The objective of this research is to inform the design of dynamic interfaces to optimize unmanned aerial vehicle (UAV) operator reliance on automation. A broad goal of the U.S. military is to improve the ratio of UAV operators to UAVs controlled. Accomplishing this goal requires the use of automation; however, the benefits of automation are jeopardized without appropriate operator reliance. To improve reliance on automation, this effort sought to accomplish several objectives organized into phases. The first phase aimed to validate metrics that could be used to gauge operator fatigue online, to understand how the reliability of automated systems influences subjective and objective responses, and to understand how the impact of automation reliability changes with different levels of fatigue. To that end, this study employed a multiple UAV simulation containing several tasks. Findings for a challenging Image Analysis task indicated a decrease in accuracy and reliance with time. Both accuracy and reliance were lower with an unreliable automated decision making aid (60% reliability) than with a reliable automated decision making aid (86.7% reliability). Further, a significant interaction indicated that reliance diminished more quickly when the automated aid was less reliable. Concerning the identification of possible eye tracking measures for fatigue, metrics for percentage of eye closure (PERCLOS), blinks, fixations, and dwell time registered changes with time on task. Fixation metrics registered reliability differences. The second phase sought to use outcomes from the first phase to build two algorithms, based on eye tracking, to drive continuous diagnostic monitoring, one simple and another complex. These algorithms were intended to diagnose the passive fatigue state of UAV operators and used subjective task engagement as the dependent variable. The simple algorithm used PERCLOS and total dwell time within the automated tasking area. The complex algorithm added percent of cognitive fixations and frequency of express fixations. The complex algorithm successfully predicted task engagement, primarily on the strength of percentage of cognitive fixations and express fixation frequency metrics.

Integrated Vehicle Health Management (IVHM) systems use models and algorithmic techniques to process Condition-based Data (CBD) to offer prognostic information and actionable imperatives in support of Condition-based Maintenance (CBM) for the system. IVHM technology was first introduced by NASA to gather data, diagnose, detect, and predict faults, and support operational and post-maintenance activities in space vehicles. Eventually, it expanded to other vehicle types such as aircraft, ships, and land vehicles [1]. In recent years, the United States Army has been implementing a policy of CBM to transition from preventive to predictive maintenance [2]. One of the many challenges faced by the Army is the lack of accurate methods to assess ground vehicle reliability using modeling and/or simulation. This study aims at developing a Markov Chain-based algorithm that can detect anomalies and that is capable of accurately predicting the operational states of military ground vehicles. Several different Markov Chain Models (MCMs) have been developed and tested in their ability to predict the next state of a vehicle, given its current state (diagnostics and prognostics), and to examine how well a given model can detect unknown measurements (anomaly detection). A target of 90% Correct Classification (PCC) was established for all the vehicle performance data. The results suggest that it is possible to predict at a high level of accuracy the likely operational states of the military vehicles using MCMs. The anomaly detection test results revealed that MCMs can clearly distinguish a change in the performance data, that does not match the expected performance.

Unmanned ground vehicles (UGV) are being explored for use in military domains. Military UGVs operate in complex off-road environments. Vehicle mobility forecasting plays an important role in understanding how and where a vehicle can operate. Traditional mobility forecasting has been done using an analytical model known as the NATO Reference Mobility Model (NRMM). There has been a push to extend the forecasting capabilities of NRMM by integrating more simulation methods. Simulation enables the repeated testing of UGVs in scenarios that would be difficult or dangerous to study in real world testing. To accurately capture UGV performance in simulation, the operating environment must be accurately modeled. Current widely used methods for generating forested virtual environments rely on random methods. These methods result in forests that can appear to be realistic when visually inspected but lack the appropriate distribution of different sizes of vegetation. The size and distribution of vegetation plays a major role in the ability of a vehicle to operate in a forested environment. Therefore, there is a need for alternative forest generation algorithms that generate more realistic virtual forests. To address this, a novel environment generation model based on forest ecology was implemented. This model accurately captures vegetation growth, disbursement, and competition. Simulated UGV self-driving performance for scenes generated using the ecological model was compared to performance for scenes generated using a widely adopted random model. Resulting speeds across each scene were averaged to predict a speed made good (SMG). Vehicle SMG predictions were made in NRMM using scene descriptions matching each of the random and ecological scenes. Using a continuous vegetation override function in simulation, SMG predictions for both methods were similar to the results of NRMM. However, the predicted speeds for scenes generated with the ecological model were different from the predicted speeds for scenes generated with the random model. When examining the distribution and frequency of different sizes of trees, ecological scenes more closely match the distribution and frequency of trees that are expected for real forested environments suggesting that predictions for speed in ecological scenes better represent potential speeds for real environments.

