The goal of this master thesis is to show the benefit of using computer games of the type First Person Shooter, FPS in the field of military simulations. The main focus in this is around a couple of topics. Creating the AI that controls the behaviour of the computer-controlled characters, the bots. Create an environment where it is possible to supervise the bots and also design a framework that enables cooperation between a group of bots, a squad. The result is Total Unreal Studio, TUS, a program where it is possible to add bots to a squad, connect them to a game server and inspect what the bots are doing. Several maneuvers that could be applied to a squad has been implemented such as room clearing where the squad clear a building from eventual enemies, room by room and other different attacking strategies. Also it is very easy to create new maneuvres for a squad as effect of the design. As the name of the program indicates, the well-known game Unreal Tournament is used as platform for the simulation. But because we use a interface between the game server and TUS, it is possible to switch to any other game and the interface is the only thing that has to be modified. To get good situation awareness a lot of node analysis is required, for instance calculating good sniping positions, pinch points and advantageous locations from where to perform an ambush. / Målet med detta examensarbete är att påvisa fördelen med att använda datorspel av typen FörstaPersonsSpel, FPS, inom militära simuleringar. Huvudinriktningen hos arbetet har rört ett flertal ämnen: att skapa det AI som kontrollerar beteendet hos datorkontrollerade karaktärer, så kallade botar, skapa en miljö där det är möjligt att övervaka botarna och även designa ett ramverk som möjliggör samarbete mellan botar i en grupp. Resultatet av examensarbetet är Total Unreal Studio, TUS, en applikation där det är möjligt att lägga till botar i en grupp, ansluta dem till en spelserver och övervaka deras agerande. Flera manövrar för en grupp av botar finns redan implementerade. Ett par av dessa är rumsrensning där stridsgruppens uppgift är att rensa en byggnad från eventuella fiender rum för rum samt andra attackmanövrar. Designens utseende gör även att det är mycket enkelt att lägga till ytterligare manövrar om så önskas. Som namnet på programmet indikerar används det välkända spelet Unreal Tournament som plattform för simuleringarna. Mellan spelet och TUS används gränssnittet Gamebots vilket gör det möjligt att byta till vilket spel som helst och det enda som behöver modifieras är gränssnittet. För att botarna ska kunna ta riktiga beslut behövs ett sätt att få uppfattning om omvärlden. Detta fås genom att analysera de navigeringsnoder som är utplacerade. Denna analys kan gå ut på att hitta bra krypskyttenoder eller fördelaktiga platser att anlägga bakhåll.

This master thesis presents the design of an implementation of a working prototype for an augmented motion capture acting environment. Motion capture (MoCap), the recording of movements to be applied to characters or objects in computer graphics simulations, is widely used in video games, advertisement, and cinema. MoCap is realized through different techniques, where one common problem is the efficiency to capture actor’s motion performances. To capture motions without obstacles for the motion detectors, actors act blindly, without graphic references while acting. Mistakes or a poor correlation between the actors performances and the computer graphics simulation requires the scene either to be taken many times or to be corrected afterwards in time-consuming post-production. These issues slow down the production process or lead to a low quality product.We suggest that one way to limit the problem of efficiency in motion capture is to let actors perform in a virtual environment. To this end, this master thesis presents a simple prototypeenvironment with the goal to support actors’ performances to improve motion capture efficiency. The idea is to surround an actor with four screens which display the virtual environment. A Microsoft Kinect camera is utilized for motion capture. Gestures are usedto trigger interactions between the actor and the virtual environment. Furthermore, the thesis explores the applicability of open source libraries, game engines, and inexpensivegeneral purpose technology. We suggest, as indicated by demonstrated validity, that virtual environments and augmented motion capture improve the conditions for actors, thus providing more efficient motion capture shots. However, further research and quantitative measurements are needed to understand and fully evaluate the effect of the presented prototype tool.

In this research, a horror game level was created using ”Unreal Engine 4” (Epic games, 2017) where white noise and processed noises was used as ambiences in order to see how it affects the perceived emotions amongst the participants. A pre-study was conducted in order to choose the stimuli for the main experiment and to test attributes. A pilot test was conducted to test the game level to find out any flaws. In the main experiment twenty participants took part in playing the finalized game level and answering a questionnaire. The results showed a change in the emotional quality depending on the noise being present, but it’s unclear if this is caused by the filtering of the noises alone or the filtering of the noises combined with other factors. A post hoc test was also conducted where a valence and arousal chart was created by letting the participants pin point the emotional attributes used in the experiments.

