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This dissertation consists of three essays on the empirics of firms' strategies in new industries. In the first chapter, I study the spatial mismatch between consumers and bikes in the dockless bike-sharing industry and an externality exacerbating the problem: when a consumer uses a bike for a low and inflexible price, she both displaces another consumer's usage for a potential higher-value trip, and may ride the bike to unpopular destinations. With a trip-level dataset of a bike-sharing company in Beijing, China, I develop a spatial structural model to estimate the demand for bikes with search frictions and local matchings. Compared to the scenario in which consumers always get bikes immediately, I find that local spatial mismatch between consumers and bikes reduces the total usage by 29.95%, or a net loss of 332,979 trips. Counterfactual analyses show that (1) doubling the number of bikes increases the trip volume by 28.46% while halving the number of bikes decreases the trip volume by 46.40%; (2) price-discriminating against short trips by 2% increases the total trip time by 0.22%; and (3) changing the frequency of bike reshuffling does not have a significant impact on the total usage of bikes. In the second chapter, I study how efficient capital markets are in supplying funds to new firms by looking at how a platform start-up, ofo, made its investment decisions in response to capital infusions. I fit the business performance of ofo, a bike-sharing platform start-up, in China and show how its financial conditions affected investment decisions. I analyze the effects of funding rounds from venture capitalists on the investment and business of the company with an event study framework. My estimates find that the firm increased its users and bikes by about 40% two weeks before receiving funds, suggesting that it spent much more on bike fleet and promotional offers in expectation of capital infusions. I also show that such boosts in business performance were short-lived: the number of trips and users often returned to normal levels two weeks after the funding day. My findings suggest that the capital market is inefficient in supplying funds to start-up companies. In the third chapter, I study the shakeout in the U.S. automobile industry with data retrieved from old annals of the automobile industry. I simulate a research productivity model and see if I could successfully trigger a shakeout. I find that only the cost reduction from technology advancements is not enough to trigger an industry shakeout and propose that more extreme settings are needed for further studies.

The vehicle manufacturing sector is constantly evolving, and corporations are fully aware of increased consumer expectations for both driver and passenger´s comfort. SCANIA CV AB, as one of the largest Swedish manufacturers of commercial vehicles, has put an emphasis on this area. To guarantee these high-quality standards, several tests are conducted daily. Within this framework, this project aims to gain a better understanding of the phenomena associated with steering wheel vibrations. This project has an experimental focus on recreating sensitive driving conditions and addressing the vibration transfer paths to the main user interface such as the steering wheel. As widely known, the main problems related to vibrations come from resonance excitations. The most obvious solution would be to simply avoid matching any system´s eigenmodes with external excitations. Considering broadband excitations such as bumpy roads or engine vibrations, it is very unlikely that none of the critical frequencies is triggered. A better and more realistic idea would be minimizing the effects of these resonances by structural optimization. However, to do so, the eigenmodes should first be addressed. For this purpose, this project focused on identifying the annoying frequencies triggered while recreating sensitive driving scenarios. These sensitive scenarios were identified by Scania as circumstances in which the steering wheel feel gets altered. Specifically, it was decided to focus on road-induced vibrations, wheel-induced vibrations and engine-induced vibrations. The main findings show that during these tests, some resonances are triggered and interesting features are captured on the steering wheel. / Fordonstillverkningssektorn växer ständigt och företag är fullt medvetna om ökade konsumentförväntningar på både förarens och passagerarnas komfort. SCANIA CV AB, som en av de största svenska tillverkarna av kommersiella fordon, har lagt vikt vid detta område. För att garantera dessa högkvalitativa standarder genomförs flera tester dagligen.Inom denna ram syftar detta projekt till att få en bättre förståelse för de fenomen som är förknippade med rattvibrationer. Detta projekt har ett experimentellt fokus på att återskapa känsliga körförhållanden och adressera vibrationsöverföringsvägarna till huvudanvändargränssnittet, såsom ratten. Som allmänt känt kommer de största problemen relaterade till vibrationer från resonansexcitationer. Den mest uppenbara lösningen skulle vara att helt enkelt undvika att matcha något systems egenmoder med externa excitationer. Med tanke på bredbandsexcitationer som gropiga vägar eller motorvibrationer är det mycket osannolikt att ingen av de kritiska frekvenserna utlöses. En bättre och mer realistisk idé skulle vara att minimera effekterna av dessa resonanser genom strukturell optimering. För att göra det bör egenmoden först behandlas. För detta ändamål fokuserade detta projekt på att identifiera de irriterande frekvenser som triggades samtidigt som känsliga körscenarier återskapades. Dessa känsliga scenarier identifierades av Scania som omständigheter där rattkänslan förändras. Specifikt beslutades att fokusera på väginducerade vibrationer, hjulinducerade vibrationer och motorinducerade vibrationer. Huvudfynden visar att under dessa tester triggas vissa resonanser och intressanta funktioner fångas på ratten.

