Tidigare forskning har visat att bilförare tenderade att underskatta hastigheten de färdas i med ca 20%. Forskning har även visat att hastighetsupplevelse hos bilförare kan påverkas av ett utökat Field of View (FoV) vilket resulterar i lägre hastighetsval (Pretto et al., 2009; Schütz et al., 2015; Lidestam, Eriksson & Eriksson, 2019). Utöver FoV har även virtuella vägmarkeringar (VRM), visats ha potentialen att påverka hastighetsval genom att bistå bilförare med ytterliggare visuell information kring dennes omgivning (Lidestam, Eriksson & Eriksson, 2019). Attityder gentemot system som syftar till att påverka bilförares hastighetsval har studerats (Wall et al., 2013), med det finns luckor i forskning gällande hur dessa upplevs av bilförare med ADHD. Vidare har även upprepning av körningar med samma konstellationer av visuella stimuli har visats påverka hastighetsval vilket skulle tyda på perceptuell inlärning sker under bilkörning (Lindestam, Eriksson & Eriksson, 2019). Syftet med den aktuella studien var att undersöka huruvida VRM påverkade hastighetsval samt hur de upplevs av bilförare med respektive utan ADHD. Studien ämnade att göra detta genom att besvara följande frågeställningar 1. a. Hur upplevdes VRM? b. Finns det en skillnad i upplevelsen av VRMs mellan bilförare med ADHD och utan ADHD? 2. Vilken effekt har ADHD, FoV, VRM och replikat på självvald hastighet? Resultaten visade att upplevelsen av VRM inte skiljde sig signifikant mellan de två guppen, trots detta skattades samtliga frågor kring upplevelsen av VRM högre av bilförare med ADHD än bilförare utan ADHD. Körningarna rapporterades som signifikant mer koncentrationskrävande av bilförare utan ADHD. Replikat och FoV uppvisade en signifikant interaktionseffekt på hastighetsval. Framtida forskning kan med fördel studera hur VRM kan utformas för att upplevas som mer hjälpsamma samt hur de bör implementeras för att bilförare ska vilja använda dem vid körningar. Det är viktigt att framtida forskning i området även inkluderar bilförare med ADHD för att säkerställa att system som utformas även är gynnsamma för dessa bilförare.

The present work deals with the development of a computational geometric framework for vision modeling for performing visibility and legibility analyses in Digital Human Modeling (DHM) using the field-of-view (FoV), estimated geometrically from 3D tessellated head scans. DHM is an inter-disciplinary area of research with the prime objective of evaluating a product, job or environment for intended users through computer-based simulations. Vision modeling in the existing DHM’s has been primarily addressed through FoV modeling using right circular cones (RCC). Perimetry literature establishes that the human FoV is asymmetric due to unrestricted zygomatic vision and restrictions on the nasal side of the face. This observation is neither captured by the simplistic RCC models in DHM, nor rigorously studied in vision literature. Thus, the RCC models for FoV are inadequate for rigorous simulations and the accurate modeling of FoV is required in DHM. The computational framework developed in this work considers three broad components namely, the geometric estimation and representation of FoV, visibility and statistical visibility, and legibility of objects in a given environment. A computational geometric method for estimating FoV from 3D laser-scanned models of the human head is presented in this work. The strong one-to-one similarity between computed and clinically perimetry maps establishes that the FoV can be geometrically computed using tessellated head models, without necessarily going through the conventional interaction based clinical procedures. The algorithm for FoV computation is extended to model the effect of gaze-direction on the FoV resulting in binocular FoV. A novel unit-cube scheme is presented for robust, efficient and accurate modeling of FoV. This scheme is subsequently used to determine the visibility of 3D tessellated objects for a given FoV. In order to carry out population based visibility studies, the statistical modeling FoV and generation of percentile-based FoV curves are introduced for a given population of FoV curves. The percentile data thus generated was not available in the current ergonomics or perimetry literature. Advanced vision analysis involving character-legibility is demonstrated using the unit-cube with an improved measure to incorporate the effect of character-thickness on its legibility.

<p>When users begin to experience virtual reality (VR) for the first time, they can be met with some degree of motion sickness and nausea, especially if continuous joystick locomotion is used. The symptoms that are induced during these VR experiences fall under the umbrella term cybersickness, and due to these uncomfortable experiences, these users can get a bad first impression and abandon the innovative technology, not able to fully appreciate the convenience and fascinating adventures VR has to offer. As such, this project compares the effects of two cybersickness mitigation methods (Dynamic Field of View (FOV) and Virtual Reference Frame), both against each other and combined, on user-reported cybersickness symptoms to determine the best combination to implement in commercial applications to help create more user-friendly VR experiences. The hypothesis is that combining the FOV reduction and the resting frame methods can mitigate VR cybersickness more effectively without hindering the user’s experience and the virtual nose method is more potent at mitigating cybersickness compared to dynamic FOV. To test these hypotheses, an experimental game was developed for the Meta Quest 2 with five levels: a tutorial level and four maze levels (one for each scenario). The participants were asked to complete the tutorial level until they got used to the virtual reality controls, and then they were instructed to complete the maze level twice with one of the following conditions for each run: no method, dynamic field of view only, virtual nose only, and dynamic field of view and virtual nose combined. After completing each maze trial, the participants were asked to complete a simulator sickness questionnaire to get their thoughts on how much sickness they felt during the test. Upon concluding the testing phase with 36 participants and compiling the data, the results showed that while the subjects preferred the dynamic FOV method even though they were able to complete the trials significantly faster with the virtual nose method, it is inconclusive regarding which method is truly more effective. Furthermore, the results showed that it is also inconclusive if the scenario with both methods enabled is significantly better or worse than either method used separately.</p>