Green buildings are increasingly in demand yet current green building practices often do not consider hazard mitigation. High-performance buildings that can withstand hazards, protect residents, and do not need to be rebuilt following a disaster are truly sustainable buildings. This report focuses on current hazard mitigation and disaster resilience standards for wildfires and earthquakes through an in-depth analysis of case studies and best practices for these hazards. The U.S. Green Building Council’s Leadership in Energy and Environmental Design (LEED) framework is the ideal vehicle to incorporate hazard mitigation methods into official green building certification. Language for a new LEED Hazard Mitigation and Resilience credit area is established using guidelines for hazard mitigation for wildfires and earthquakes. / text

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.

<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>