In Turkey, big investments are made to improve the existing train lines for use of new high speed trains. Most of the bridges on the existing train lines are typical and in this thesis one of the standard types, the classic steel truss bridge is investigated. This thesis presents the dynamic investigation of standard type existing truss bridge for passenger comfort criteria under the high speed train loadings. Two different computational analysis models have been developed to idealize the vehicle-bridge modeling to evaluate the passenger comfort that were influenced by dynamic vibrations on bridges induced by trains. Field tests of this bridge have been conducted by two separate institutes, Middle East Technical University and Turkish State Railways, to determine the state of the bridge under existing low-speed train loadings. Eigenvalue and Time history analysis of the LARSA 4D structural analysis program has been used to investigate the vehicle bridge interactions. The solutions obtained from the analysis have been evaluated with the experimental results. Different rehabilitation options are analytically studied to improve the serviceability of standard steel truss bridges per Eurocode 1990:2002, Eurocode 1991-2:2003, UIC 774-3 and UIC 776-1. The focus of this research is to define a relationship between span weight per meter and passenger comfort as well as the stiffness of this type of bridge.

The purpose of this project has been to further develop the ergonomic comfort andextended use of a concept sleigh early in development by Bombardier Recreational Productsin Finland. Their concept already featured a modern looking exterior design with a largewindow, innovative doors that gives of vibes of a modern sports car. The original conceptalso has multifunctional benches that allows storage and a prone position. The goal has beento deliver my final concept in the shape of a 3D-model with the new features. Side goals wasgiven besides the ergonomic improvements, these were to make the sleigh fit on a 3.5-meter trailer along with a snowmobile and see if components from other products producedby BRP Finland, Rovaniemi, would be ergonomically beneficial to the sleigh while notaffecting the dimensions in an undesirable way. The process of this project has been basedon three main phases namely Inspiration, Ideation, and Creation. The first phase focused onexploring the market and the users of similar products with the help of a competitor analysiswith sleighs suggested by the company. During the Inspiration phase an academic study wasmade where relevant knowledge was collected. That was for example to support thisdevelopment with information about how the users and stakeholders should be involvedduring an Industrial design process. Very useful information about ergonomics andanthropology aspects was discovered and applied. A form was sent out to users where it wasshown that the passenger comfort was the most important aspect of a sleigh. The secondphase was focused on development of new ideas that were spawned during two workshopsand sketching methods. The third phase, Creation, finalised the concepts and throughmatrices the best concept was selected based on criteria taken from the user’s interest andother aspects of the sleigh like the side goals of the project. The result of this project wasconcept Virgo, which is a concept based in BRPs original design with features spawned andevaluated during this project. Much research and reiterations has gone into thisdevelopment to arrive at minor improvements to bring great customer value to the sleigh ifimplemented when it becomes available on the market

