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Title: OPTIMIZING DYNAMIC LOGIC REALIZATIONS FOR PARTIAL RECONFIGURATION OF FIELD PROGRAMMABLE GATE ARRAYS.
Creator: Parris, Matthew, DeMara, Ronald, University of Central Florida
Abstract / Description: Many digital logic applications can take advantage of the reconfiguration capability of Field Programmable Gate Arrays (FPGAs) to dynamically patch design flaws, recover from faults, or time-multiplex between functions. Partial reconfiguration is the process by which a user modifies one or more modules residing on the FPGA device independently of the others. Partial Reconfiguration reduces the granularity of reconfiguration to be a set of columns or rectangular region of the device....
Show moreMany digital logic applications can take advantage of the reconfiguration capability of Field Programmable Gate Arrays (FPGAs) to dynamically patch design flaws, recover from faults, or time-multiplex between functions. Partial reconfiguration is the process by which a user modifies one or more modules residing on the FPGA device independently of the others. Partial Reconfiguration reduces the granularity of reconfiguration to be a set of columns or rectangular region of the device. Decreasing the granularity of reconfiguration results in reduced configuration filesizes and, thus, reduced configuration times. When compared to one bitstream of a non-partial reconfiguration implementation, smaller modules resulting in smaller bitstream filesizes allow an FPGA to implement many more hardware configurations with greater speed under similar storage requirements. To realize the benefits of partial reconfiguration in a wider range of applications, this thesis begins with a survey of FPGA fault-handling methods, which are compared using performance-based metrics. Performance analysis of the Genetic Algorithm (GA) Offline Recovery method is investigated and candidate solutions provided by the GA are partitioned by age to improve its efficiency. Parameters of this aging technique are optimized to increase the occurrence rate of complete repairs. Continuing the discussion of partial reconfiguration, the thesis develops a case-study application that implements one partial reconfiguration module to demonstrate the functionality and benefits of time multiplexing and reveal the improved efficiencies of the latest large-capacity FPGA architectures. The number of active partial reconfiguration modules implemented on a single FPGA device is increased from one to eight to implement a dynamic video-processing architecture for Discrete Cosine Transform and Motion Estimation functions to demonstrate a 55-fold reduction in bitstream storage requirements thus improving partial reconfiguration capability.
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Date Issued: 2008
Identifier: CFE0002323, ucf:47793
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002323

Title: Enhancing Cognitive Algorithms for Optimal Performance of Adaptive Networks.
Creator: Lugo-Cordero, Hector, Guha, Ratan, Wu, Annie, Stanley, Kenneth, University of Central Florida
Abstract / Description: This research proposes to enhance some Evolutionary Algorithms in order to obtain optimal and adaptive network configurations. Due to the richness in technologies, low cost, and application usages, we consider Heterogeneous Wireless Mesh Networks. In particular, we evaluate the domains of Network Deployment, Smart Grids/Homes, and Intrusion Detection Systems. Having an adaptive network as one of the goals, we consider a robust noise tolerant methodology that can quickly react to changes in...
Show moreThis research proposes to enhance some Evolutionary Algorithms in order to obtain optimal and adaptive network configurations. Due to the richness in technologies, low cost, and application usages, we consider Heterogeneous Wireless Mesh Networks. In particular, we evaluate the domains of Network Deployment, Smart Grids/Homes, and Intrusion Detection Systems. Having an adaptive network as one of the goals, we consider a robust noise tolerant methodology that can quickly react to changes in the environment. Furthermore, the diversity of the performance objectives considered (e.g., power, coverage, anonymity, etc.) makes the objective function non-continuous and therefore not have a derivative. For these reasons, we enhance Particle Swarm Optimization (PSO) algorithm with elements that aid in exploring for better configurations to obtain optimal and sub-optimal configurations. According to results, the enhanced PSO promotes population diversity, leading to more unique optimal configurations for adapting to dynamic environments. The gradual complexification process demonstrated simpler optimal solutions than those obtained via trial and error without the enhancements.Configurations obtained by the modified PSO are further tuned in real-time upon environment changes. Such tuning occurs with a Fuzzy Logic Controller (FLC) which models human decision making by monitoring certain events in the algorithm. Example of such events include diversity and quality of solution in the environment. The FLC is able to adapt the enhanced PSO to changes in the environment, causing more exploration or exploitation as needed.By adding a Probabilistic Neural Network (PNN) classifier, the enhanced PSO is again used as a filter to aid in intrusion detection classification. This approach reduces miss classifications by consulting neighbors for classification in case of ambiguous samples. The performance of ambiguous votes via PSO filtering shows an improvement in classification, causing the simple classifier perform better the commonly used classifiers.
