Urban homes are vertical. Suburban homes are horizontal. They are two distinct typologies. Both urban and suburban homes relate to their location, vertical like the city, and horizontal like the suburbs. These homes are very recognizable in the American landscape. Suburban homes are 1-2 stories with a garage, a yard, and tree-lined streets. Urban homes are many apartments stacked on top of each other within a single building, each with a small balcony and a parking garage underneath. What about the in between? What happens in the spaces that are not quite urban, and yet not quite suburban? So many people live in these spaces today. They want the excitement and jobs the city offers, but they also want the comfort and space of the suburbs, especially for their families. This building is a response to those spaces, a building that is urban, but is also suburban. / Master of Architecture

Most phenomena in engineering fields involve physical variables that can potentially be predicted using simple or complex mathematical models. However, traffic engineers and researchers are faced with a complex challenge since they have to deal with the human element. For instance, it can be stated that the biggest challenge facing researchers in the area of car-following theory relates to accounting for the human-in-the-loop while modeling the longitudinal motion of the vehicles. In fact, a major drawback of existing car-following models is that the human-in-the-loop is not modeled explicitly. This is specifically important since the output from car-following models directly impacts several other factors and measures of effectiveness, such as vehicle emissions and fuel consumption levels. The main contribution of this research relates to modeling and incorporating, in an explicit and independent manner, the human-in-the-loop component in car-following theory in such a way that it can be either activated or deactivated depending on if a human driver is in control of the vehicle. That would ensure that a car-following model is able to reflect the different control and autonomy levels that a vehicle could be operated under. Besides that, this thesis offers a better understanding of how humans behave and differ from each other. In fact, through the implementation of explicit parameters representing the human-in-the-loop element, the heterogeneity of human behavior, in terms of driving patterns and styles, is captured. To achieve its contributions, the study starts by modifying the maximum acceleration vehicle-dynamics model by explicitly incorporating parameters that aim to model driver behavior in its expression making it suitable for the representation of typical acceleration behavior. The modified variant of the model is demonstrated to have a flexible shape that allows it to model different types of variations that drivers can generate, and to be superior to other similar models in that it predicts more accurate acceleration levels in all domains. The resulting model is then integrated in the Rakha-Pasumarthy-Adjerid car-following model, which uses a steady-state formulation along with acceleration and collision avoidance constraints to model the longitudinal motion of vehicles. The validation of the model using a naturalistic dataset found that the modified formulation successfully integrated the human behavior component in the model and that the new formulation decreases the modeling error. Thereafter, this dissertation proposes a new car-following model, which we term the Fadhloun-Rakha model. Even though structurally different, the developed model incorporates the key components of the Rakha-Pasumarthy-Adjerid model in that it uses the same steady state formulation, respects vehicle dynamics, and uses very similar collision-avoidance strategies to ensure safe following distances between vehicles. Besides offering a better fit to empirical data, the Fadhloun-Rakha model is inclusive of the following characteristics: (1) it models the driver throttle and brake pedal input; (2) it captures driver variability; (3) it allows for shorter than steady-state following distances when following faster leading vehicles; (4) it offers a much smoother acceleration profile; and (5) it explicitly captures driver perception and control inaccuracies and errors. Through a quantitative and qualitative evaluation using naturalistic data, the new model is demonstrated to outperform other state-of-the-practice car-following models. In fact, the model is proved to result in a significant decrease in the modeling error, and to generate trajectories that are highly consistent with the observed car-following behavior. The final part of this study investigates a case in which the driver is excluded and the vehicles are operating in a connected environment. This section aims to showcase a scenario in which the human-in-the-loop is deactivated through the development of a platooning strategy that governs the motion of connected cooperative multi-vehicle platoons. / Doctor of Philosophy / Even though the study of the longitudinal motion of vehicles spanned over several decades leading to the development of more precise and complex car-following models, an important aspect was constantly overlooked in those models. In fact, due to the complexity of modeling the human-in-the-loop, the vehicle and the driver were almost always assumed to represent a single entity. More specifically, ignoring driver behavior and integrating it to the vehicle allowed avoiding to deal with the challenges related to modeling human behavior. The difficulty of mathematically modeling the vehicle and the driver as two independent components rather than one unique system is due to two main reasons. First, there are numerous car models and types that make it difficult to determine the different parameters impacting the performance of the vehicle as they differ from vehicle to vehicle. Second, different driving patterns exist and the fact that they are mostly dependent on human behavior and psychology makes them very difficult to replicate mathematically. The research presented in this thesis provides a comprehensive investigation of the human-in-the-loop component in car-following theory leading to a better understanding of the human-vehicle interaction. This study was initiated due to the noticeable overlooking of driver behavior in the existing literature which, as a result, fails to capture the effect of human control and perception errors.