Highly automated driving is approaching reality at a high speed. BMW is planningto put its first autonomous driving vehicle on the road already by 2021. The path torealising this new technology is however, full of challenges. Not only the transverseand longitudinal dynamic vehicle motion play an important role in experiencedcomfort but also the requirements and expectations of the occupants regarding thevertical dynamic vibration behaviour. Especially during long trips on the motorwaywhere the so far active driver becomes the chauffeured passenger, who reads, worksor sleeps in his newly gained time. These new use-cases create new requirements forthe future design of driving comfort which are yet to be fully discovered.This work was carried out at the BMW headquarters and had the aim to usedifferent machine learning models to investigate and identify patterns between thesubjective comfort values reported by participants in a study, on a comfort scale of 1-7 and the mechanical vibrations that they experienced, measured inm/s2. The datawas collected in a previous independent study and statistical methods were used toinsure the quality of the data. A comparison of the ISO 2631-1 comfort ratings andthe study’s findings is done to understand the need for a more sophisticated model to predict comfort in autonomous driving. The work continued by investigating different dimensionality reduction methods and their influence on the performance of the models. The process used to build, optimise and validate neural networks and other models is included in the method chapter and the results are presented. The work ends with a discussion of both the prediction results and the modelsre-usability. The machine learning models investigated in this thesis have shown great po-tential for detecting complex pattern that link feelings and thoughts to mechanical variables. The models were able to predict the correct level of comfort with up to50% precision when trying to predict 6 or 7 levels of comfort. When divided into high versus low discomfort, i.e. predicting one of two comfort levels, the models were able to achieve a precision of up to 75.4%.Excluded from this thesis is the study of differences in attentive vs inattentive state when being driven in an autonomous driving vehicle. It became clear shortly before the start of this work, that the experiment that yielded the data used for it failed to find a statistically significant difference between the two states. / Självkörande bilar är snart inte längre en dröm utan en mycket sann verklighet. År 2021 planerar BMW att släppa ut sin första autonoma bil på vägarna. Dock är vägen till att förverkliga denna nya teknik full av utmaningar. Utöver den tvärgående och längsgående dynamiska styrningen av fordonet, så spelar även passagerarens förväntningar på det vertikala dynamiska vibrationsbeteendet en växande roll. Speciellt under långa resor på motorvägen där den för nuvarande aktiva föraren blir passagerare, som läser, arbetar eller sover under sin nyvunna tid. De nya användarsenarierna ställer i sin tur nya krav på bilens komfort. Krav som inte har blivit hittills utförligt undersäkta, fastän de kan komma att spela en stor roll i teknikens framgång.Detta examensarbete genomfördes hos BMW:s huvudkontor i Tyskland och hade som mål att undersöka olika maskininlärningsmodeller och deras förmåga att identifiera mönster mellan de subjektiva komfortvärden som rapporterats av deltagarna i en studie, givna på skala 1-7, och de mekaniska vibrationerna som de upplevde mätta i m/s^2. Uppgifterna samlades in i en tidigare oberoende studie. Statistiska metoder användes för att säkerställa datakvaliteten. I detta arbeter har en jämförelse mellan ISO 2631-1-komfortbedömningar och undersökningsresultaten gjorts för att förstå behovet av en mer sofistikerad komfortstandard för att objektifera komfort i självkörande bilar. Arbetet fortsatte med att undersöka olika metoder för att minska datadimensionerna och deras inflytande på modellernas prestanda. Processen som används för att bygga, optimera och validera neurala nätverk och andra modeller är inkluderad i metoddelen och resultaten är presenterade och förklarade därefter. Arbetet avslutas med en diskussion kring både resultatets validitet och modellernas användbarhet.De maskininlärningsmodeller som undersöktes i detta examensarbete har visat stor potential för att upptäcka komplexa mönster som kopplar känslor och tankar till mekaniska variabler. Modellerna kunde förutsäga rätt komfortnivå med upp till 50% precision när 6 eller 7 nivåer av komfort användes. Vid uppdelning i hög mot låg komfort, dvs att kunna förutsäga en av två komfortnivåer, kunde modellerna uppnå en precision på upp till 75.4%.

In globalizing world, increase in demand for high speed rail travel requires comfortable ride over bridges while maintaining an economical design. These bridges either have composite steel I-girders, prestressed precast I or box girder superstructures. The span lengths can reach up to 40 meters. If frequency of wheel load pass at a point on bridge matches with one the critical frequencies of the structure, excessive vibration can developed both at the train and the bridge even if the structure is structurally safe. Excessive vibration can discomfort the passengers. Focus of this study is given to identify certain thresholds for the rigidity of span to minimize the passenger discomfort at short-span composite steel I-girder high speed railroad bridges. In this context, various span lengths with different girder configurations have been analyzed under various train design speeds and ballast stiffness. Eigenvalue analyses are performed to determine critical frequencies of bridges. Moving force models are used to determine structural vibrations as recommended by high speed railroad bridge design specifications. It is well-known that stiffer structures can have significantly less vibration amplitudes than lighter ones providing a comfortable ride for high speed train passes.

