<p dir="ltr">Most road fatalities are caused by human error. To help mitigate this issue and enhance overall transportation safety, companies are turning to advanced driver assistance systems and autonomous vehicle development. Perception, a key module of these systems, mostly uses light detection and ranging (LiDAR) sensors and enables efficient obstacle detection and environment mapping. Extensive research on the use of LiDAR for autonomous driving has been documented in the literature. Yet still, several researchers and practitioners have advocated continued investigation of LiDAR placement alternatives. To address this research need, this thesis research begins with a comprehensive review of different sensor technologies – camera, radio detection and ranging, global positioning system, and inertial measurement units – and exploring their inherent strengths and limitations. Next, the thesis research developed a methodological multiple criteria framework and implemented it in the context of LiDAR placement optimization. Given the numerous criteria and placement alternatives associated with LiDAR placement, multi-criteria decision analysis (MCDA) was identified as an effective tool for LiDAR placement optimization. MCDA has been applied to some extent in decision-making regarding autonomous vehicle development. However, its application in LiDAR placement optimization remains unexplored. In evaluating the LiDAR placement alternatives, the research first established the placement alternatives and then developed a comprehensive yet diverse set of criteria – point density, blind spot regions, sensor cost, power consumption, sensor redundancy, ease of installation, and aesthetics. The data collection methods included the CARLA simulator, sensor datasheets, and questionnaire surveys. The relative importance among the evaluation criteria was established using weighting techniques such as respondent-assigned weighting, equal weighting, and randomly generated weighting. Then, to standardize the different measurement units, scaling was carried out using value functions developed for each criterion using data from the respondents. Finally, the weighted and scaled criteria measures were amalgamated to obtain the overall evaluation score for each alternative LiDAR placement design. This enabled the ranking of the placement designs and the identification of the best-performing and worst-performing designs. Hence, the optimization method used is the enumeration technique. The findings of this study serve as a reference for future similar efforts that seek to optimize LiDAR placements based on select criteria. Further, it is expected that the thesis’s framework will contribute to an enhanced understanding of the overall impact of LiDAR placement on autonomous vehicles, thus enabling the cost-effective design of their placement and, ultimately, improving AV operational outcomes, including traffic safety.</p>

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Over the last few decades, freshwater turtles have become more common in the global illegal wildlife trade because of the growing demand in the pet trade. Illegally traded turtles may be intercepted and deposited by a number of agencies. However, when turtles are confiscated, many uncertainties and risks make releasing them back to the wild difficult. Therefore, we used tools from decision analysis to achieve the following three objectives: (1) to identify points of intervention in illegal turtle trade using conceptual models, (2) to outline the linked decisions for turtle confiscation and repatriation using decision trees, and (3) to evaluate the decision trees for two example scenarios, one with complete information and one with uncertainty. We used the wood turtle (Glyptemys insculpta) as a case study, which is a species of conservation concern, in part due to illegal wildlife trafficking. We conducted informational interviews of biologists, law enforcement, land managers, and zoo staff, which we refer to as a decision makers. Interviews revealed that decisions regarding the disposition of confiscated turtles are complicated by uncertainty in disease status and potential differences in origin and confiscation locations. Decision makers that handle confiscated turtles also recognize that their decisions are linked, where linkages rely on personal contacts. In evaluating our decision trees, we found that despite different amounts and kinds of uncertainties, release of the confiscated wood turtles to the wild provided the highest conservation value. Collectively, our research shows how the use of decision trees can help improve decision making in the face of uncertainty.

Transport infrastructure investment decision making is typically based on a range of inputs such as social, environmental and economic factors. The benefit cost ratio (BCR), a measure of economic efficiency (“value for money”) determined through cost benefit analysis (CBA), is dependent on accurate estimates of the various option costs and net social benefits such as reductions in travel time, accidents, and vehicle operating costs. However, most evaluations are deterministic procedures using point estimates for the inputs and producing point estimates for the outputs. Transport planners have primarily focused on the cost risks and treat risk through sensitivity testing. Probabilistic risk analysis techniques are available which could provide more information about the statistical confidence of the economic evaluation outputs. This research project report investigated how risk and uncertainty are dealt with in the literature and guidelines. The treatment of uncertainty in the Nelson Arterial Traffic Study (ATS) was reviewed and an opportunity to apply risk analysis to develop probabilities of sea level rise impacting on the coastal road options was identified. A simplified transport model and economic evaluation case study based on the ATS was developed in Excel to enable the application of @RISK Monte Carlo simulation software. The simplifications mean that the results are not comparable with the ATS. Seven input variables and their likely distributions were defined for simulation based on the literature review. The simulation of seven variables, five worksheets, and 10,000 iterations takes about 30 seconds of computation time. The input variables in rank order of influence on the BCR were capital cost, car mode share, unit vehicle operating cost, basic employment forecast growth rate, and unit value of time cost. The deterministically derived BCR of 0.75 is associated with a 50% chance that the BCR will be less than 0.6, although this probability is partly based on some statistical parameters without an empirical basis. In practice, probability distribution fitting to appropriate datasets should be undertaken to better support probabilistic risk analysis conclusions. Probabilities for different confidence levels can be reported to suit the risk tolerance of the decision makers. It was determined that the risk analysis approach is feasible and can produce useful outputs, given a clear understanding of the data inputs and their associated distributions.

