Autonomous vehicles are an important topic in modern day research, both for the private and public sector. One of the reasons why self-driving cars have not yet reached consumer market is because of levels of uncertainty. This is often tackled with multiple sensors of different kinds which helps gaining robust- ness in the vehicle’s system. Radars, lidars and cameras are often the sensors used and the expenses can rise up quickly, which is not always feasible for different markets. This could be addressed with using fewer, but more robust sensors for visualization. This thesis addresses the issue of one particular failure mode for camera sensors, which is reduced view range affected by rainy weather. Kalman filter and discrete wavelet transform with bilateral filtering are evaluated as rain removal algorithms and tested with the state-of-the-art object detection algorithm, You Only Look Once (YOLOv3). Filtered videos in daylight and evening light were tested with YOLOv3 and results show that the accuracy is not improved enough to be worth implementing in autonomous vehicles. With the graphics card available for this thesis YOLOv3 is not fast enough for a vehicle to stop in time when driving in 110km/h and an obstacle appears 80m ahead, however an Nvidia Titan X is assumed to be fast enough. There is potential within the research area and this thesis suggests that other object detection methods are evaluated as future work. / Autonoma fordon är för privat samt offentlig sektor ett viktigt område i modern forskning. Osäkerheten med autonoma fordon är en viktig anledning till varför de idag inte nått konsumentmarknaden. Systemen för autonoma fordon blir mer robusta med inkludering av flera sensorer av olika typer, vilka oftast är kameror, radar och lidars. Fordon med dessa sensorer kan snabbt öka i pris vilket gör dem mindre tillgängliga för olika marknader. Detta skulle kunna lösas med färre sensorer som däremot är mer robusta. Denna avhandling diskuterar problemet med en specific felmodell för kameror, vilket är minskat synfält som påverkas av regnigt väder. Kalman filter och diskret vågkomponent-transformation med bilateral filtrering utvärderades som regnborttagningsalgoritmer och testades med You Only Look Once (YOLOv3), en modern objektigenkänningsmetod. Filtrerade videofilmer i dagstid och kvällstid testades med YOLOv3 och resultaten visade att noggrannheten inte ökade tillräckligt mycket för att vara användbara för autonoma fordon. Med grafikkorten tillgängliga för denna avhandling är inte YOLOv3 snabb nog för ett fordon att hinna stanna i tid före kollision om bilen kör i 110km/h och ett föremål dyker upp 80m framför. Däremot antas det att fordon utrustade med Nvidias Titan X borde hinna stanna i tid före kollision. Avhandlingen ser däremot potential inom detta forskningsområde och föreslår att liknande test fast med andra objektigenkänningsmetoder bör utföras.

Today’s sustainability assessment frameworks are no longer applicable when evaluating the newautomotive vehicles. Therefore, the need for suitable automotive evaluation frameworks increasesas companies and scientists are trying to predict the important sustainability characteristics oftomorrows car and how it will affect our societies. The goal is to create a conceptual sustainabilityassessment framework to solve the very complex question of what the most important criteria areand how this new transportation type might affect our society. This is done using a systemapproach, a method that is suitable for studying interrelations between the influencing factors incomplex problems like the one between the sustainability dimensions. Scenario analysis has beenused in order to create the future environment and do a segmentation of the plausible concepts offuturistic transportation options. The evaluation criteria have been developed by gatheringinformation through a literature study and from primary sources via interviews.The resulting framework is composed of 19 evaluation criteria from the different dimensions ofsustainability. The framework allows the user to insert a futuristic concept and evaluate it tocompare a numeric score to other concepts to get indicators of how sustainable the concept is. Thesegmentation of futuristic vehicles shows that the most plausible types of automated vehicles areshared taxis, non-shared taxis and privately owned vehicles, all affecting society differently.The thematic analysis of the criteria has shown that there some relationships and types of criteriathat are more important than others. The most essential discovered correlations between criteriaare: Production and affordability and also maintenance & operation and affordability, affordabilitywith accessibility, affordability & accessibility and traffic volumes and further traffic Volumesand pollution. The developed framework is believed to have the desired function of creating a trustworthyassessment of autonomous vehicles based on the literature study and previous discoveries withinthe field. The evaluation of the different segments is left for future work. / Dagens ramverk för hållbarhetsbedömningar är inte längre användbara vid utvärdering av nyasjälvkörande fordon. Därför har behovet ökat av lämpliga ramverk som fokuserar påhållbarhetsutvärderingar när företag och forskare försöker förutse de viktigahållbarhetsegenskaperna av morgondagens fordon och hur de kommer att påverka vårt samhälleutifrån ett hållbarhetsperspektiv. Målet med studien är att skapa ett konceptuellt ramverk förhållbarhetsbedömning som kan hjälpa till att lösa den mycket komplexa frågan om vilka viktigakriterier bör inkluderas vid en evaluering av denna nya typ av transport. Studien har följt ettsystematiskt tillvägagångssätt kallat ”System approach”, en metod som är lämplig för studier därrelationer mellan olika påverkande faktorer är väldigt komplexa, som den mellanhållbarhetsdimensionerna. Scenarioanalys har används för att skapa en framtida miljö och ensegmentering av de mest trovärdiga koncepten av framtida transportalternativ. Utvärderingskriterierna har utvecklats genom att samla in information från en litteraturstudie ochfrån primära källor genom intervjuer. Det resulterande ramverket är sammansatt av 19 utvärderingskriterier inom de olikadimensionerna för hållbarhet. Med det resulterade ramverket kan användaren införa ett futuristisktfordonskoncept och bedöma detta för att få ett numeriskt resultat och jämföra dessa med andrautvärderingar för att få en indikation om hur hållbara koncepten är gentemot varandra. Segmenteringen av de futuristiska fordonstyperna visar att de mest trovärdiga typerna avautomatiserade färdmedel är delade taxitjänster, privata taxitjänster och privatägda fordon, allamed olika påverkan på samhället. Den tema-baserade analys av kriterierna har visat att det finns vissa relationer och typer av kriteriersom är viktigare än andra. De viktigaste upptäckta relationerna mellan kriterier är: Produktion ochekonomisk tillgänglighet, underhåll och ekonomisk tillgänglighet, ekonomisk tillgänglighet medtillgänglighet till transport, tillgänglighet till transport och trafikvolymer, ekonomisk tillgänglighetoch trafikvolymer och slutligen så påverkar trafikvolymerna utsläppet. Det utvecklade konceptuella ramverket antas ha den önskade funktionen att skapa en pålitligbedömning av autonoma fordon baserat på litteraturstudien och tidigare upptäckter inom fältet. Utvärderingen av de olika segmenten lämnas till framtida studier.

