This thesis is focused on the monitoring system in the fleet management. Frauds are increasingly caused due to company cars. The emphasis is put especially on costs saving resulting from the introduction of the monitoring and a more effective control. The work defines modern elements of control, their functions and impact on costs. It outlines pros and cons connected with the journey log. Practical examples are given as an illustration, including an alternative solution with a savings calculation.

Résumé indisponible. / The VIPAFLEET project aims at developing a framework to manage a fleet of IndividualPublic Autonomous Vehicles (VIPA). We consider a fleet of cars distributed at specifiedstations in an industrial area to supply internal transportation, where the cars can beused in different modes of circulation (tram mode, elevator mode, taxi mode). The goalis to develop and implement suitable algorithms for each mode in order to satisfy all therequests either under an economic point aspect or under a quality of service aspect, thisby varying the studied objective functions.We model the underlying online transportation system as a discrete event basedsystem and propose a corresponding fleet management framework, to handle modes,demands and commands. We consider three modes of circulation, tram, elevator andtaxi mode. We propose for each mode appropriate online algorithms and evaluate theirperformance, both in terms of competitive analysis and practical behavior by computationalresults. We treat in this work, the pickup and delivery problem related to theTram mode and the Elevator mode the pickup and delivery problem with time windowsrelated to the taxi mode by means of flows in time-expanded networks.

In recent years, advances in information technology have led to an increasing number of devices (or things) being connected to the internet; the resulting data can be used by applications to acquire new knowledge. The Internet of Things (IoT) (a network of computing devices that have the ability to interact with their environment without requiring user interaction) and big data (a field that deals with the exponentially increasing rate of data creation, which is a challenge for the cloud in its current state and for standard data analysis technologies) have become hot topics. With all this data being produced, new applications such as predictive maintenance are possible. One such application is monitoring a fleet of vehicles in real-time to predict their remaining useful life, which could help companies lower their fleet management costs by reducing their fleet's average vehicle downtime. Consensus self-organized models (COSMO) approach is an example of a predictive maintenance system for a fleet of public transport buses, which attempts to diagnose faulty buses that deviate from the rest of the bus fleet. The present work proposes a novel IoT-based architecture for predictive maintenance that consists of three primary nodes: namely, the vehicle node (VN), the server leader node (SLN), and the root node (RN). The VN represents the vehicle and performs lightweight data acquisition, data analytics, and data storage. The VN is connected to the fleet via its wireless internet connection. The SLN is responsible for managing a region of vehicles, and it performs more heavy-duty data storage, fleet-wide analytics, and networking. The RN is the central point of administration for the entire system. It controls the entire fleet and provides the application interface to the fleet system. A minimally viable prototype (MVP) of the proposed architecture was implemented and deployed to a garage of the Soci\'et\'e de Transport de l'Outaouais (STO), Gatineau, Canada. The VN in the MVP was implemented using a Raspberry Pi, which acquired sensor data from a STO hybrid bus by reading from a J1939 network, the SLN was implemented using a laptop, and the RN was deployed using meshcentral.com. The goal of the MVP was to perform predictive maintenance for the STO to help reduce their fleet management costs. The present work also proposes a fleet-wide unsupervised dynamic sensor selection algorithm, which attempts to improve the sensor selection performed by the COSMO approach. I named this algorithm the improved consensus self-organized models (ICOSMO) approach. To analyze the performance of ICOSMO, a fleet simulation was implemented. The J1939 data gathered from a STO hybrid bus, which was acquired using the MVP, was used to generate synthetic data to simulate vehicles, faults, and repairs. The deviation detection of the COSMO and ICOSMO approach was applied to the synthetic sensor data. The simulation results were used to compare the performance of the COSMO and ICOSMO approach. Results revealed that in general ICOSMO improved the accuracy of COSMO when COSMO was not performing optimally; that is, in the following situations: a) when the histogram distance chosen by COSMO was a poor choice, b) in an environment with relatively high sensor white noise, and c) when COSMO selected poor sensors. On average ICOSMO only rarely reduced the accuracy of COSMO, which is promising since it suggests deploying ICOSMO as a predictive maintenance system should perform just as well or better than COSMO . More experiments are required to better understand the performance of ICOSMO. The goal is to eventually deploy ICOSMO to the MVP.