Predictive decision theory explains how humans should make decisions in practice given that they are not always perfect rational decision makers. Based on the prescriptive decision theory, this study addresses criticism of universal decision making models for supplier selections which have the notion of being used uniquely in all types of supplier choice situations. Issues raised are whether this performance is correct and how a dynamic decision-making model could create a more customized decision-making model which does not add much responsibility to the decision maker's judgment. A case study at Logosol, a small industrial company identifies by process mapping a complex supplier selection process consisting of three steps; prototype creation, null-series and production, based on test manufacturing. The supplier selection process is used as the basis for the creation of a dynamic decision making model. Dynamic decision-making models have the basic principle of learning from a decision and using that information in the next decision, which is considered useful in the business case as they not only use test manufacturing for product testing but also for collecting information about the supplier. Finally, the created dynamic decision model shows that universal decision-making models cannot be used in many complex supplier selection processes involving a plurality of steps. The model must be adapted to the company's individual process, however the identification method or some parts of the model used in this study may be used to create a dynamic decision model for other companies or organizations. / Preskriptiv beslutsteori säger hur människan borde fatta beslut i praktiken givet att de inte alltid är perfekt rationella beslutsfattare. Utifrån den preskriptiva beslutsteorin riktas i denna studie kritik mot universella beslutsmodeller för leverantörsval vilka har föreställningen om sig att användas kunna användas universellt i alla olika typer av leverantörsvalssituationer. Frågeställningar som väckts är om denna föreställning stämmer, samt hur en dynamisk beslutsmodell skulle kunna skapa en mer anpassad beslutsmodell vilken inte lägger lite mycket ansvar på beslutsfattarens omdöme. Genom en fallstudie hos Logosol ett litet industriföretag identifieras med hjälp av processkartläggning en komplex leverantörsvalsprocess innefattande tre steg; prototypskapande, nollserieskapande samt produktion utifrån testtillverkning. Fallföretagets leverantörsvalsprocess används som grund för skapande av en dynamisk beslutsmodell. Dynamiska beslutsmodeller har den grundläggande principen att medta lärdom från ett beslut in i nästa, vilket anses användbart för fallföretagets leverantörsvalsprocess då dom inte bara använder testtillverkning för test av produkt utan även för insamling av information om leverantören. Studien visar att föreställningen stämmer, den skapade dynamiska beslutsmodellen visar att universella beslutsmodeller inte är särskilt användbara i många komplexa leverantörsvalsprocesser innefattande ett flertal steg. Modellen måste anpassas för företagets individuella process, dock kan identifieringsmetoden eller vissa delar av modellen som använts i denna studie möjligtvis användas för att skapa en dynamisk beslutsmodell för andra företag eller organisationer.

<p>U radu su istražene mogućnosti za razvoj modela za izbor<br />lokacije proizvodnih sistema. Razvijen je model za izbor<br />lokacije proizvodnih sistema i verifikovan u studiji<br />slučaja na teritoriji AP Vojvodine i opštine Inđija.<br />Posebno značajan rezultat je fazi ekspertni sistem za<br />analizu kriterijuma odlučivanja, geografski informacioni<br />sistem za skrining i prostorni sistem za podršku u izboru<br />lokacije proizvodnih sistema.</p> / <p>This paper examines the possibilities of model development for<br />production systems site selection. Developed model for production<br />systems site selection is presented and tested in case study of AP<br />Vojvodina and Indjija municipality. A particularly important result is<br />developed fuzzy expert system for factor analysis, geographic<br />information system for screening and spatial decision support system.</p>