Cette thèse porte sur la question de la perception des systèmes d’appuis situés à l’intérieur des transports publics urbains, premières interfaces entre l’usager et le matériel roulant, en vue d’améliorer leur confort. Une exploration a été effectuée afin d’objectiver le toucher des surfaces et tenter de caractériser instrumentalement l’interaction entre le voyageur et la surface d’appui, réduit à un toucher tangentiel et à un contact plan/plan. L’étude, liant tribologie et évaluation sensorielle, montre la difficulté inhérente à la mesure des sensations. Des tendances ont été observées entre les données tribologiques et sensorielles et encouragent à poursuivre dans cette voie. En outre, la question du confort est abordée de manière globale et un nouveau cadre d’étude est proposé. Les réflexions initiées ici souhaitent ouvrir la voie vers une nouvelle approche de la conception, l’approche anthropocentrée, venant compléter la vision actuelle très technocentrée du milieu ferroviaire. / This thesis aims to improve passenger comfort in urban public transports by focusing on the perception of supports in the passenger compartment, which are the primary interfaces between the traveler and the rolling stock. An exploration was carried out in order to objectify the touch of surfaces and try to characterize instrumentally the interaction between the passenger and the support, reduced to a tangential touch and a planar contact surface. The study, linking tribology and sensory evaluation, shows the inherent difficulty of the measure of sensations. Tendencies have been observed between tribological and sensory data and encourage to continue on this path. In addition, the notion of comfort is addressed in a comprehensive manner and a new framework is proposed. The reflections initiated in this research wish to pave the way for a human-centered approach for conception, completing the current vision that is very technocentric in the rail environment.

In response to the planned increase in operational speeds and axle loads of passengertrains that may lead to resonance-induced excessive vibrations in railway bridges,recent studies examined the reliability of bridges concerning train running safety andpassenger comfort limit states. In this respect, valuable information regarding theimportance of input variables can be obtained by conducting Sensitivity Analysis (SA).For instance, the determination of unimportant variables (where they can be treated asconstant) reduces the computational time, which is usually very high for probabilisticsimulations. In some of the previous studies, only deterministic SA has beenperformed. This thesis follows a stochastic approach using Global Sensitivity Analysis(GSA) methods. The considered performance functions are vertical acceleration anddeflection of single track ballasted simply supported reinforced concrete bridges.To reduce the computational time, available semi-analytical solution of a planarbeam under the passage of a series of moving loads is employed. To simulatethe bridge behaviour realistically, simplified methods to account for rail irregularityamplification, train-bridge interactions, and axle load redistribution were adopted.The considered random variables are train modal properties, number of train coaches,bogie spacing, axle spacing and loads, bridge mass, flexural stiffness and damping,and rail amplification factor. The analyses were carried out for a selected set of bridgelengths [10-30]m and a range of train speeds [100-400] km/hr. The study findingsshow that, in both acceleration and displacement, the dynamic response of the bridgeis sensitive to randomness in bridge mass, moment of inertia, coach length, and axleloads. Furthermore, the rail amplification factor and Young’s modulus are primarilyimportant for acceleration and displacement, respectively.