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Date Issued: 2018
Identifier: CFE0007046, ucf:52003
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007046

Title: Reliability and Robustness Enhancement of Cooperative Vehicular Systems: A Bayesian Machine Learning Perspective.
Creator: Nourkhiz Mahjoub, Hossein, Pourmohammadi Fallah, Yaser, Vosoughi, Azadeh, Yuksel, Murat, Atia, George, Eluru, Naveen, University of Central Florida
Abstract / Description: Autonomous vehicles are expected to greatly transform the transportation domain in the near future. Some even envision that the human drivers may be fully replaced by automated systems. It is plausible to assume that at least a significant part of the driving task will be done by automated systems in not a distant future. Although we are observing a rapid advance towards this goal, which gradually pushes the traditional human-based driving toward more advanced autonomy levels, the full...
Show moreAutonomous vehicles are expected to greatly transform the transportation domain in the near future. Some even envision that the human drivers may be fully replaced by automated systems. It is plausible to assume that at least a significant part of the driving task will be done by automated systems in not a distant future. Although we are observing a rapid advance towards this goal, which gradually pushes the traditional human-based driving toward more advanced autonomy levels, the full autonomy concept still has a long way before being completely fulfilled and realized due to numerous technical and societal challenges. During this long transition phase, blended driving scenarios, composed of agents with different levels of autonomy, seems to be inevitable. Therefore, it is critical to design appropriate driving systems with different levels of intelligence in order to benefit all participants. Vehicular safety systems and their more advanced successors, i.e., Cooperative Vehicular Systems (CVS), have originated from this perspective. These systems aim to enhance the overall quality and performance of the current driving situation by incorporating the most advanced available technologies, ranging from on-board sensors such as radars, LiDARs, and cameras to other promising solutions e.g. Vehicle-to-Everything (V2X) communications. However, it is still challenging to attain the ideal anticipated benefits out of the cooperative vehicular systems, due to the inherent issues and challenges of their different components, such as sensors' failures in severe weather conditions or the poor performance of V2X technologies under dense communication channel loads. In this research we aim to address some of these challenges from a Bayesian Machine- Learning perspective, by proposing several novel ideas and solutions which facilitate the realization of more robust, reliable, and agile cooperative vehicular systems. More precisely, we have a two-fold contribution here. In one aspect, we have investigated the notion of Model-Based Communications (MBC) and demonstrated its effectiveness for V2X communication performance enhancement. This improvement is achieved due to the more intelligent communication strategy of MBC in comparison with the current state-of-the-art V2X technologies. Essentially, MBC proposes a conceptual change in the nature of the disseminated and shared information over the communication channel compared to what is being disseminated in current technologies. In the MBC framework, instead of sharing the raw dynamic information among the network agents, each agent shares the parameters of a stochastic forecasting model which represents its current and future behavior and updates these parameters as needed. This model sharing strategy enables the receivers to precisely predict the future behaviors of the transmitter even when the update frequency is very low. On the other hand, we have also proposed receiver-side solutions in order to enhance the CVS performance and reliability and mitigate the issues caused by imperfect communication and detection processes. The core concept for these solutions is incorporating other informative elements in the system to compensate for the lack of information which is lost during the imperfect communication or detection phases. For proof of concept, we have designed an adaptive FCW framework which considers the driver's feedbacks to the CVS system. This adaptive framework mitigates the negative impact of imperfectly received or detected information on system performance, using the inherent information of these feedbacks and responses. The effectiveness and superiority of this adaptive framework over traditional design has been demonstrated in this research.
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Date Issued: 2019
Identifier: CFE0007845, ucf:52807
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007845

Title: STUDY OF DESIGN FOR RELIABILITY OF RF AND ANALOG CIRCUITS.
Creator: Tang, Hongxia, Yuan, Jiann-Shiun, Wu, Xinzhang, Sundaram, Kalpathy, Chow, Lee, University of Central Florida
Abstract / Description: Due to continued device dimensions scaling, CMOS transistors in the nanometer regime have resulted in major reliability and variability challenges. Reliability issues such as channel hot electron injection, gate dielectric breakdown, and negative bias temperature instability (NBTI) need to be accounted for in the design of robust RF circuits. In addition, process variations in the nanoscale CMOS transistors are another major concern in today's circuits design.An adaptive gate-source biasing...