There is broad consensus that a transition to renewable energy and a low-carbon economy is crucial for future development and prosperity, yet there are differing perspectives on how such a transition should be achieved. The overarching goal of this dissertation, which is comprised of three interrelated studies, is to analyze and compare energy futures scenarios to achieve a renewable energy transition and low-carbon economy in the State of Vermont. In the first study, an analysis is presented of the role of energy pricing regimes and economic policy in the context of pursuing a renewable energy transition in the State of Vermont. Through the development and application of a system dynamics model, results address the limits to technological substitution due to path dependence on nonrenewable energy. The role of complementary economic policy is also highlighted to shift from a goal of quantitative growth to qualitative development in order to decouple economic welfare from energy consumption. In the second study, an analysis is presented of the impact of modeled energy transition scenarios to address energy development and land use trade-offs. Simulations with a spatio-temporal land cover change model find that Vermont could achieve a complete transition to renewable electricity using in-state resources through developing between 11,000 and 100,000 hectares of land for solar and wind, or up to four percent of state land area, including some environmentally sensitive land. This approach highlights the need for integration of energy policy and land use planning in order to mitigate potential energy-land use conflict. In the final study, trade-offs between energy, economic, environmental, and social dimensions of Vermont's renewable energy transition are explored through the use of a multi-criteria decision analysis. Energy transition alternatives were designed to reveal trade-offs at the intersection of economic growth and carbon price policy. While there were no optimal pathways to achieving Vermont's energy transition, some energy transition alternatives achieve a more socially desirable balance of benefits and consequences. Navigating the trade-offs inherent in the ongoing energy transition will require an adaptive approach to policymaking that incorporates iterative planning, experimentation, and learning.

A well-functioning infrastructure is the foundation of a stable society, where payment systems are an important part. Grocery stores provide the general public with groceries and rely on customer consumption. Disruptions in the card payment system leads to consequences because 97% of all customers have access to card payment and is the payment method they prefer to use.  The aim of the survey is to find out about food stores' experience of disruptions in the payment system and how they wish a good management for this to look like. Next, a general crisis management model is developed to mitigate the consequences of a disruption in the payment system. A qualitative method is used to sample a result from each individual stores’ experiences and wishes.  Earlier research where decision analysis is used to handle disruptions in the payment system within the food industry has not been found. Through interviews and theories can a crisis management model for payment disruptions be developed, and examine the business continuity of food stores. The results of the survey shows that food stores today do not have any risk management to handle a break in the payment system or how a desirable management of it would look like. They have previously handled this by letting the customer pay with cash. A smaller store let a customer pay at another time. The general crisis management model has three phases: preliminary studies, management and evaluation. The preliminary studies involve that the store evaluates which payment methods they are capable of implementing. The management of a crisis takes place in three iterative steps; offer alternative payment methods, see how the crisis develops and finally remedy it. The evaluation step in the model is important because a positive outcome can not be guaranteed and therefore continued research is encouraged. / En välfungerande infrastruktur är grunden för ett stabilt samhälle där betalningssystem är en viktig del. Livsmedelsbutiker förser befolkningen med dagligvaror och är beroende av kundernas konsumtion. Störningar i kortbetalningssystemet medför konsekvenser eftersom 97 % av alla kunder har tillgång till kortbetalning och är den betalningsmetod de föredrar att använda.  Målet med undersökningen är att ta reda på livsmedelsbutikers erfarenheter av betalningsstopp och hur de önskar att en bra hantering för detta ser ut. Därefter tas en generell krishanteringsmodell fram som mildrar konsekvenserna av ett betalningsstopp. För att undersöka detta intervjuas butiker angående deras affekter av alternativa betalningsmetoder. En kvalitativ metod används för att få ett resultat utifrån butikernas erfarenheter och önskemål.  Tidigare forskning där metoden beslutsanalys tillämpas för att hantera betalningsstopp inom livsmedelsindustrin hittas inte. Genom intervjuer och teorier tas en krishanteringsmodell för betalningsstopp fram. Resultatet av undersökningen är att livsmedelsbutiker idag inte har någon riskhantering av betalningsstopp eller uppfattning av hur en önskvärd hantering ser ut. De har tidigare hanterat detta genom att låta kunden betala med kontanter. En mindre butik har låtit kunden betala vid ett senare tillfälle. Den generella krishanteringsmodellen sker i tre steg: förstudier, hantering och utvärdering. I förstudierna ser butiken över vilka betalningsmetoder de är kapabla till att implementera. I hanteringsfasen itereras tre steg; erbjuda alternativa betalningsmetoder, se hur krisen utvecklas och slutligen åtgärda det. Utvärderingssteget i modellen är viktig eftersom ett positivt utfall inte kan garanteras och därför uppmuntras fortsatt forskning av denna.