Videoconferencing is one of the most common telepresence methods today and educational videos is rising in popularity among distance learners. Traditional videoconferencing is unable to convey gestures and mutual eye contact between participants. This study aim to propose a Virtual Reality telepresence solution using game engines. A literature study confirmed the effectiveness achieved in VR is comparable to the effectiveness in face-to-face meetings. The suggested solution implements whiteboard functionality from a real-life perspective, confirming it is possible to include new functionality and directly transfer old functionality to the VR system from the communication systems today. The system was evaluated based on the response time, packet loss, bandwidth, frame rate and through user tests. The evaluation shows it is possible to design a telepresence system with VR capable of passing the Turing Test for Telepresence. The participants of the user tests did not experience discomfort and they were positively inclined to the telepresence system. Though, discomfort may emerge if the VR character is used with a common office workstation. Future studies in this topic would involve modifications of the third person camera, making the head's rotation follow the direction of the camera view and implementing movable eye pupils on the VR character using the upcoming eye-tracking accessory.

abstract: Autonomous Vehicles (AVs), or self-driving cars, are poised to have an enormous impact on the automotive industry and road transportation. While advances have been made towards the development of safe, competent autonomous vehicles, there has been inadequate attention to the control of autonomous vehicles in unanticipated situations, such as imminent crashes. Even if autonomous vehicles follow all safety measures, accidents are inevitable, and humans must trust autonomous vehicles to respond appropriately in such scenarios. It is not plausible to program autonomous vehicles with a set of rules to tackle every possible crash scenario. Instead, a possible approach is to align their decision-making capabilities with the moral priorities, values, and social motivations of trustworthy human drivers.Toward this end, this thesis contributes a simulation framework for collecting, analyzing, and replicating human driving behaviors in a variety of scenarios, including imminent crashes. Four driving scenarios in an urban traffic environment were designed in the CARLA driving simulator platform, in which simulated cars can either drive autonomously or be driven by a user via a steering wheel and pedals. These included three unavoidable crash scenarios, representing classic trolley-problem ethical dilemmas, and a scenario in which a car must be driven through a school zone, in order to examine driver prioritization of reaching a destination versus ensuring safety. Sample human driving data in CARLA was logged from the simulated car’s sensors, including the LiDAR, IMU and camera. In order to reproduce human driving behaviors in a simulated vehicle, it is necessary for the AV to be able to identify objects in the environment and evaluate the volume of their bounding boxes for prediction and planning. An object detection method was used that processes LiDAR point cloud data using the PointNet neural network architecture, analyzes RGB images via transfer learning using the Xception convolutional neural network architecture, and fuses the outputs of these two networks. This method was trained and tested on both the KITTI Vision Benchmark Suite dataset and a virtual dataset exclusively generated from CARLA. When applied to the KITTI dataset, the object detection method achieved an average classification accuracy of 96.72% and an average Intersection over Union (IoU) of 0.72, where the IoU metric compares predicted bounding boxes to those used for training. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

Training simulators are valuable tools in education of forest machine operators. One important part of the education is to learn about damages occurring due to the forest machines and how they can be avoided. Two types of damages are especially severe, soil compaction and formation of wheel ruts. Compaction reduces the amount of water and nutrients in the soil, and impedes root growth. Furthermore, water is gathered in wheel ruts, leading to transport of organic materia and heavy metals into water courses. These damages can be avoided through planning of the harvesting activities with respect to season, weather, and the conditions on the site. The main focus point is to avoid driving on wet soil, since wetness makes it more susceptible to damage.  The aim of this thesis is to investigate how this should be incorporated in a simulator. Implementations are made in Unreal Engine with AGX Dynamics for Unreal, which already has a deformable terrain called AGX Terrain. This terrain was investigated by creating two terrain materials, representing dry and wet Swedish forest soil, and driving a forwarder on them.  AGX Terrain was found to be simple to use and gave fair results, the rut depths were comparable in size with empirical results. However, it was limited in the sense that shearing was not taken into account and there was no possibility of having different material properties across the terrain. A potential solution to these problems is suggested, in which a more extensive way of computing stress propagation and the resulting damages is used. Further investigations has to be made in order to find out if this approach is of good use.

This work deals with driving skills training problematics using a driving school 3D simulator, which monitors the observance of road traffic rules. Existing simulators are categorized by characteristics and described. The text contains a list of implemented rules and a summary of suitable tools. The resultant application is based on the Unreal engine and the text describes the various stages of development.