Increasing the operational speed of trains has attracted a lot of interest in the last decades and has brought new challenges, especially in terms of infrastructure design methodology, as it may induce excessive vibrations. Such demands can damage bridges, which in turn increases maintenance costs, endangers the safety of passing trains and disrupts passenger comfort. Conventional design provisions should therefore be evaluated in the light of modern concerns; nevertheless, several previous studies have highlighted some of their shortcomings. It should be emphasized that most of these studies have neglected the uncertainties involved, which preventsthe reported results from representing a complete picture of the problem. In this respect, the present thesis is dedicated to evaluating the performance of conventional design methods, especially those related to running safety and passenger comfort, using probabilistic approaches. To achieve this objective, a preliminary study was carried out using the first-order reliability method for short/medium span bridges passed by trains at a wide range of operating speeds. Comparison of these results with the corresponding deterministic responses showed that applying a constant safety factor to the running safety threshold does not guarantee that the safety index will be identical for all bridges. It also shows that the conventional design approaches result in failure probabilities that are higher than the target values. This conclusion highlights the need to update the design methodology for running safety. However, it would be essential to determine whether running safety is the predominant design criterion before conducting further analysis. Therefore, a stochastic comparison between this criterion and passenger comfort was performed. Due to the significant computational cost of such investigations, subset simulation and crude Monte-Carlo (MC) simulation using meta-models based on polynomial chaos expansion were employed. Both methods were found to perform well, with running safety almost always dominating the passenger comfort limit state. Subsequently, classification-based meta-models, e.g. support vector machines, k-nearest neighbours and decision trees, were combined using ensemble techniques to investigate the influence of soil-structure interaction on the evaluated reliability of running safety. The obtained results showed a significant influence, highlighting the need for detailed investigations in further studies. Finally, a reliability-based design optimization was conducted to update the conventional design method of running safety by proposing minimum requirements for the mass per length and moment of inertia of bridges. It is worth mentioning that the inner loop of the method was solved by a crude MC simulation using adaptively trained Kriging meta-models. / Att öka tågens hastighet har väckt stort intresse under de senaste decennierna och har medfört nya utmaningar, särskilt när det gäller broanalyser, eftersom tågen inducerar stora vibrationer. Sådana vibrationer kan öka underhållskostnaderna, äventyra säkerheten för förbipasserande tåg och påverka passagerarkomforten. Konstruktionsbestämmelser bör därför utvärderas mot bakgrund av dessa problem; dock har flera tidigare studier belyst några av bristerna i dagens bestämmelser. Det bör understrykas att de flesta av dessa studier har försummat de osäkerheter som är involverade, vilket hindrar de rapporterade resultaten från att representera en fullständig bild av problemet. I detta avseende syftar denna avhandling till att utvärdera prestandan hos konventionella analysmetoder, särskilt de som rör körsäkerhet och passagerarkomfort, med hjälp av sannolikhetsmetoder. För att uppnå detta mål genomfördes en preliminär studie med första ordningens tillförlitlighetsnmetod för broar med kort/medellång spännvidd som passeras av tåg med ett brett hastighetsspektrum. Jämförelse av dessa resultat med motsvarande deterministiska respons visade att tillämpa en konstant säkerhetsfaktor för verifieringen av trafiksäkerhet inte garanterar att säkerhetsindexet kommer att vara identiskt för alla broar. Det visar också att de konventionella analysmetoderna resulterar i brottsannolikheter som är högre än målvärdena. Denna slutsats belyser behovet av att uppdatera analysmetoden för trafiksäkerhet. Det skulle emellertid vara viktigt att avgöra om trafiksäkerhet är det dominerande designkriteriet innan ytterligare analyser genomförs. Därför utfördes en stokastisk jämförelse mellan detta kriterium och kriteriet för passagerarkomfort. På grund av den betydande. analystiden för sådana beräkningar användes delmängdssimulering och Monte-Carlo (MC) simulering med metamodeller baserade på polynomisk kaosutvidgning. Båda metoderna visade sig fungera bra, med trafiksäkerhet som nästan alltid dominerade över gränsningstillståndet för passagerarkomfort. Därefter kombinerades klassificeringsbaserade metamodeller som stödvektormaskin och beslutsträd genom ensembletekniker, för att undersöka påverkan av jord-brointeraktion på den utvärderade tillförlitligheten gällande trafiksäkerhet. De erhållna resultaten visade en signifikant påverkan och betonade behovet av detaljerade undersökningar genom ytterligare studier. Slutligen genomfördes en tillförlitlighetsbaserad konstruktionsoptimering för att föreslå ett minimikrav på erforderlig bromassa per längdmeter och tröghetsmoment. Det är värt att nämna att metodens inre loop löstes med en MC-simulering med adaptivt tränade Kriging-metamodeller. / <p>QC 20210910</p>

This study explores the application of multi-agent reinforcement learning (MARL) to enhance the decision-making, safety, and passenger comfort of Autonomous Vehicles (AVs)at uncontrolled intersections. The research aims to assess the potential of MARL in modeling multiple agents interacting within a shared environment, reflecting real-world situations where AVs interact with multiple actors. The findings suggest that AVs trained using aMARL approach with global experiences can better navigate intersection scenarios than AVs trained on local (individual) experiences. This capability is a critical precursor to achieving Level 5 autonomy, where vehicles are expected to manage all aspects of the driving task under all conditions. The research contributes to the ongoing discourse on enhancing autonomous vehicle technology through multi-agent reinforcement learning and informs the development of sophisticated training methodologies for autonomous driving.