Private cars are responsible for 15% of carbon emissions in the European Union. Ride hailing services like taxis could serve the door-to-door mobility demand of private car users with fewer overall vehicles. If the service combines multiple user trips, it might even reduce the distance driven compared to private cars which becomes ecologically sustainable. Such ride sharing services are particularly sustainable when many users share one vehicle. But connecting the trips of all users yields many small detours. These detours reduce if some users walk a short distance to a neighboring stop. When multiple stops are combined, vehicles drive to fewer stops. Such stop pooling promises to make ride sharing even more sustainable. Some ride sharing services already integrate short user walks into their system. But the effects of stop pooling on ride sharing systems are yet to be understood. Methods from theoretical physics like mean-field theory and agent-based modeling enable a systemic analysis of complex ride sharing systems. This thesis demonstrates that ride sharing may be more sustainable when users accept short walks. With stop pooling, users wait shorter for vehicles and drive shorter because of more direct vehicle routes. In consequence, the user travel time decreases on average despite additional walk time at constant fleet size. Put differently, stop pooling allows to reduce the fleet size at constant travel time. This also reduces the distance driven by all vehicles that is proportional to the fleet size when sufficient users share one vehicle. This result is robust in a data-driven model using taxi trip data from Manhattan (New York City, USA) with fluctuating demand over the day. At constant fleet size the travel time fluctuates with the demand and might deviate a lot from the expected average travel time. Such unreliable travel times might deter users from ride sharing. However, stop pooling reduces the travel time, the more the higher the travel time without walking. Consequently, stop pooling also reduces the fluctuations in the travel time. This effect is particularly large when adapting the maximum allowed walk distance to the current demand. In adaptive stop pooling users walk further at higher demand. Then, the travel time in ride sharing is more reliable when users accept short walks. All in all, this thesis contributes to the fundamental understanding of the collective dynamics of ride sharing and the effect of stop pooling at a systemic level while also explaining underlying mechanisms. The results suggest that ride sharing providers and users benefit from integrating adaptive stop pooling into the service. Based on the results, a framework can be established that roughly adjusts fleet size to demand to ensure that the ride sharing service operates sustainably. Even if this fleet size remains constant throughout the day, adaptive stop pooling keeps the travel time reliable.:1. Introduction 1 1.1. Private Cars are Unsustainable . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2. Potentially More Sustainable Ride Sharing Faces Detours . . . . . . . . . . . . . 2 1.3. Less Detours in Ride Sharing with Walking to Pooled Stops . . . . . . . . . . . . 4 1.4. Physics Methods Help Understanding Ride Sharing . . . . . . . . . . . . . . . . . 5 1.5. Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2. Fundamentals - A Physics Perspective on Ride Sharing 7 2.1. State of Research on Ride Sharing . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1. Ride Sharing Systems are Complex . . . . . . . . . . . . . . . . . . . . . . 8 2.1.2. Measuring Efficiency and Sustainability of Ride Sharing Services . . . . . 8 2.1.3. Ride Sharing might be More Sustainable when Users Accept Short Walks 10 2.1.4. Data-Driven Analysis Yields more Detailed Results . . . . . . . . . . . . . 11 2.1.5. Open Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2. Theoretical Physics Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.1. What is a Complex System? . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2.2. Mean-Field Theory Simplifies Complex Systems . . . . . . . . . . . . . . 13 2.2.3. Model Complex Systems Based on Agents, not on Equations . . . . . . . 