Show moreDue to continued device dimensions scaling, CMOS transistors in the nanometer regime have resulted in major reliability and variability challenges. Reliability issues such as channel hot electron injection, gate dielectric breakdown, and negative bias temperature instability (NBTI) need to be accounted for in the design of robust RF circuits. In addition, process variations in the nanoscale CMOS transistors are another major concern in today's circuits design.An adaptive gate-source biasing scheme to improve the RF circuit reliability is presented in this work. The adaptive method automatically adjusts the gate-source voltage to compensate the reduction in drain current subjected to various device reliability mechanisms. A class-AB RF power amplifier shows that the use of a source resistance makes the power-added efficiency robust against threshold voltage and mobility variations, while the use of a source inductance is more reliable for the input third-order intercept point.A RF power amplifier with adaptive gate biasing is proposed to improve the circuit device reliability degradation and process variation. The performances of the power amplifier with adaptive gate biasing are compared with those of the power amplifier without adaptive gate biasing technique. The adaptive gate biasing makes the power amplifier more resilient to process variations as well as the device aging such as mobility and threshold voltage degradation. Injection locked voltage-controlled oscillators (VCOs) have been examined. The VCOs are implemented using TSMC 0.18 (&)#181;m mixed-signal CMOS technology. The injection locked oscillators have improved phase noise performance than free running oscillators.A differential Clapp-VCO has been designed and fabricated for the evaluation of hot electron reliability. The differential Clapp-VCO is formed using cross-coupled nMOS transistors, on-chip transformers/inductors, and voltage-controlled capacitors. The experimental data demonstrate that the hot carrier damage increases the oscillation frequency and degrades the phase noise of Clapp-VCO.A p-channel transistor only VCO has been designed for low phase noise. The simulation results show that the phase noise degrades after NBTI stress at elevated temperature. This is due to increased interface states after NBTI stress. The process variability has also been evaluated.
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Date Issued: 2012
Identifier: CFE0004223, ucf:49000
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004223

Title: Simulation-Based Cognitive Workload Modeling and Evaluation of Adaptive Automation Invoking and Revoking Strategies.
Creator: Rusnock, Christina, Geiger, Christopher, Karwowski, Waldemar, Xanthopoulos, Petros, Reinerman, Lauren, University of Central Florida
Abstract / Description: In human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is...
Show moreIn human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is one potential solution to resolve these issues, while maintaining the benefits of traditional automation. Adaptive automation occurs dynamically, with the quantity of automated tasks changing in real-time to meet performance or workload goals. While numerous studies evaluate the relative performance of manual and adaptive systems, little attention has focused on the implications of selecting particular invoking or revoking strategies for adaptive automation. Thus, evaluations of adaptive systems tend to focus on the relative performance among multiple systems rather than the relative performance within a system.This study takes an intra-system approach specifically evaluating the relationship between cognitive workload and situational awareness that occurs when selecting a particular invoking-revoking strategy for an adaptive system. The case scenario is a human supervisory control situation that involves a system operator who receives and interprets intelligence outputs from multiple unmanned assets, and then identifies and reports potential threats and changes in the environment. In order to investigate this relationship between workload and situational awareness, discrete event simulation (DES) is used. DES is a standard technique in the analysis of systems, and the advantage of using DES to explore this relationship is that it can represent a human-computer system as the state of the system evolves over time. Furthermore, and most importantly, a well-designed DES model can represent the human operators, the tasks to be performed, and the cognitive demands placed on the operators. In addition to evaluating the cognitive workload to situational awareness tradeoff, this research demonstrates that DES can quite effectively model and predict human cognitive workload, specifically for system evaluation.This research finds that the predicted workload of the DES models highly correlates with well-established subjective measures and is more predictive of cognitive workload than numerous physiological measures. This research then uses the validated DES models to explore and predict the cognitive workload impacts of adaptive automation through various invoking and revoking strategies. The study provides insights into the workload-situational awareness tradeoffs that occur when selecting particular invoking and revoking strategies. First, in order to establish an appropriate target workload range, it is necessary to account for both performance goals and the portion of the workload-performance curve for the task in question. Second, establishing an invoking threshold may require a tradeoff between workload and situational awareness, which is influenced by the task's location on the workload-situational awareness continuum. Finally, this study finds that revoking strategies differ in their ability to achieve workload and situational awareness goals. For the case scenario examined, revoking strategies based on duration are best suited to improve workload, while revoking strategies based on revoking thresholds are better for maintaining situational awareness.
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Date Issued: 2013
Identifier: CFE0004927, ucf:49607
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004927

Title: BIOSIGNAL PROCESSING CHALLENGES IN EMOTION RECOGNITIONFOR ADAPTIVE LEARNING.