No description available.

American Association of State Highway and Transportation Officials (ASHTO) specifications have prescribed lateral load distribution factors to calculate the bending moments and shear forces for the design of highway bridges for civilian highway traffic. The maximum bending moments and shear forces caused by a wheel line load (or the entire vehicle) placed on the girders are multiplied by the distribution factors to calculate the design forces to include the effect of the load distribution laterally to the girders by the bridge deck. However, the use of these AASHTO distribution factors may not provide accurate estimate of the maximum forces for military vehicles, which usually have significantly different loading pattern than those of the civilian vehicles. Therefore, this study was conducted to develop new formulas for the lateral load distribution factors for military vehicles. The study considered six different types of military vehicles, three wheeled vehicles and the other three tracked vehicles. The bridge database used for developing AASHTO distribution factors formulas was also used in this study. The focus of this study was to develop the distribution factors formulas for three different types of bridges: steel girder bridges, pre-stressed concrete bridges, and concrete T-beam bridges. The bridges in each category were analyzed for the six types of military vehicles by the harmonic decomposition approach to calculate the distribution factor. This thesis provides a total of 52 new formulas for different types of vehicles, different types of bridges, bending moment and shear force values, interior and exterior girders, and for single and multiple lane loading cases. The distribution factors calculated with the formulas were compared with those calculated by direct analyses of the bridges to evaluate the accuracy of the proposed formulas. Comparisons were also made between the values calculated by the new formulas, post-LRFD formulas prescribed in 1996 AASHTO Standard Specification, and simple pre-LRFD formulas that were prescribed by AASHTO before 1994. / Master of Science

[pt] O estudo da dinâmica lateral é de grande importância para análise do comportamento de um veículo durante manobras e fundamental para a implementação de sistemas de controle de estabilidade e de trajetória em veículos autônomos. Nesse contexto, baseado em medições experimentais de um veículo militar de três eixos durante manobras de mudança dupla de faixa a diferentes velocidades, o presente trabalho apresenta métodos de identificação de sistemas para obtenção de modelos lineares por meio da ferramenta CONTSID (CONTinuous-Time System IDentification), disponível no MATLAB; de modelos não lineares baseados em Redes Neurais; e, por fim, a proposta de emprego de modelos híbridos com o intuito de minimizar o erro associado à primeira abordagem, somando-se ao modelo linear, o valor estimado do resíduo com a aplicação de redes neurais. Por se tratarem de modelos obtidos a partir de dados observados, como parâmetros de entrada e de saída do sistema, foram selecionados o ângulo do volante e a taxa de guinada do veículo, respectivamente. Com a utilização do dados observados, foi realizada a identificação das funções de transferência para cada velocidade, o que possibilitou a análise da influência dessa variável no comportamento dinâmico do sistema. Em seguida, empregou-se uma abordagem via redes neurais ao mesmo conjunto de dados, com a construção de arquiteturas distintas por meio da modificação do número de neurônios, número de camadas e função de ativação. Por fim, um modelo híbrido foi combinado utilizando-se a modelagem linear e não linear para obtenção de melhorias na resposta do modelo final estimado. De acordo com os resultados, as técnicas empregadas apresentaram viabilidade de aplicação e resultados satisfatórios, destacando-se o aprimoramento do modelo linear por meio de sua substituição pelo modelo híbrido baseado em redes neurais. Do exposto, objetiva-se destacar o potencial dos métodos apresentados de forma que, posteriormente, esses estudos possam ser aprofundados para implementação de malhas de controle veicular, com o intuito de contribuir com o aumento da segurança, melhoria do conforto e no desenvolvimento de veículos autônomos. / [en] The study of lateral dynamics is of great importance for the vehicle behavior analysis during turning maneuvers, and it is fundamental to stability or path control systems used in autonomous vehicles. In this context, based on experimental measurements of a three-axle military wheeled vehicle during double lane changes maneuvers at different speed, this work presents methods for the identification of linear models using the CONTSID (CONTinuous-Time System IDentification) toolbox, available in MATLAB; nonlinear models based on artificial neural networks; and, the application of hybrid models to reduce the error associated with the first approach, combining the linear model to the estimated error using neural networks. Since those are data-driven methods, as input and output parameters of the system, the wheel steering angle and the yaw rate of the vehicle were respectively selected. Using the CONTSID toolbox, the identification of the transfer functions for each speed was performed, making it possible to evaluate the influence of this variable in the system s dynamics behavior. Thereafter, a neural network approach was applied to the same data set, changing architecture s parameters, such as number of neurons, layers and the activation function. At last, a hybrid model approach was presented through the combination of previous linear and nonlinear approaches to improve the estimated model response. The proposed methods showed satisfatory results, highlighting the improvement in the linear model through its replacement by the hybrid model based on neural networks. Therefore, this work aims to show the potential of the methods presented, and posteriorly contribute to studies on the implementation of vehicle control systems to increase safety, improve comfort and in the development of autonomous vehicles.