This thesis presents the use of sliding mode control applied to a 1/10th scale robotic car to operate at a desired slip. Controlling the robot car at any desired slip has a direct relation to the amount of force that is applied to the driving wheels based on road surface conditions. For this model, the desired traction/slip is maintained for a specific surface which happens to be a Lego treadmill platform. How the platform evolved and the robot car was designed are also covered. To parameterize the system dynamics, simulated annealing is used to find the minimal error between mathematical simulations and physical test results. Also discussed is how the robot car and microprocessor can be modeled as a hybrid system. The results from testing the robot car at various desired percent slip show that it is possible to control the slip dynamics of a 1/10th scale automated robotic car and thus pave the way for further studies using scaled model cars to test an automated highway system. / Master of Science

In this study a real-time open loop estimate of the disturbance displacement input to the tire and an external disturbance force, representing handling and aerodynamic forces, acting on the sprung mass of a quarter-car suspension test rig was generated. This information is intended for use in active control methods applied to vehicle suspensions. This estimate is achieved with two acceleration measurements as inputs to the estimator; one each on the sprung and unsprung masses. This method is differentiated from current disturbance accommodating control, bilinear observers, and preview control methods. A description of the quarter-car model and the experimental test rig is given. The equations of motion for the quarter-car model are derived in state space as well as a transfer function form. Several tests were run in simulation to investigate the performance of three integration techniques used in the estimator. These tests were first completed in continuous time prior to transforming to discrete time. Comparisons are made between the simulated and estimated displacement and velocity of the disturbance input to the tire and disturbance force input to the sprung mass. The simulated and estimated dynamic tire normal forces are also compared. This process was necessary to select preliminary values for the integrator transfer function to be implemented in real-time. Using the acceleration measurements from the quarter-car test rig, a quarter-car parameter optimization for use in the estimator was performed. The measured and estimated tire disturbance input, disturbance input velocity, and dynamic tire normal force signals are compared during experimental tests. The results show that the open loop observer provides estimates of the tire disturbance velocity and dynamic tire normal force with acceptable error. The results also indicate the quarter-car test rig behaves linearly within the frequency range and amplitude of the disturbance involved in this study. The resultant access to the disturbance estimate and dynamic tire force estimate in real-time enables pursuit of novel control methods applied to active vibration control of vehicle suspensions. / Master of Science

Passenger car equivalents (PCEs) are used in highway capacity analysis to convert a mixed vehicle flow into an equivalent passenger car flow. This calculation is relevant to capacity and level of service determination, lane requirements, and determining the effect of traffic on highway operations. The most recent Highway Capacity Manual 2000 reports PCEs for basic freeway segments according to percent and length of grade and proportion of heavy vehicles. Heavy vehicles are considered to be either of two categories: trucks and buses or RVs. For trucks and buses, PCEs are reported for a typical truck with a weight to power ratio between 76.1 and 90.4 kg/kW (125 and 150 lb/hp). The weight to power ratio is an indicator of vehicle performance. Recent development of vehicle dynamics models make it possible to define PCEs for trucks with a wider variety of weight to power ratios. PCEs were calculated from the relative impact of trucks on traffic density using the simulation model INTEGRATION. The scope of this research was to evaluate PCEs for basic freeway segments for trucks with a broader range of weight to power ratios. Such results should make freeway capacity analysis more accurate for mixed vehicle flow with a non-typical truck population. In addition, the effect of high proportion of trucks, pavement type and condition, truck aerodynamic treatment, number of freeway lanes, truck speed limit, and level of congestion was considered. The calculation of PCEs for multiple truck weight to power ratio populations was not found to be different from single truck weight to power ratio populations. The PCE values were tabulated in a compatible format to that used in the Highway Capacity Manual 2000. / Master of Science

This research effort aims to compare car-following models when the models are calibrated to individual drivers with the naturalistic data. The models used are the GHR, Gipps, Intelligent Driver, Velocity Difference, Wiedemann, and the Fritzsche model. This research effort also analyzes the Wiedemann car-following model using car-following periods that occur at different speeds. The Wiedemann car-following model uses thresholds to define the different regimes in car following. Some of these thresholds use a speed parameter, but others rely solely upon the difference in speed between the subject vehicle and the lead vehicle. This research effort also reconstructs the Wiedemann car-following model for truck driver behavior using the Naturalistic Truck Driving Study's (NTDS) conducted by Virginia Tech Transportation Institute. This Naturalistic data was collected by equipping 9 trucks with various sensors and a data acquisition system. This research effort also combines the Wiedemann car-following model with the GHR car-following model for trucks using The Naturalistic Truck Driving Study's (NTDS) data. / Master of Science

