This thesis presents a search for direct and gluino-mediated production of supersymmetric scalar top-quark pairs in the all-hadronic final state using top tagging. The result of search is based on a 13 TeV proton-proton sample collected with the CMS detector at the LHC, corresponding to an integrated luminosity of $36 fb^{-1}$. The results of the search are interpreted in several Simplified Models (SMS).

Traffic assignment models are an important component in analyzing the relationship between demand and supply in the transportation network for design, planning, and control purposes. The static traffic assignment model has been used in practice for several decades. With the latest development in the area of Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS), there is an increasing demand for dynamic traffic assignment models to serve as a basis for studying various issues in these areas.

Existing dynamic user-equilibrium traffic assignment (DUETA) models are mostly expanded from the static user-equilibrium traffic assignment model by intro- ducing the time dimension along with a group of additional constraints. Whereas the equivalency between the solution to the traffic assignment model and the user-equilibrium condition as defined by Wardrop is well established in the static case, the same may not be true for the dynamic case. This paper examines the general form of DUETA models as proposed in previous research and shows that, if queuing behavior is represented in the model at a minimal level, the solution to conventional DUETA models with an objective function of the form Et Xi Jti(t) f(w)dw may not necessarily converge to or approximate the Wardropian user-equilibrium condition in the dynamic sense as defined by many researchers.

Traffic data from single loop detectors are one of the dominant data sources widely used in many traffic operation centers and traveler information systems. Speed estimation from single loop detectors is mainly based on occupancy data, a conversion factor from occupancy to density (which is related to vehicle length), and the assumed relationship between flow, speed, and density. This paper investigates the discrepancy between the speed estimated with single loops and the speed measured directly from double loops. It was found that the inaccuracy of speed estimation with single loops is mainly caused by the irregular behavior of vehicle pace. Under congested or unstable traffic conditions, the distribution of vehicle pace within a given time interval often exhibits a large variance accompanied by a strong skewness. Accuracy in speed estimation can be improved by computing occupancy in a different way, using the median vehicle passage time over the detector as opposed to the mean vehicle passage time often used in the conventional method. The performance of the enhanced speed estimation method is very encouraging. The use of the median vehicle passage time reduces the skewness of pace data.

This report documents our validation effort on the Incremental Transfer (IT) model, which is a macroscopic traffic flow model capable of handling freeway systems with special lanes and priority vehicles. The validation study is performed with field data from a 1.7-mile long freeway segment with a congested off-ramp in Oakland, California. In our study, vehicles exiting the off- ramp of this segment are treated as "regular vehicles" and through vehicles as "special vehicles." By assuming that the exiting or "regular" vehicles must stay on the "near" side lanes, we examine the spatial evolution of separate versus coalesced queues developed in the region resulting from a capacity reduction on the exit ramp. The observed queuing pattern is then compared with that predicted by the IT model. Qualitatively, the IT model yields a queuing pattern similar to the one observed in the field data. The model predicts the separate versus coalesced queues in a way that no other macroscopic traffic flow models can do. However, the predictions of the exact queue location are not accurate. The errors may be caused by the lack of sufficient input information required by the model and the difference between the unique traffic characteristics of the test site and model assumptions.

This paper explores the performance of signal timing plans calibrated with perfect or imperfect information. The arrival information considered include arrival rates and arrival distributions. The study is conducted for different levels of arrival rates and different forms of arrival distributions under a wide range of arrival information inaccuracy, traffic intensity, and intersections with balanced and unbalanced flows.

Our results indicate that the increase in delay, the number of stops, and queue length is in general insignificant when the arrival distribution used to calibrate the optimal timing plan is over- or under-estimated. For the same level of over- or under-estimation, the increase in delay and other measures can be high only when the flow level is very high. The effect, however, is attenuated for overestimation of flow since the cycle length is bounded by a predetermined upper bound. Overall, underestimation of flow appears to be more serious than overestimation of flow in terms of increase in total delay.

Traffic congestion in the Los Angeles region may cost individuals and industry as much as $2 billion a year, in lost time and lost productivity. Much of this cost is borne by the trucking industry and its customers. To address this concern, this report develops and evaluates strategies for reducing congestion delays incurred by less-than-truckload (LTL) motor carriers in Los Angeles.

Describes the computer program BTS which is a macroscopic tool for simulating the performance of freeway bottlenecks

BTS can be used to evaluate a variety of changes in highway design to improve bottlenecks, such as: (1) addition of highway lanes, (2) addition of automated or HOV lanes, or (3) incident management strategies to reduce the frequency, duration and magnitude of incidents. BTS can also be used to project future highway conditions as baselevel traffic grows or driver behavior changes.

The new version of BTS was enhanced to include incident dependencies, variable weather conditions, reneging, and randomly varying traffic volumes. As of yet, BTS is not capable of analyzing highway performance on a network basis. However, even in large networks delays are often dominated by a few key bottlenecks. BTS can be used to study the performance of these key locations.

This paper presents a qualitative description of the evolution of traffic congestion during the morning rush hour in a long freeway leading to a single destination. Traffic is generated at the freeway’s many on - ramps during a short period of time and then is assumed to subside. Capacity limitations create queues on the ramps and the freeway, which is assumed to evolve according with the hydrodynamic theory of traffic flow. A special case that can be described with just a few parameters is analyzed in detail.

The simplicity of our scenario allows the results to be easily verified independently; they can then be used to check whether ‘the existing traffic assignment models are consistent with the basic laws of traffic flow. We found that unreasonable results are obtained with “point queue’’ models, currently a favored approach in the dynamic traffic assignment literature. A computer program, based on the cell transmission model (Daganzo, 1992), is put to the same test.

This study looked at the operations and functions performed at the Caltrans Transportation Management Centers (TMC) with focus on the data sources, data processing, and performance measures. Recommendations are made for making greater use of archived real-time archived data. These include establishing a performance monitoring system, using the data to estimate performance measures, and providing procedures for data processing and dissemination.