Dagens samhälle är starkt beroende av ett flertal kritiska infrastrukturer varav elproduktion, telekommunikationssystem och transportsystem är några. Dessa kritiska infrastrukturer är mycket hopflätade och internt beroende av varandra. De är alla mer eller mindre sårbara och riskerar att förlora delar eller hela deras funktionalitet. Samhället har som mål att skydda all sin kritiska infrastruktur på bästa sätt mot möjliga hot och försöker minimera risken för negativa händelser. Det som ständigt bör eftersträvas är bättre metoder för att kvantifiera och i förlängningen hantera dessa risker. I ett samhälle som är stark beroende av elektroniska system kan det finnas antagonister som har till avsikt att med hjälp av elektromagnetiska störning slå ut eller begränsa funktioner i infrastrukturen. Detta gör exempelvis autonoma fordon sårbara om inga säkerhetsåtgärder vidtas. Det innebär att risknivåer och acceptabla risker i samband med autonoma fordon behöver identifieras och fastställas. Syftet med detta examensarbete är att beskriva vad ett autonomt fordon är, identifiera vilka risker det finns samt hur stor påverkan dessa risker har på autonoma fordon vid en IEMI-attack. Examensarbetet omfattar en bakgrundsstudie som behandlar hur autonoma fordon fungerar, samt vilka tänkbara risker avsiktlig elektromagnetiska störningar kan visa för autonoma fordon. Resultatet från examensarbetet visar att de komponenter som misstänks vara utsatt för elektromagnetisk störning bör genomgå en riskanalys. Detta för att validera risken samt den elektromagnetiska störningens konsekvenser. / Today's society is heavily dependent on a number of critical infrastructures, of which electricity generation, telecommunications systems and transport systems are few. These critical infrastructures are highly interlinked and interdependent. They are all more or less vulnerable and risk losing parts or their entire functionality. The society's goal is to safeguard all critical infrastructure in the best possible way against possible threats and try to minimize the risk of fallout. What is constantly being sought is better methods of quantifying and managing these risks in the long run. The risks are linked to verified risk levels that deal with an acceptance limit. In a society that is highly dependent on electronic systems, there may also be antagonists who intend to disable or limit functions in the infrastructure by means of electromagnetic interference. This makes for example autonomous vehicles vulnerable if no safety measures are taken. This means that risk levels and acceptable risks associated with autonomous vehicles need to be identified and established. The purpose of this study is to describe what an autonomous vehicle is, identify what risks there are and how much impact these risks have on autonomous vehicles. The following thesis work includes a background study that deals with the functioning of autonomous vehicles, and what possible risks involve intentional electromagnetic interference for autonomous vehicles? The result of the study indicates that all components suspected of being exposed to electromagnetic interference should undergo a risk analysis. This to validate the risk and its consequence.