Creator: Vartak, Aniket, Mikhael, Wasfy, University of Central Florida
Abstract / Description: User-centered computer based learning is an emerging field of interdisciplinary research. Research in diverse areas such as psychology, computer science, neuroscience and signal processing is making contributions the promise to take this field to the next level. Learning systems built using contributions from these fields could be used in actual training and education instead of just laboratory proof-of-concept. One of the important advances in this research is the detection and assessment of...
Show moreUser-centered computer based learning is an emerging field of interdisciplinary research. Research in diverse areas such as psychology, computer science, neuroscience and signal processing is making contributions the promise to take this field to the next level. Learning systems built using contributions from these fields could be used in actual training and education instead of just laboratory proof-of-concept. One of the important advances in this research is the detection and assessment of the cognitive and emotional state of the learner using such systems. This capability moves development beyond the use of traditional user performance metrics to include system intelligence measures that are based on current neuroscience theories. These advances are of paramount importance in the success and wide spread use of learning systems that are automated and intelligent. Emotion is considered an important aspect of how learning occurs, and yet estimating it and making adaptive adjustments are not part of most learning systems. In this research we focus on one specific aspect of constructing an adaptive and intelligent learning system, that is, estimation of the emotion of the learner as he/she is using the automated training system. The challenge starts with the definition of the emotion and the utility of it in human life. The next challenge is to measure the co-varying factors of the emotions in a non-invasive way, and find consistent features from these measures that are valid across wide population. In this research we use four physiological sensors that are non-invasive, and establish a methodology of utilizing the data from these sensors using different signal processing tools. A validated set of visual stimuli used worldwide in the research of emotion and attention, called International Affective Picture System (IAPS), is used. A dataset is collected from the sensors in an experiment designed to elicit emotions from these validated visual stimuli. We describe a novel wavelet method to calculate hemispheric asymmetry metric using electroencephalography data. This method is tested against typically used power spectral density method. We show overall improvement in accuracy in classifying specific emotions using the novel method. We also show distinctions between different discrete emotions from the autonomic nervous system activity using electrocardiography, electrodermal activity and pupil diameter changes. Findings from different features from these sensors are used to give guidelines to use each of the individual sensors in the adaptive learning environment.
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Date Issued: 2010
Identifier: CFE0003301, ucf:48503
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0003301

Title: Driving performance adaptation through practice with and without distracters in a simulated environment.
Creator: Gentzler, Marc, Smither, Janan, Neider, Mark, Rinalducci, Edward, Mcconnell, Daniel, Ray, Roger, University of Central Florida
Abstract / Description: A preponderance of research points to the detrimental effects of distraction on driving performance. An interesting question is whether practice can improve distracted driving. The results from the few longitudinal simulator-based research studies conducted on driving distraction have been inconclusive. This may be because practice effects could be confounded with participants adapting to driving in the simulator. Therefore, participants in the current studies were trained until performance...
Show moreA preponderance of research points to the detrimental effects of distraction on driving performance. An interesting question is whether practice can improve distracted driving. The results from the few longitudinal simulator-based research studies conducted on driving distraction have been inconclusive. This may be because practice effects could be confounded with participants adapting to driving in the simulator. Therefore, participants in the current studies were trained until performance reached a steady state prior to introducing the distracters.In this dissertation, two single-subject design studies were used to investigate the effects of training on distracted driving. The first study included two participants who experienced several different types of distracters. In the second study distracters were introduced before and after the training phase. The two distracters selected for Study 2 included conversing on a handheld phone and texting on a touchscreen phone continuously while driving in a city scenario. Previous research has not compared texting to phone, has had relatively littleexamination of texting and driving alone, and has primarily focused on hands-free phones and on highway settings. Participants drove on a city route which they had previously memorized to add realism to the driving task. Measures collected included speed maintenance, lane deviations/position errors, stop errors, and turn errors in both studies. In Study 2, subjective workload and reaction time were also collected.Findings indicated that training improved performance substantially for all participants in both studies compared to the initial baseline. Participants who experienced six and even nine sessions of the initial baseline did not necessarily improve more than those who only had three sessions. Performance for some participants did not improve in the initial baseline. The lower error levels in training remained fairly stable in subsequent baselines showing that actual learning did occur. Texting had higher error levels than phone both pre and post-training. There were no practice effects noticed for the distracters post-training for any of the participants, and in fact errors increased across sessions for phone and especially texting in Study 2. Training helped improve performance during the phone distraction more so than texting overall, although this varied for different dependent measures. Although errors were reduced after training in the distracter phases, the data actually showed that the performance difference between the baselines and the distracters pre-training was smaller than the differences post-training. Based on these findings, it is recommended that researchers conducting driving simulation research systematically train their participants on driving the simulator before they begin data collection.