Microscopic traffic simulation software have gained significant popularity and are widely used both in industry and research mainly because of the ability of these tools to reflect the dynamic nature of the transportation system in a stochastic fashion. To better utilize these software, it is necessary to understand the underlying logic and differences between them. A Car-following model is the core of every microscopic traffic simulation software. In the context of this research, the thesis develops procedures for calibrating the steady-state car-following models in a number of well known microscopic traffic simulation software including: CORSIM, AIMSUN, VISSIM, PARAMICS and INTEGRATION and then compares the VISSIM and INTEGRATION software for the modeling of traffic signalized approaches. The thesis presents two papers. The first paper develops procedures for calibrating the steady-state component of various car-following models using macroscopic loop detector data. The calibration procedures are developed for a number of commercially available microscopic traffic simulation software, including: CORSIM, AIMSUN2, VISSIM, Paramics, and INTEGRATION. The procedures are then applied to a sample dataset for illustration purposes. The paper then compares the various steady-state car-following formulations and concludes that the Gipps and Van Aerde steady-state car-following models provide the highest level of flexibility in capturing different driver and roadway characteristics. However, the Van Aerde model, unlike the Gipps model, is a single-regime model and thus is easier to calibrate given that it does not require the segmentation of data into two regimes. The paper finally proposes that the car-following parameters within traffic simulation software be link-specific as opposed to the current practice of coding network-wide parameters. The use of link-specific parameters will offer the opportunity to capture unique roadway characteristics and reflect roadway capacity differences across different roadways. Second, the study compares the logic used in both the VISSIM and INTEGRATION software, applies the software to some simple networks to highlight some of the differences/similarities in modeling traffic, and compares the various measures of effectiveness derived from the models. The study demonstrates that both the VISSIM and INTEGRATION software incorporate a psycho-physical car-following model which accounts for vehicle acceleration constraints. The INTEGRATION software, however uses a physical vehicle dynamics model while the VISSIM software requires the user to input a vehicle-specific speed-acceleration kinematics model. The use of a vehicle dynamics model has the advantage of allowing the model to account for the impact of roadway grades, pavement surface type, pavement surface condition, and type of vehicle tires on vehicle acceleration behavior. Both models capture a driver's willingness to run a yellow light if conditions warrant it. The VISSIM software incorporates a statistical stop/go probability model while current development of the INTEGRATION software includes a behavioral model as opposed to a statistical model for modeling driver stop/go decisions. Both software capture the loss in capacity associated with queue discharge using acceleration constraints. The losses produced by the INTEGRATION model are more consistent with field data (7% reduction in capacity). Both software demonstrate that the capacity loss is recovered as vehicles move downstream of the capacity bottleneck. With regards to fuel consumption and emission estimation the INTEGRATION software, unlike the VISSIM software, incorporates a microscopic model that captures transient vehicle effects on fuel consumption and emission rates. / Master of Science

For controller design, design of experiments, and other dynamic simulation purposes there is a need to be able to predict the dynamic response and joint reaction forces of a quarter-car suspension. This need is addressed by this study through development and system identification of both a linear and a non-linear multibody dynamics McPherson strut quarter-car suspension model. Both models are developed using a method customary to multibody dynamics so that the same numerical integrator can be used to compare their respective performances. This method involves using the Lagrange multiplier form of the constrained equations of motion to assemble a set of differential algebraic equations that characterize each model's dynamic response. The response of these models to a band-limited random tire displacement time array is then simulated using a Hilber-Hughes-Taylor integrator. The models are constructed to match the dynamic response of a state-of-the-art quarter-car test rig that was designed, constructed, and installed at the Institute for Advanced Learning and Research (IALR) for the Performance Engineering Research Lab (PERL). Attached to the experimental quarter-car rig was the front left McPherson strut suspension from a 2004 Porsche 996 Grand American Cup GS Class race car. This quarter-car rig facilitated acquisition of the experimental reference data to which the simulated data is compared. After developing these models their optimal parameters are obtained by performing system identification. The performance of both models using their respective optimal parameters is presented and discussed in the context of the basic linearity of the experimental suspension. Additionally, a method for estimating the loads applied to the experimental quarter-car rig bearings is developed. Finally, conclusions and recommendations for future research and applications are presented. / Master of Science