Background. In order to increase the visual fidelity of characters in video games, strand-based hair rendering within Unreal Engine 4 is explored in this thesis. Because of the complex nature of hair, explicit hair models can be very costly to render and simulate. It is theorized that utilizing customized hair and simulation settings, tailored to specific types of hairstyles could alleviate this issue while preserving visual fidelity. Objectives. The aim of this thesis is to provide an insight into what can be done to increase visual appeal and computer performance of physical simulation for different types of hairstyles and determine if customized settings may cause a significant impact on the perceived level of realism. The objectives of this thesis are to acquire a set of different strand-based hairstyles, determine a set of customized hair and simulation settings which can be applied to them, create a test scene inside of Unreal Engine 4 and render out a set of images and videos to be used in a user experiment, measure the performance of each customized setting and finally synthesize the acquired data. Methods. In order to achieve the aims and objectives of this thesis, a user experiment that utilizes the 2AFC method to let participants compare image- and video-pairs is performed as well as a performance experiment using the built-in profiling tools in Unreal Engine 4. In addition, a pilot experiment was performed in order to ascertain that the experiments would be feasible on the available hardware. Results. The results show that there was a significant difference in the perceived level of realism when different simulation settings was applied to the hairstyles, with customized settings being preferred to the default setting. The voting results on the image-pairs showed a preference for fine hair strands while the strand count did not have as much of an impact. It was shown that participants could easier distinguish between the different simulation- and hair-settings in long hair compared to short hair. The performance experiment showed that the amount of hair strands had the biggest impact on computer performance. Conclusions. Customizing hair and simulation settings to different types of hairstyles could provide a heightened perceived level of realism and a limited performance boost, from what could be derived from these experiments. Lowering the hair strand count was determined to be the most effective method of increasing performance. The performance of strand-based hair is currently not quite reaching a consistent 60 frames per second on the tested hardware, but with further optimizations it is believed that this could be acquired, especially on more powerful graphics cards. Future work should keep focus on increasing the stability of real-time strand-based hair simulation.

Recent advancements in audio technology for computer games has made possible for implementations with binaural audio. Compared to regular stereo sound, binaural audio offers possibilities for a player to experience spatial sound, including sounds along the vertical plane, using their own headphones. A computer game prototype called “Crystal Gatherer” was created for this study to explore the possibilities of binaural audio imple- mentation regarding localization and perception of objects that make sound in a 3D game. The game featured two similar game levels, with the difference that one used binaural sound, and the other stereo sound. The levels consisted of a dark space that the player could navigate freely with the objective to find objects that make sound, called “crystals”, as fast as they could. An experiment was conducted with 14 test sub- jects that played the game, qualitative and quantitative data was collected, including the time the players took to complete the game levels, respectively, and answers about how they experienced the levels. A majority of test subjects reported that they per- ceived a difference between the levels. No significant difference was found between the levels in terms of efficacy of finding the objects that made sound. Some test subjects stated that they found localization was better in the binaural level of the game, others found the stereo level to be better in this respect. The study shows that there can exist possibilities for binaural audio to change the perception of audio in computer games.

Drönare är ett växande fenomen i dagens samhälle och deras användningsområdenhar snabbt ökat de senaste åren. För att underlätta utvecklingen av drönarteknologi kansimuleringar tillämpas då de möjliggör testning i en kontrollerad och riskfri miljö. I dettaprojekt visualiseras simuleringar av drönare i ett försök att skapa värde för denna utveckling. Visualiseringen skedde med hjälp av Unreal Engine 5. Under projektets gång studerades arbetsmetoderna som nyttjades och hur en systemanatomi kan bidra till utvecklingen iett småskaligt mjukvaruprojekt. Största värdet som producerades för kunden var kommunikationsmodulen. Kommunikationen uppnåddes med hjälp av två JSON-filer som visualiseringen respektive simuleringen skrev till för att kommunicera med varandra. Värdeti denna modul ligger i att kunden sökte en modulär lösning för att kommunicera mellanen 3D-visualisering och en simulering. En erfarenhet som uppmärksammades angåendearbetsmetoderna är vikten av en fungerande gruppdynamik. Bidragande faktorer till detvar agila arbetsmetoder, goda kommunikationsvägar och en väl planerad användning avGit. Systemanatomier upplevdes ge begränsat värde till projektet.