14 2.2.4. Methods from Statistical Physics to Evaluate Multi-Agent Simulations . . 14 2.2.5. Model Street Networks Using Graph Theory . . . . . . . . . . . . . . . . 20 3. Model for Ride Sharing with Walking to Pooled Stops 25 3.1. Ride Sharing Combines Trips with Similar Directions . . . . . . . . . . . . . . . . 25 3.2. Stop Pooling with Dynamic Stop Locations Maintains Flexibility . . . . . . . . . 26 3.3. Simple Algorithm Assigns Users by Reducing Bus Detour . . . . . . . . . . . . . 28 3.3.1. Standard Ride Sharing Algorithm . . . . . . . . . . . . . . . . . . . . . . 28 3.3.2. Stop Pooling Algorithm at Similar Speed . . . . . . . . . . . . . . . . . . 29 3.4. Basic Setting in Continuous Space . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.4.1. Uniform Request Distribution . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.4.2. Heterogeneous Request Distribution . . . . . . . . . . . . . . . . . . . . . 32 3.5. Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.5.1. Relative Distance Driven Measures Ecological Sustainability . . . . . . . . 33 3.5.2. Measure Service Quality by Average User Travel Time . . . . . . . . . . . 34 3.5.3. Further Observables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.5.4. Bisection Method to Find Minimal Travel Time with Small Effort . . . . 36 3.6. Model Extensions Yield More Detailed Results . . . . . . . . . . . . . . . . . . . 37 3.6.1. Fine-Grained Street Network Enables Short Walk Distances . . . . . . . . 38 iii Contents 3.6.2. Data-Driven Demand is Heterogeneous . . . . . . . . . . . . . . . . . . . . 39 3.6.3. Explicit Stop Times Ensure Penalty For Each Stop . . . . . . . . . . . . . 41 3.6.4. Imbalanced Demand Requires Rebalancing of Buses . . . . . . . . . . . . 42 3.6.5. More Detailed Assignment Algorithm Uses Constraints . . . . . . . . . . 43 4. Quantifying Sustainability of Ride Sharing 45 4.1. Two Mechanisms Influence Ride Sharing Sustainability . . . . . . . . . . . . . . . 46 4.1.1. Pickup Detours Increase Distance Driven . . . . . . . . . . . . . . . . . . 46 4.1.2. Trip Overlap Reduces Distance Driven . . . . . . . . . . . . . . . . . . . . 47 4.2. Distance Driven Reduces with Bus Occupancy . . . . . . . . . . . . . . . . . . . 48 4.3. Ride Sharing is more Sustainable than Private Cars for Sufficient Load . . . . . . 50 4.4. Result is Robust for more Complex Models . . . . . . . . . . . . . . . . . . . . . 52 4.5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5. Ride Sharing Sustainability with Stop Pooling 55 5.1. Ride Sharing Trades Sustainability for Travel Time . . . . . . . . . . . . . . . . . 57 5.2. Stop Pooling is more Sustainable at Same Travel Time . . . . . . . . . . . . . . . 58 5.2.1. Roughly Constant Distance Driven Despite Saved Stops . . . . . . . . . . 58 5.2.2. Stop Pooling Reduces Travel Time . . . . . . . . . . . . . . . . . . . . . . 59 5.2.3. Stop Pooling Breaks The Trade-off Between Sustainability And Travel Time 60 5.3. Higher Stop Pooling Effect for High Loads . . . . . . . . . . . . . . . . . . . . . . 61 5.3.1. Stop Pooling Limits Growth of Best Travel Time . . . . . . . . . . . . . . 62 5.3.2. Stop Pooling Breaks Trade-off for Sufficient Load . . . . . . . . . . . . . . 63 5.4. Robust Effect for Simple Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 5.5. Robust Effect with More Detailed Model . . . . . . . . . . . . . . . . . . . . . . . 66 5.5.1. Load Quantifies Stop Pooling Sustainability . . . . . . . . . . . . . . . . . 67 5.5.2. Already 1.2 Minutes Walk Time might Save 1 Minute Travel Time . . . . 68 5.5.3. Robust Result for Different Parameters . . . . . . . . . . . . . . . . . . . 69 5.6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 6. Ride Sharing Reliability with Stop Pooling 71 6.1. Unreliable Standard Ride Sharing with Fluctuating Demand . . . . . . . . . . . . 72 6.2. More Reliable Stop Pooling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.3. Robust Effect of Stop Pooling with Limited User Delay . . . . . . . . . . . . . . 77 6.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.5. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 7. Discussion 81 7.1. Results and Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.1.1. When is Ride Sharing More Sustainable than Private Cars? . . . . . . . . 