[pt] O setor elétrico brasileiro vem sofrendo fortes mudanças estruturais, cujo principal objetivo é criar um caráter competitivo para permitir ao setor crescer não mais por investimentos estatais, mas sim pela atuação do capital privado. Assim sendo, a Agência Nacional de Energia Elétrica (ANEEL) passa a oferecer uma multiplicidade de oportunidades de investimentos, geradas principalmente pela recente implantação dos leilões de unidades geradoras de energia (em sua maioria hidrelétricas) e de linhas transmissoras. Em vista disso, essa dissertação propõe um modelo de avaliação de projetos de geração hidrelétrica sob condições de incerteza utilizando-se a metodologia de opções reais. Este trabalho busca incorporar a flexibilidade gerencial à avaliação de projetos através do uso de Árvores Binomiais de Decisão, com probabilidades neutras ao risco, para a avaliação por Opções Reais em Tempo Discreto. O método é computacionalmente intenso, mas de modelagem mais simples e intuitiva que os métodos tradicionais de Opções Reais, permitindo assim uma maior flexibilidade na elaboração do modelo. A aplicação prática foi realizada através da avaliação da opção de venda de energia de uma Pequena Central Hidrelétrica (PCH). / [en] The Brazilian electric sector comes suffering strong structural changes, whose main objective is to create a competitive to allow the sector to grow not more for state investments, but for the private capital. The Agência Nacional de Energia Elétrica (ANEEL) starts to offer a multiplicity of chances of investments, generated mainly for the recent implantation of the auctions of generating units of energy (in its hydroeletrics majority) and of transmission lines. In sight of this, this work propose a model to hydroelectric generation asset valuation under uncertainty conditions using real options methodology. This work aims to incorporate managerial flexibility to the projects valuation using Decision Trees, with neutral probabilities to the risk, for the Real Options Valuation in Discrete Time. The method is computational intense, but simpler and more intuitive than the traditional methods of Real Options, thus allowing a bigger flexibility in the modeling of the problem.The practical application is applied to the problem of option of energy sale valuation of Small Hydroeletric Generation Asset.

Com o aumento do número de desastres e consequente incremento no número de pessoas vitimadas, a preparação para esses eventos é uma necessidade das sociedades modernas. Neste sentido, o planejamento das operações logísticas para atendimento as situações de emergências é uma atividade recente e pouco explorada na produção acadêmica. O objetivo deste trabalho é estabelecer uma metodologia para definir locais para o pré-posicionamento de materiais utilizados no socorro a populações afetadas por desastres através de um modelo de otimização estocástica de dois estágios e análise de decisão multicritério e que considerem parâmetros quantitativos e qualitativos. Com base nos custos de transporte e do não atendimento a demanda, e utilizando informações como mapeamentos de riscos; custos de transporte; histórico de ocorrências de desastres; cobertura geográfica; compras de materiais; capacidades de depósitos e de transporte, um modelo estocástico de programação linear minimiza os custos operacionais para abastecimento às vítimas. Uma análise detalhada sobre como atribuir penalidades para demanda não atendida também é apresentada. Devido à incerteza quanto a severidade de um desastre e a influência da mídia nas fases pós-desastres estes parâmetros são representados na forma de cenários. O resultado do modelo estocástico mostra a quantidade de locais e quais localidades minimizam o custo operacional. Após a obtenção desse resultado, uma nova etapa é utilizada para decisão de escolha do local, com a aplicação de modelo de decisão multicritério que considere, além dos valores obtidos pela modelagem, critérios subjetivos característicos a operações humanitárias. Os resultados finais mostram que modelos estocásticos promovem resultados mais confiáveis que os determinísticos, especialmente, em situações nas quais materiais disponíveis não podem atender toda a demanda e que a consideração de critérios qualitativos e quantitativos proporciona uma decisão mais robusta em operações humanitárias. / The increase in disasters and the consequent increase in the number of victims make it highly necessary to prepare for these events in modern societies. Logistics operations planning to meet emergencies is a recent activity and little explored in academic production. Our aim is to establish a method to locate pre-positioned materials used in disaster relief through a two-stage stochastic optimization model and a multi-criteria decision analysis that consider quantitative and qualitative parameters. Based on transportation and unattended demand costs, and using information such as risk mapping, transportation costs, historical occurrences of disasters, coverage, materials purchase, warehouses and transport capacities, a stochastic linear programming model minimizes the operating costs to supply the victims. A detailed analysis on how to assign penalties for unmet demand is also presented. Due to the uncertainty of the disasters severity and the influence of the media in phases after disasters, these parameters are represented as scenarios. The result of the stochastic model shows the quantity and the locations that minimize the operational cost. After this result, a new phase is applied for site selection, with the application of multi-criteria decision analysis that consider the values provided by the model and subjective criteria characteristic of humanitarian operations. The final results show that stochastic models promote more reliable results than deterministic ones, especially in situations in which the materials available cannot meet all the demand and that the consideration of qualitative and quantitative criteria provides better decisions in humanitarian operations.