Automated vehicles are those which are capable of sensing their environments in order to perform at least some aspects of the safety-critical control (like steering, throttling, or braking) without direct human input. As a guide for planners and policymakers, the objective of this thesis is to develop a strong foundation for anticipating the potential impacts resulting from advancements in vehicle automation. To establish the foundation, this thesis uses a robust qualitative methodology, coupling a review of literature on the potential advantages and disadvantages of vehicle automation and lessons from past innovations in transportation, with recent trends of the Millennial Generation, carsharing services, and a series of interviews with thought-leaders in automation, planning, policymaking, transportation, and aviation. Five significant findings emerged from this thesis: (1) the impacts of vehicle automation differ depending on one’s visions of what automation means, how it is implemented, what the automation does, and where it operates; (2) current limitations of vehicle automation to perform all aspects of the dynamic driving task in all driving conditions make it difficult to move from level-4 to level-5 automation; (3) level-5 automation is required to have any effect on carsharing, mobility, and quality of life; (4) assuming effective planning and policymaking techniques, housing preferences, urban growth, and increases in total VMT will likely not be significantly impacted by vehicle automation; (5) human drivers may never be allowed to disengage their attention from a partially-automated vehicle, specifically in applications where drivers are expected to reengage their attention in safety-critical situations. From the perspective of understanding the bigger picture, this thesis developed a proposed future scenario of vehicle automation in the next five to ten years that is used to suggest guiding principles for policymakers, and key recommendations for planners, engineers, and researchers.

Self-driving cars rely on their sense of sight to function effectively in chaotic and uncontrolled environments. Thanks to recent developments in computer vision, specifically convolutional neural networks, autonomous vehicles have developed the ability to see at or above human-level capabilities, which in turn has allowed for rapid advances in self-driving cars. Unfortunately, much like humans being confused by simple optical illusions, convolutional neural networks are susceptible to simple adversarial inputs. As there is no overlap between the optical illusions that fool humans and the adversarial examples that threaten convolutional neural networks, little is understood as to why these adversarial examples dupe such advanced models and what effective mitigation techniques might exist to resolve these issues. This thesis focuses on these adversarial images. By extending existing work, this thesis is able to offer a unique perspective on adversarial examples. Furthermore, these extensions are used to develop a novel attack that can generate physically robust adversarial examples. These physically robust instances provide a unique challenge as they transcend both individual models and the digital domain, thereby posing a significant threat to the efficacy of convolutional neural networks and their dependent applications.

This dissertation presents the theory, design, implementation and successful deployment of a cognitive engine decision algorithm by which a cognitive radio-equipped mobile robot may adapt its motion and radio parameters through multi-objective optimization. This provides a proof-of-concept prototype cognitive system that is aware of its environment, its user's needs, and the rules governing its operation. It is to take intelligent action based on this awareness to optimize its performance across both the mobility and radio domains while learning from experience and responding intelligently to ongoing environmental mission changes. The prototype combines the key features of cognitive radios and autonomous vehicles into a single package whose behavior integrates the essential features of both. The use case for this research is a scenario where a small unmanned aerial vehicle (UAV) is traversing a nominally cyclic or repeating flight path (an â •orbitâ •) seeking to observe targets and where possible avoid hostile agents. As the UAV traverses the path, it experiences varying RF effects, including multipath propagation and terrain shadowing. The goal is to provide the capability for the UAV to learn the flight path with respect both to motion and RF characteristics and modify radio parameters and flight characteristics proactively to optimize performance. Using sensor fusion techniques to develop situational awareness, the UAV should be able to adapt its motion or communication based on knowledge of (but not limited to) physical location, radio performance, and channel conditions. Using sensor information from RF and mobility domains, the UAV uses the mission objectives and its knowledge of the world to decide on a course of action. The UAV develops and executes a multi-domain action; action that crosses domains, such as changing RF power and increasing its speed. This research is based on a simple observation, namely that cognitive radios and autonomous vehicles perform similar tasks, albeit in different domains. Both analyze their environment, make and execute a decision, evaluate the result (learn from experience), and repeat as required. This observation led directly to the creation of a single intelligent agent combining cognitive radio and autonomous vehicle intelligence with the ability to leverage flexibility in the radio frequency (RF) and motion domains. Using a single intelligent agent to optimize decision making across both mobility and radio domains is unified multi-domain decision making (UMDDM). / Ph. D.

