Engineering Commons^™

Trajectory Based Traffic Analysis And Control Utilizing Connected Autonomous Vehicles, Yu Wang

USF Tampa Graduate Theses and Dissertations

Recent scholars have developed a number of stochastic car-following models that have successfully captured driver behavior uncertainties and reproduced stochastic traffic oscillation propagation. While elegant frequency domain analytical methods are available for stability analysis of classic deterministic linear car-following models, there lacks an analytical method for quantifying the stability performance of their peer stochastic models and theoretically proving oscillation features observed in the real world. To fill this methodological gap, this study proposes a novel analytical method that measures traffic oscillation magnitudes and reveals oscillation characteristics of stochastic linear car-following models. We investigate a general class of stochastic linear car-following …

Dynamic Prediction Of Runway Configuration And Airport Acceptance Rate, Yuan Wang

USF Tampa Graduate Theses and Dissertations

Automated prediction of runway configuration and airport capacity is critical for the future generation of air traffic management. In the future aviation industry, multi-sources weather forecast information will be available for air traffic decision-making units; how to use these data efficiently is key for overall efficiency of air traffic management. Currently, air traffic management personnel lack tools to assist them to translate weather forecast data into real-time airport capacity. Runway configurations and AARs of airports in a multi-airport system are determined by different air traffic controller personnel. The lack of synchronization may lead to the loss of efficiency of the …

Statistical Learning Of Biomedical Non-Stationary Signals And Quality Of Life Modeling, Mahdi Goudarzi

USF Tampa Graduate Theses and Dissertations

Statistical learning is a set of tools for modeling and understanding complex datasets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning.

The classification of biomedical non-stationary signals such as Electroencephalogram (EEG) is always a challenging problem due to their complexity. The low spatial resolution on the scalp, curse of dimensionality, poor signal-to-noise ratio are disadvantages of working with biomedical signals. EEG signals are unstructured data which needs preprocessing steps to extract informative features which are measurable and predictive. In the first two chapters of this dissertation, EEG …

Statistical Anomaly Detection And Mitigation Of Cyber Attacks For Intelligent Transportation Systems, Ammar Haydari

USF Tampa Graduate Theses and Dissertations

Secure vehicular communication is a critical factor for secure traffic management. Perfect security in intelligent transportation systems (ITS) has solid and efficient intrusion detection systems (IDS). In this paper, we consider false data injection attacks and distributed denial-ofservice attacks (DDoS), especially the stealth low-rate DDoS attacks, targeting the integrity and availability, respectively, in vehicular ad-hoc networks (VANET). Novel statistical intrusion detection and mitigation techniques are proposed for the considered attacks. The performance of the proposed methods are evaluated using a traffic simulator and a real traffic dataset. Comparisons with the state-of-the-art solutions clearly demonstrate the superior performance of the proposed …

Steady State Hydroplaning Risk Analysis And Evaluation Of Unsteady State Effects, Menna Yassin

USF Tampa Graduate Theses and Dissertations

Hydroplaning is a major concern on high speed roadways during heavy rainfall events. Hydroplaning tools are widely used by designers to reduce their roadway’s hydroplaning potential, therefore reducing the possibilities of severe crashes. This dissertation presents two methodologies for improving the prediction of hydroplaning potential.

The first phase focused on improving an existing widely used software called PAVDRN. Using multiple datasets from the Florida Department of Transportation, the author filtered the data using specific criteria to leave only truly dynamic hydroplaning crashes. The author then evaluated PAVDRN’s prediction capabilities and assessed its reliability in predicting a hydroplaning crash. Using past …

Routing And Designing Networks For Two Transportation Problems, Liu Su

USF Tampa Graduate Theses and Dissertations

Routing and designing are essential for transportation networks. With effective routing and designing policies, transportation networks can work safely and efficiently. There are two transportation problems: hazardous materials (hazmat) transportation and warehouse logistics. This dissertation addresses the routing of networks for both problems. For hazmat transportation, the routing can be regulated via network design. Due to catastrophic consequences of potential accidents in hazmat transportation, a risk-averse approach for routing is necessary. In this dissertation, we consider spectral risk measures, for risk-averse hazmat routing. In addition, we introduce a network design problem to select a set of closed road segments for …

Diversity And Network Coded 5g Wireless Network Infrastructure For Ultra-Reliable Communications, Nabeel Ibrahim Sulieman

USF Tampa Graduate Theses and Dissertations

This dissertation is directed towards improving the performance of 5G Wireless Fronthaul Networks and Wireless Sensor Networks, as measured by reliability, fault recovery time, energy consumption, efficiency, and security of transmissions, beyond what is achievable with conventional error control technology. To achieve these ambitious goals, the research is focused on novel applications of networking techniques, such as Diversity Coding, where a feedforward network design uses forward error control across spatially diverse paths to enable reliable wireless networking with minimal delay, in a wide variety of application scenarios. These applications include Cloud-Radio Access Networks (C-RANs), which is an emerging 5G wireless …