On May 31st 1916, during the First World War, one of the greatest naval battles took place in the North Sea outside of the Danish west coast between the naval forces of Great Britain and Germany. This paper aims to examine the outcome of the Battle of Jutland through three different perspectives on victory and defeat. The battle is well-debated as it has been considered a draw, as both actors saw themselves as victorious states after the battle. This study therefore contributes to the debate by systematically investigate how three different perspectives on victory and defeat can explain the outcome. Through the perspectives end-state understandings, cost-benefit calculus and match-fixing, events during the battle and which contributed to the subsequent discussions about the outcome, will be analyzed. The study results in the finding that one of the three perspectives, match-fixing, can explain victory and defeat in the battle. The result therefore shows that an systematic analyze of the perspectives can explain the outcome of the battle. This is an important contribution to the further research and demonstrates that there are ways to systematically measure an outcome with an explanatory ambition.

“GreenPeace” es una tendencia que hoy en día las personas siguen, la cual tiene como objetivo poner fin a los abusos en contra del medio ambiente y disfrutar de un futuro “verde”. Es así que varios países se están inclinando en poner reglas estrictas respecto al cuidado del ecosistema, una de estas son eliminar o reducir la emisión de gases contaminantes por parte de los autos a motor. En varios países como Brasil, Suiza, Holanda entre otros; ya se pusieron limitaciones al funcionamiento de los autos a motor. Es así que las empresas empezaron a ofrecer autos eléctricos e híbridos. En el Perú está sucediendo algo parecido, ya que el estado ha empezado a brindar incentivos como la eliminación del ISC; asimismo, tienen planeado ofrecer bonos y otro tipo de ayuda con el fin de incentivar el ingreso de los autos eléctricos e híbridos. Por tal motivo a futuro, las empresas automotoras que no se unan a este cambio, no serán sostenibles y estarán destinadas a quebrar. El presente trabajo de investigación profesional ha sido realizado con la finalidad de evaluar el impacto financiero que tendrán las empresas importadoras del sector automotriz a razón de la renovación del parque automotor en Lima con autos híbridos. Por lo tanto, ha sido desarrollado en relación a los conceptos financieros, principalmente, los costos, ya que, es la variable más influyente del tema investigado. Este trabajo de investigación se centra en el estudio de las empresas importadoras del sector automotriz en Lima. Es importante que las empresas en general del sector y sus principales gerencias, comprendan el impacto financiero que tendrán en el futuro próximo a razón de importar autos híbridos y la verdadera importancia de hacerlo, ya que, la escasez del combustible va en ascenso con el transcurso de los años y del consumo. En consecuencia, se espera que el presente trabajo de investigación sirva como base para lograr el entendimiento del sector y como se verá impactado financieramente a razón de la importación de estos vehículos. Para validar las hipótesis planteadas, se emplearon instrumentos de investigación cualitativos y cuantitativos. El instrumento cualitativo utilizado fue entrevista a profundidad a expertos del sector y los instrumentos cuantitativos fueron las encuestas realizadas. Todo el trabajo de investigación realizado tuvo como finalidad recabar información cualitativa y cuantitativa para corroborar las hipótesis planteadas. Finalmente, se desarrollará un caso práctico en el que se plantearán tres escenarios que comparan información financiera respecto a los vehículos de combustible convencionales que se encuentran en el mercado y a los vehículos híbridos. / "GreenPeace" is a trend that people nowadays follow, which aims to end abuses against the environment and enjoy a "green" future. Thus, several countries are inclined to set strict rules regarding the care of the ecosystem, one of these is to eliminate or reduce the emission of polluting gases by motor cars. In several countries like Brazil, Switzerland, Holland among others; limitations were already placed on the operation of motor cars. Thus, companies began offering electric and hybrid cars. Something similar is happening in Peru, since the state has begun to provide incentives such as the elimination of the ISC; They also plan to offer bonuses and other assistance in order to encourage the entry of electric and hybrid cars. For this reason in the future, automotive companies that do not join this change will not be sustainable and will be destined to fail. This professional research work has been carried out with the purpose of evaluating the financial impact that the importing companies of the automotive sector will have due to the renewal of the automotive fleet in Lima with hybrid cars. Therefore, it has been developed in relation to financial concepts, mainly costs, since it is the most influential variable of the subject under investigation. This research work focuses on the study of import companies in the automotive sector in Lima. It is important that companies in general in the sector and their main management understand the financial impact they will have in the near future due to the import of hybrid cars and the true importance of doing so, since fuel shortages are on the rise with the course of the years and consumption. Consequently, this research work is expected to serve as a basis for understanding the sector and how it will be financially impacted due to the importation of these vehicles. To validate the hypotheses raised, qualitative and quantitative research instruments were used. The qualitative instrument used was an in-depth interview with experts from the sector and the quantitative instruments were the surveys carried out. All the research work carried out was aimed at gathering qualitative and quantitative information to corroborate the hypotheses. Finally, a case study will be developed in which two scenarios that compare financial information regarding conventional fuel vehicles on the market and hybrid vehicles will be considered. / Tesis