81 7.1.2. How Does Stop Pooling Influence Sustainability of Ride Sharing? . . . . . 82 7.1.3. How Does Stop Pooling Influence Reliability of Ride Sharing? . . . . . . . 82 7.2. Limitations of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 7.2.1. Simple Algorithms for Ride Sharing and Stop Pooling . . . . . . . . . . . 82 7.2.2. Integrate Adaptive Stop Pooling into Virtual Bus Stops . . . . . . . . . . 83 7.2.3. Distance Driven as Estimator for Ecological Sustainability . . . . . . . . . 83 7.2.4. Deviations from Load Prediction . . . . . . . . . . . . . . . . . . . . . . . 84 7.2.5. Mean-Field Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 7.2.6. Further Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 7.3. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 A. Appendix 87 A.1. Manhattan Street Network Resembles Grid . . . . . . . . . . . . . . . . . . . . . 87 A.2. Computation Details of Bisection Method . . . . . . . . . . . . . . . . . . . . . . 88 A.3. Average Pickup Distance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 A.4. Robustness of Ride Sharing Sustainability . . . . . . . . . . . . . . . . . . . . . . 90 A.5. Stop Pooling Saves Stops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 A.6. Stop Pooling Effectively Reduces Load . . . . . . . . . . . . . . . . . . . . . . . . 92 A.7. Example Breaking of Trade-off in Simple Model . . . . . . . . . . . . . . . . . . . 93 A.8. Transition in Best Walk Limit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 A.9. Maximal Trade-off Shift Increases with Load . . . . . . . . . . . . . . . . . . . . 95 A.10.Rebalancing Buses is more Important with Constraint . . . . . . . . . . . . . . . 97 A.11.Breaking of Trade-off in Complex Model . . . . . . . . . . . . . . . . . . . . . . . 98 A.12.More Stop Pooling at Destinations and High Demand . . . . . . . . . . . . . . . 99 A.13.Roughly Constant Wait and Drive Time in Adaptive Stop Pooling . . . . . . . . 100 A.14.Influence of Capacity Constraint . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 A.15.Walk Time of Rejected Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Bibliography 101 Acknowledgment 116 Statement of Contributions 118

No description available.

No description available.

Tires are the most influential component of the vehicle as they constitute the only contact between the vehicle and the road and have to generate and transmit forces necessary for the driver to control the vehicle. The demand for the tire models are increasing due to the need to study the variations of force generation mechanisms due to various variables such as load, pressure, speed, and road surface irregularities. Another need from the vehicle manufactures is the study of potential incompatibilities associated with safety systems such as Anti-lock Braking System (ABS) and Electronic Stability Control (ESC) and tires. For vehicle dynamic simulations pertaining to the design of safety systems such as ABS, ESC and ride controllers, an accurate and computationally efficient tire model is required. As these control algorithms become more advanced, they require accurate and extended validity in the range of frequencies required to cover dynamic response due to short wavelength road disturbances, braking and steering torque variations. Major thrust has been provided by the tire industry to develop simulation models that accurately predict the dynamic response of tires without the use of computationally intensive tools such as FEA. The objectives of this research are • To develop, implement and validate a rigid ring tire model and a simulation tool to assist both tire designers and the automotive industry in analyzing the effects of tire belt vibrations, road disturbances, and high frequency brake and steering torque variations on the handling, braking, and ride performances of the vehicle. • To further enhance the tire model by considering dynamic stiffness changes and temperature dependent friction properties. • To develop, and implement novel control algorithms for braking, stability, and ride performance improvements of the vehicle / Ph. D.