Many major car manufacturers predict that autonomous vehicles controlled by AI (Artificial Intelligence) will be the future of the automotive industry. This means that AI makes the decisions even in emergency situations where people can be injured. Therefore, policies and guidelines are required for how autonomous vehicles should act in emergency situations (Faggella, 2020). This study will focus on how young adults view this dilemma.   The purpose of this study is to investigate how young adults believe that an AV (Autonomous Vehicle) should act in emergency situations, and understand what gives rise to their way of thinking.   To achieve the purpose of the survey and answer the research questions, a qualitative data collection through semi-structured interviews has been performed. The data collected was analyzed  with the help of a quantitative data analysis where the themes, patterns and connections that were identified are presented in the results and analyzed in the discussion (chapter 7).   The results generated by the empirical evidence show that young adults' view on how autonomous vehicles should act in emergency situations are largely in line with what previous studies have concluded. The result indicates that young adults find it most important to save as many lives as possible but also to follow the law. / Många stora biltillverkare förutspår att autonoma fordon som styrs med hjälp av AI (Artificial Intelligence) kommer att vara framtiden för bilindustrin. Detta medför att det är AI som fattar besluten även i nödsituationer där människor kan komma till skada. Därför krävs det policys och riktlinjer för hur autonoma fordon ska agera i nödsituationer (Faggella, 2020).  Denna undersökning fokuserar på hur unga vuxna ser på detta dilemma.    Syftet med detta examensarbete är att undersöka hur unga vuxna anser att en AV (Autonomous Vehicle) ska agera i nödsituationer, samt förstå vad som ger upphov till deras tankesätt.    För att uppnå undersökningens syfte och besvara två forskningsfrågor har kvalitativa data samlats in genom semistrukturerade intervjuer. Den data som samlades in analyserades med hjälp av en kvantitativ dataanalys där de teman, mönster och samband som hittades redovisas i resultatet och analyseras i diskussionen (kapitel 7).    De resultat som empirin genererade visar på att unga vuxnas synsätt på hur autonoma fordon skall agera i nödsituationer stämmer till stor del överens med vad tidigare undersökningar har kommit fram till. Resultatet pekar på att unga vuxna tycker är allra viktigast är att rädda så många liv som möjligt men även att följa lagen.

Shared autonomous vehicles present a significant opportunity to change the way that urban mobility is viewed by society. By providing a shared mobility platform at a cost lower than has previously been obtainable there are significant possibilites to enable a new era of mobility for consumers. This opportunity, however, comes with significant risks in the form of emissions and increased road usage. Understanding how the risks and benefits of shared autonomous vehicles can be balanced is crucial to be able to adequately prepare for their introduction. One of the primary ways to understand the interplay between the risks and benefits of autonomous vehicles is through the use of computer simulations. However, typically simulations must be defined for a specific area and provide results that are not applicable to a wide range of areas and situations. This work presents the development of a framework that can be used to simulate SAV behaviour at any given region of interest. This framework automates the process of generating a directed non-planar graph using data gathered from the OpenStreetMap project. It further provides tools to generate activity based trips that are statistically similar in time and density to provided data that reflects the trips in the simulation area. In the absence of this data, this work has identified the 2009 National Household Travel Survey as an acceptable surrogate for data specific to a region. The framework then provides methods by which the trip origins and destinations are mapped into the directed non-planar graph representation of the area of interest. This mapping is performed using real-world data including business locations and census data. Finally the framework is capable of simulating the activity of SAV in response to the defined trips given a variety of starting conditions and relocation strategies. In addition to the simulation framework this work presents a novel relocation strategy for unoccupied SAV based on the potential field methods that have been used in robotic navigation. This method provides a continously differentiable function that describes the unmet demand in the service area for a network of shared autonomous vehicles. The tunable parameters of the method are explored by using a design of experiments, and optimal values reflecting different scenarios are identified.The method is also evaluated in the context of both and over- and under-supply of vehicles for the given demand. As a result this method has been shown to provide substantial reductions in the wait time for a vehicle to service a trip with a minimal increase in the total distance that is traveled by all vehicles in the network.

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Autonomous vehicles (AVs) have become increasingly prevalent in modern society, with multiple companies pursuing avenues to advance technology. Despite the promises of safer driving, mitigating accidents and reducing stress, mixed opinions exist on the reliability and trustworthiness of the technology. While many factors form opinions regarding AVs, the component of personal values in AV discourse has not been well-documented. This research focuses on understanding which personal values are most prominent in AV discourse and how individuals prioritize these personal values. We studied two AV-focused data sources to gain perspective: 24 TED Talk transcripts and 20,000 Reddit user posts. Next, we scored the prevalence of personal values using the Personal Values Dictionary (PVD). Our results found that self-direction, achievement, power, stimulation, and conformity had an overall positive inclination in AV discourse. However, we also found value conflicts between both data sets, indicating a potential dissonance between professional opinions and those of typical consumers. Our findings provide insight into values literature and issues consumers bring up when discussing or adopting AVs. Our research on value conflicts can also link to consumers' potential adoption of AVs. Thus, we provide potentially useful perspectives for companies to address these concerns directly in their AV production, advertising, and design philosophies.