Now-a-days safety systems and their advanced features have become a major part of human lives. People are ready to pay accordingly for the features they get for and very enthusiastic towards technology and latest trends. One such thing is drone or multicopter. These days everybody is getting interested in drones to buy, not only the fact that it is used in various scientific ways, sports and recreation purposes but also the latest advancements that was taking place in the development of light weight flying vehicles has made many scientific researchers, multinational companies and almost all the people to turn their eye towards the development of drones. And many companies are doing research for development of new safety features which can be called as the safety for the future. Some companies already introduced drones into the market and are used in different ways for different purposes. The usage of this vehicles depends on how intelligently one uses these multicopters. This thesis introduces a feature that adds safety to the multicopters to prevent them from flying to no-fly-regions. The work in this thesis is done to provide an approach by the usage of Raspberry Pi 2 B for multicopter applications as the main development board. It also helps the multicopter to prevent entering the NFR by detecting the NFRs around them intelligently and avoid them so there shouldn\'t be any problem or damage for the multicopters. Here we use GPS sensor for getting the NMEA data as input to know the latitude and longitude positions and then transferred to RPI2 B which allows us to know the latitude and longitude positions and then transfer this data into database to store the data through a wireless medium i.e., Wi-Fi medium. Based on the information stored in database we can see the location in a graphical manner using the open street maps (OSM). After that different checks are performed to avoid the NFR : (i) We will check if the current point lies inside or outside the no-fly-region based on the map information of NFR using the Point in Polygon algorithm and then (ii) we are using some area based detection 4 algorithm to check the distance from the point to line using Paul Brouke algorithm to see how far is the next NFR from the current point and avoiding it and the information is updated and stored in the database accordingly .(iii) Later, if the multicopter is out of all no-fly-region then the distance to the next NFR or nearest ones is analyzed and the information will be used for safety purpose. By using geometry and algorithms we are checking and finding out the NFRs and avoid entering into the NFR space. If the point is detected inside a no-fly-region then the last point outside this region will be detected which is marked as safe and the multicopter will be backtracked to the previous point before entering the no-fly-region i.e., the safe point. This paper not only aims at multicopter safety but also throws light into the future systems that are going to be developed in the field of Car-2-X, ensuring extended safety of the passengers.

Bakgrund: Studien har undersökt hur köpbeslutsprocessen och det fysiska mötet ser ut i bilhandeln samt om det finns skillnader mellan hur kvinnor och män upplever köpbeslutsprocessen inom bilhandeln. Studiens ämne valdes på grund av att det gjorts tidigare studier inom bilhandeln gällande köpbeslutsprocessen, men att det finns en brist sedan det digitala mötet kom in i bilden. Det har även genomförts flera studier om skillnader mellan mäns och kvinnors skillnader i köpbeteende, men det finns inga som studerar om skillnaderna ser likadana ut i bilbranschen. Forskningsfråga: Studiens huvudfråga lyder: Hur interagerar bilhandeln med kunden i köpbeslutsprocessen genom det fysiska säljmötet för att det ska leda till försäljning av bil? Studiens underfråga lyder: Skiljer sig bilköp åt för män och kvinnor och i sådana fall på vilket sätt? Syfte: Syftet med studien är att undersöka hur bilhandeln kan arbeta vid köpbeslutsprocessen i förhållande till det fysiska säljmötet och vad som gör att kunden genomför ett köp av bil.Vidare är syftet att studera om det finns några skillnader mellan män och kvinnor vid köpet av bil och om det finns, på vilket sätt skiljer de sig. Metod: Den här studien har en kvalitativ undersökningsmetod och ett abduktivt angreppssätt. Resultatet i studien bygger på 12 semistrukturerade intervjuer med respondenter spridda över Sverige. Slutsats: Studien har visat att köpbeslutsprocessen är oförändrad, i sin struktur, av den digitala närvaron. Däremot ser det fysiska mötet annorlunda ut då säljaren behöver inleda med att ta reda på hur långt kunden kommit i sin köpbeslutsprocess. Studiens underfråga har medfört resultat som visar att kvinnors och mäns evolutionära roller byter plats inom bilindustrin då det är män som uppskattar att handla mer hedonistiskt och kvinnor mer funktionellt. / Background: The study has examined how the buying decision process and the physical meeting work in car sales and whether there are differences between how women and men experience the buying decision process in the industry. The subject of the study was chosen due to the fact that there are previous studies in car sales regarding the buying decision process, but that there has been a shortage since the digital meeting came into the picture. There have also been several studies on differences in buying behaviour between men and women, but there are no studies regarding whether the differences look the same in the car industry. Research question: The main question of the study is: How does the car sales interact with the customers in the buying decision process through the physical sales meeting in order for it to lead to sales of a car? The study´s sub question reads: Do car purchase differ for men and women, and in such a case how? Purpose: The purpose of the study is to investigate how car sales can work in the buying decision process in relation to the physical sales meeting and what makes the customer to purchase a car. Furthermore, the aim is to study whether there are any differences between men and women in the purchase of a car and, if there is, how they differ. Method: This study has applied a qualitative method and abductive approach. The results of the study are based on 12 semi-structured interviews with respondents spread across Sweden. Conclusion: The study has shown that the buying decision process is unchanged, in its structure, of the digital presence. However, the physical meeting looks different as the seller needs to start by finding out how far the customer has come in the buying decision process. The study's sub question has resulted in results that show that women and men's evolutionary roles change places in the automotive industry as it is the men who appreciate to buy more hedonic and women more functionally.