be designed to test whether the modest link between engagement and total cabin sales is mediated by knowledge attainment. The implications of the findings demonstrate theoretical, empirical and practical relevance, particularly as it is linked to adults learning optimally in computer-mediated, workplace settings.

This thesis deals with the research of consumer behavior and specifics of buyer decision-making process of Czechs during booking of their foreign holidays and methodology of market segmentation in tourism, or in the segment of cruises. Analysis of current trends and determinants on the supply and demand helps to build a competitive marketing strategy emerging of travel agency in the segment of cruises.

Cruise travel has become very popular worldwide. The North American cruise market is the world's biggest. Asian countries are among the fastest-growing outbound market for cruise travel. The Taiwanese cruise market has grown substantially. However, few research studies have examined Taiwanese travelers' motivation to experience a cruise vacation, and their satisfaction with the experience. Primary data was collected from a convenience sample of Taiwanese tourists who had been on North American cruise tours. Survey respondents were first time cruisers, over 40 years old, married, and had a Bachelor's degree, or higher. Push and pull motivational factors were identified. Respondents were influenced by recommendations from media and people. Respondents were satisfied with tangibles, cleanliness, food choices and selection, and responsiveness of staff. An overwhelming majority of cruisers would re-visit and recommend this trip. Implications for researchers and practitioners are suggested.

The purpose of this Bachelor thesis was to establish a method for determining the chemical oxygen demand (COD) fractionation in wastewater from cruise liners. COD fractions of interest were soluble biodegradable (SS), particulate biodegradable (XS), soluble unbiodegradable (SI) and particulate unbiodegradable (XI). Three types of wastewater (gray water, black water and permeate) were analysed and a method with a physiochemical approach was established. The method was originally elaborated by Jun Wu et al in the study “Wastewater COD biodegradability fractionated by simple physical–chemical analysis” (2014) Chemical Engineering Journal[ES1] [JB2]  258, p 450-459. The method was also used for comparison reasons of the COD fractionation in permeate before and after advanced treatment with nanofiltration and ozonation. Total COD in permeate was almost half of the initial value after nanofiltration and XI was eliminated. After ozonation no significant difference was observed neither in total COD concentration or fractionation pattern. The conclusion is that this method to determine the COD fractions has potential but it needs further optimization in form of adjusting the methods matrix specifically based on wastewater from cruise liners. / NAUTEK

The thesis deals with the design, realisation and functional verification of an electronic cruise control unit. Required inputs, outputs and controller of the control unit are identified first. The design and layout of the electronical components, including the processor, power supply and other necessary hardware is discussed. The algorithm for the control unit is developed in C/C++ and thoroughly analysed. The functionality of the cruise control unit equipped with the algorithm is verified through a case study performed on a combustion engine.