No description available.

<p>The Swedish Military Defence is about to make a large reorganization. Surplus, everything from tanks to personal underwear, enough to equip 800,000 soldiers will be destroyed or sold to the highest bidder. This thesis is a discourse analysis about the argumentation in media between the Military and the enthusiast, who are interested in military vehicles and military surplus.</p> / <p>Uppsatsen är en kartläggning och diskursanalys av den argumentation som förekommit i den mediala debatten rörande den svenska Försvarsmaktens avveckling av överskott. Morgondagens försvar ska vara baserat på kvalité istället för kvantitet. Från att ha haft ett försvar som omfattat omkring 800 000 personer under vapen i händelse av ofred ska det nya försvaret skäras ned till att omfatta omkring 200 000 personer. En mängd materiel, allt från stridsvagnar och underkläder, blir således överflödig. Försvarsmakten skall fram till utgången av 2004 ha genomfört omorganisationen. Tillvägagångssättet att avveckla överskottet varierar, destruktion, försäljning och som bistånd är exempel på avvecklingsalternativ. De olika tillvägagångssätten har fått kritik från olika aktörer som deltagit i debatten. Det opinionen reagerat på är att, i många fall, helt fungerande och ny materiel destruerats eller så har kritik riktats mot de olika försäljningsförfarandena som Försvarsmakten tillämpat. Uppsatsen undersöker aktörernas argumentering i debatten och försöker att analysera varför argumenteringen ser ut som den gör. </p>

The Swedish Military Defence is about to make a large reorganization. Surplus, everything from tanks to personal underwear, enough to equip 800,000 soldiers will be destroyed or sold to the highest bidder. This thesis is a discourse analysis about the argumentation in media between the Military and the enthusiast, who are interested in military vehicles and military surplus. / Uppsatsen är en kartläggning och diskursanalys av den argumentation som förekommit i den mediala debatten rörande den svenska Försvarsmaktens avveckling av överskott. Morgondagens försvar ska vara baserat på kvalité istället för kvantitet. Från att ha haft ett försvar som omfattat omkring 800 000 personer under vapen i händelse av ofred ska det nya försvaret skäras ned till att omfatta omkring 200 000 personer. En mängd materiel, allt från stridsvagnar och underkläder, blir således överflödig. Försvarsmakten skall fram till utgången av 2004 ha genomfört omorganisationen. Tillvägagångssättet att avveckla överskottet varierar, destruktion, försäljning och som bistånd är exempel på avvecklingsalternativ. De olika tillvägagångssätten har fått kritik från olika aktörer som deltagit i debatten. Det opinionen reagerat på är att, i många fall, helt fungerande och ny materiel destruerats eller så har kritik riktats mot de olika försäljningsförfarandena som Försvarsmakten tillämpat. Uppsatsen undersöker aktörernas argumentering i debatten och försöker att analysera varför argumenteringen ser ut som den gör.