Les rides de Barracuda et de Tiburon sont deux reliefs sous-marins situés dans la partie ouest de l'océan Atlantique, là où la lithosphère océanique des plaques Amérique du Nord (NAM) et Amérique du Sud (SAM) est entraînée par subduction sous la plaque Caraïbe, formant l'arc volcanique des Petites Antilles et le prisme d’accrétion de Barbade. Le processus et la période de soulèvement conduisant au relief actuel de ces rides (qui semblent être un marqueur important dans l'histoire géodynamique de la région) sont sujets à débat depuis des décennies.L’interprétation de nouvelles données de sismique réflexion et de bathymétrie multifaisceaux acquises à travers les rides de Barracuda et de Tiburon (campagne Antiplac, 2007 ) a permis de dater les périodes de soulèvements des rides et réaliser des reconstructions paléogéographiques incluant les flux sédimentaires majeurs, depuis le Crétacé jusqu’ à l’Actuel.L’analyse structurale révèle des phases de réactivations tardives d’anciennes zones de fractures dans un contexte transpressif, conduisant aux surrections des rides de Tiburon et de Barracuda.Les processus géologiques possibles impliqués dans la formation des rides de Barracuda et de Tiburon coïncident avec les modèles cinématiques récents décrivant les mouvements relatifs entre les plaques NAM et SAM, le long de la limite de plaque diffuse.Ces résultats permettent de mieux définir la limite de plaque entre NAM et SAM. Elle est nécessairement hétérogène exploitant les zones de faiblesses dans la lithosphère que sont les zones de fracture. Au sein de cette limite de plaque la lithosphère serait donc fragmentée. / The Barracuda Ridge and the Tiburon Rise, two oceanic-basement ridges, lie in the western Atlantic Ocean, where oceanic lithosphere of the North American (NAM) and South American (SAM) plates is subducted beneath the Caribbean plate, creating the Lesser Antilles volcanic arc and the Barbados Ridge accretionary complex. The process and the timing of the uplift leading to the present day morphologies of the Tiburon and Barracuda ridges, that seem to be key markers in the geodynamic history of the region, has remained a matter of debate for decades.From the analysis of new multibeam and seismic reflection profiles acquired in 2007 (Antiplac crusie) DSDP-ODP boreholes available, we provide new information on the timing of the formation of the Barracuda Ridge and Tiburon Rise in their present-day configurations. We propose paleogeographic reconstructions with the main sediments fluxes deposited in the area of the Barracuda and Tiburon ridges from the Late Cretaceous to present. Structural analysis shows reactivation of fracture zones in a transpressive setting leading to the uplifts of the Barracuda and Tiburon Ridges.The location of the Barracuda Ridge and the Tiburon Rise and the timing of the uplift fit well with recent global plate kinematic models describing the movements of NAM relative to SAM along a diffuse plate boundaryThis NAM-SAM plate boundary zone, therefore must most certainly be heterogeneous in nature, exploiting weaknesses in the lithosphere provided by fracture zones where mechanically advantageous, but forming new boundary segments elsewhere, to transfer motion between reactivated segments of the fracture zones.