In recent years, the paradigm of personal urban mobility has radically evolved as an increasing number of Mobility-on-Demand (MoD) systems continue to revolutionize urban transportation. Hailed as the future of sustainable transportation, with significant implications on urban planning, these systems typically utilize a fleet of shared vehicles such as bikes, electric scooters, cars, etc., and provide a centralized matching platform to deliver point-to-point mobility to passengers. In this dissertation, we study MoD systems along three operational directions – (1) modeling: developing analytical models that capture the rich stochasticity of passenger demand and its impact on the fleet distribution, (2) economics: devising strategies to maximize revenue, and (3) control: developing coordination mechanisms aimed at optimizing platform throughput. First, we focus on the metropolitan bike-sharing systems where platforms typically do not have access to real-time location data to ascertain the exact spatial distribution of their fleet. We formulate the problem of accurately predicting the fleet distribution as a Markov Chain monitoring problem on a graph representation of a city. Specifically, each monitor provides information on the exact number of bikes transitioning to a specific node or traversing a specific edge at a particular time. Under budget constraints on the number of such monitors, we design efficient algorithms to determine appropriate monitoring operations and demonstrate their efficacy over synthetic and real datasets. Second, we focus on the revenue maximization strategies for individual strategic driving partners on ride-hailing platforms. Under the key assumption that large-scale platform dynamics are agnostic to the actions of an individual strategic driver, we propose a series of dynamic programming-based algorithms to devise contingency plans that maximize the expected earnings of a driver. Using robust optimization techniques, we rigorously reason about and analyze the sensitivity of such strategies to perturbations in passenger demand distributions. Finally, we address the problem of large-scale fleet management. Recent approaches for the fleet management problem have leveraged model-free deep reinforcement learning (RL) based algorithms to tackle complex decision-making problems. However, such methods suffer from a lack of explainability and often fail to generalize well. We consider an explicit need-based coordination mechanism to propose a non-deep RL-based algorithm that augments tabular Q-learning with a combinatorial optimization problem. Empirically, a case study on the New York City taxi demand enables a rigorous assessment of the value, robustness, and generalizability of the proposed approaches.

<p>  </p> <p>Recently, aircraft using liquid hydrogen gas-turbine engines (also referred to as liquid hydrogen aircraft) have drawn more attention from the aviation industry as an option to decarbonize commercial aviation. Liquid hydrogen aircraft can have a lower environmental impact than kerosene aircraft and can be a vital part of the net-zero carbon emission plan. However, uncertainties and challenges still exist, including the design of liquid hydrogen aircraft, how their operation might differ from kerosene aircraft, and most importantly, the feasibility of achieving aviation decarbonization goals when these aircraft operate in fleets alongside existing fleets of aircraft. This paper focuses on the modeling and the design of liquid hydrogen aircraft and describes operational studies to evaluate the environmental impact of introducing liquid hydrogen aircraft into a fleet operating on a worldwide network. The studies use the Fleet-Level Environmental Evaluation Tool (FLEET) to simulate different scenarios and account for the estimated hydrogen cost and equivalent carbon emissions. Results show that the “most likely" scenario where a 175-seat class single-aisle liquid hydrogen aircraft enter service in 2035, could result in a total fleet-level carbon emission reduction of 7.11% compared to a baseline scenario with no liquid hydrogen aircraft in the airline fleet. The simulation considers different liquid hydrogen pricing scenarios and equivalent carbon emissions assumptions. A fleet with multiple seat classes of liquid hydrogen aircraft may result in smaller carbon emission reduction than might initially be expected due to the delayed replacements of Jet-A aircraft in the fleet caused by the high costs of liquid hydrogen aircraft. The FLEET simulations show a maximum possible reduction of 45.72% of the total fleet-level carbon emission in 2050 comparing to the baseline scenario with no-liquid hydrogen aircraft, obtained by introducing multiple models of liquid hydrogen aircraft using green hydrogen to replace the existing fleet instead of future kerosene aircraft. The introduction of liquid hydrogen aircraft also significantly impact the profitability of the total fleet, which has an unexpected impact on the fleet allocation and composition. Further studies on the liquid hydrogen fleet pricing and implementation, as well as refinements on the FLEET tool, are recommended in order to gain a more realistic understanding of how the liquid hydrogen fleet might impact the global aviation.</p>

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:Bauliche und territoriale Entwicklung Beziehungen und Konflikte

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