O tema do conforto na automobilística é bastante extenso e possuidor de muitas interpretações. A ideia central deste trabalho é definir e direcionar alguns métricos para que, durante as fases de conceituação e desenvolvimento de um veículo, seja possível ter um direcional de definição de componentes e atributos veiculares de modo a facilitar o direcionamento dos atributos no programa veicular, e assim atingir suas necessidades. Como exemplo empregado, é empregado um veículo de plataforma tipo B em desenvolvimento por uma montadora, o qual teve as molas de suspensão definidas e rigidezes laterais de eixos com base em material técnico interno equivalente aos estudos apresentados neste trabalho. É adotada uma abordagem inicialmente empírica conforme os primeiros estudos de suspensões independentes realizados neste continente, depois o trabalho é complementado com exigências de normas especificas para vibrações (ISO2361, ISO5008, BS6055) de modo a caracterizar energia vibracional e a interpretação pelo ser humano. Porém como hoje em dia as suspensões automotivas são muito mais complexas, existem componentes específicos para as várias condições de solicitação, deste modo a análise é limitada a situações de ride (conforto) primário e handling (dirigibilidade) em situações de sublimite na faixa linear (cerca de 0,5 g). Como conclusão dos estudos, é possível ter em um veículo atributos de estabilidade sem necessariamente prejudicar o conforto, pois sendo definidos corretamente os componentes elásticos da dinâmica vertical para situações estacionárias e de ride primário, é definido seu equilíbrio estacionário e assim não é necessário comprometimento dos atributos de outros componentes para compensar alguma deficiência existente. / The range of assumptions for ride comfort is considered very wide in the automotive world and they can assume lots of possible interpretations. The central idea in this work is define and manage some metrics that, during the concept and development phases of a vehicular program, be possible to follow a better direction for the attributes development and so reach the program targets. As the example in this work, a B platform typical vehicle is used and it is under development in a carmaker, its suspension springs and axle roll stiffness were setup with technical information similar to the ones presented in this work. The initial approach is empiric as occurred with the first independent suspension system studies in this continent and in the sequence, the work is complemented with standards for vibrational issues (ISO2361, ISO5008, BS6055), after this, finally how the vibrational energy is defined and perceived by human beings. The automotive suspensions of current days are very complex and there are lots of specific components to do a specific work, so the analysis are limited to primary ride and sub limit handling (up to 0,5 g). As conclusion, its possible setup a car that is comfortable and stable in the same time, since the elastic components for the vertical dynamics and steady state conditions are correctly set, so its correct balance is reached and no other components attributes are compromised to compensate any deficiency.

Due to the detrimental effects of ride vibrations on occupants and increasing safety concerns, improvement in vehicle dynamic characteristics has become a key focus of researchers. Typically, ride and handling problems have been dealt with independently. There is a dearth of vehicle models capable of capturing occupant biodynamics and its implication on vehicle ride and handling. Also in general, the objective of conventional control systems has been to attenuate vertical dynamic response of the sprung mass of a vehicle. Feedback control based algorithms are predominantly used in active/semi-active suspensions that ignore the biodynamics of occupants. In the current work, a new 50 degree-of-freedom (DOF) combined nonlinear multi-occupant vehicle model is developed using the lumped parameter modelling (LPM) approach. The current model provides a platform for performing a combined study of ride, handling and occupant biodynamics. The model is capable of simulating the combined effect of sitting occupancies, road inputs and driving maneuvers on biodynamic responses. It is analyzed using MATLAB/SIMULINK functionalities and validated by independently correlating the computed responses with existing experimental results. A study is performed on ride behavior of a vehicle-occupant system under two different transient road inputs. In addition, the effect of road roughness on vehicle ride is also studied. Random road profiles are generated from road roughness spectrum given in the ISO 8608:1995 manual. Insights are developed into the ride dynamics of a vehicle traversing over roads of classes A, B, C and D at given test velocities. The effect of sitting occupancies and vehicle velocities on lateral dynamics is also studied. Results underscore the need for considering sitting occupancies while analyzing vehicle dynamics and also highlight the potential of the current model. Furthermore, a Moore-Penrose Pseudoinverse based feed-forward controller is developed and implemented in an independently acting semi-active seat suspension system. Feasibility of feed-forward control in primary suspensions is also investigated. Finally, issues of stability, performance and limitation of the controller are discussed.