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Date Issued: 2014
Identifier: CFE0005169, ucf:50658
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005169

Title: Microgrid Control and Protection: Stability and Security.
Creator: Keshavarztalebi, Morteza, Behal, Aman, Haralambous, Michael, Sun, Wei, Jain, Amit Kumar, Kutkut, Nasser, University of Central Florida
Abstract / Description: When the microgrid disconnects from the main grid in response to, say, upstream disturbance orvoltage fluctuation and goes to islanding mode, both voltage and frequency at all locations in themicrogrid have to be regulated to nominal values in a short amount of time before the operation ofprotective relays. Motivated by this, we studied the application of intelligent pinning of distributed cooperative secondary control of distributed generators in islanded microgrid operation in a power...
Show moreWhen the microgrid disconnects from the main grid in response to, say, upstream disturbance orvoltage fluctuation and goes to islanding mode, both voltage and frequency at all locations in themicrogrid have to be regulated to nominal values in a short amount of time before the operation ofprotective relays. Motivated by this, we studied the application of intelligent pinning of distributed cooperative secondary control of distributed generators in islanded microgrid operation in a power system. In the first part, the problem of single and multi-pinning of distributed cooperative secondary control of DGs in a microgrid is formulated. It is shown that the intelligent selection of a pinning set based on the number of its connections and distance of leader DG/DGs from the rest of the network, i.e., degree of connectivity, strengthens microgrid voltage and frequency regulation performance both in transient and steady state. The proposed control strategy and algorithm are validated by simulation in MATLAB/SIMULINK using different microgrid topologies. It is shown that it is much easier to stabilize the microgrid voltage and frequency in islanding mode operationby specifically placing the pinning node on the DGs with high degrees of connectivity than byrandomly placing pinning nodes into the network. In all of these research study cases, DGs areonly required to communicate with their neighboring units which facilitates the distributed controlstrategy.Historically, the models for primary control are developed for power grids with centralized powergeneration, in which the transmission lines are assumed to be primarily inductive. However, fordistributed power generation, this assumption does not hold since the network has significant resistive impedance as well. Hence, it is of utmost importance to generalize the droop equations, i.e., primary control, to arrive at a proper model for microgrid systems. Motivated by this, we proposed the secondary adaptive voltage and frequency control of distributed generators for low and medium voltage microgrid in autonomous mode to overcome the drawback of existing classical droop based control techniques. Our proposed secondary control strategy is adaptive with line parameters and can be applied to all types of microgrids to address the simultaneous impacts of active and reactive power on the microgrids voltage and frequency. Also, since the parameters in the network model are unknown or uncertain, the second part of our research studies adaptive distributed estimation/compensation. It is shown that this is an effective method to robustly regulate the microgrid variables to their desired values.The security of power systems against malicious cyberphysical data attacks is the third topic of this dissertation. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.
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Date Issued: 2016
Identifier: CFE0006338, ucf:51569
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006338

Title: Optimal Switch Timing for Piezoelectric-Based Semi-Active Vibration Reduction Techniques.
Creator: Kelley, Christopher, Kauffman, Jeffrey, Das, Tuhin, Xu, Yunjun, University of Central Florida
Abstract / Description: Semi-active vibration reduction techniques switch a piezoelectric transducer between an open circuit and a shunt circuit in a way that reduces vibration. The steady-state vibration amplitude is reduced by exploiting the change in stiffness between states, manipulating the converted electrical energy, or both. Semi-active techniques typically require four switches per vibration cycle. Control laws such as state switching and synchronized switch damping require switches to occur at every...
Show moreSemi-active vibration reduction techniques switch a piezoelectric transducer between an open circuit and a shunt circuit in a way that reduces vibration. The steady-state vibration amplitude is reduced by exploiting the change in stiffness between states, manipulating the converted electrical energy, or both. Semi-active techniques typically require four switches per vibration cycle. Control laws such as state switching and synchronized switch damping require switches to occur at every displacement extrema. Due to the complexity of analyzing a system with discrete switches, these control laws were developed based on intuition. The few analyses that attempt to determine an optimal switching law mathematically only evaluate the system at resonance. This thesis investigates the effects of switch timing on vibration reduction and the frequency dependence of the optimal switch timing control law. Regardless of the switch timing, sensing uncertainties, noise, and modeling errors can cause the switches to occur away from the designed moment. Thus, this work also quantifies the expected degradation in vibration reduction performance due to variations in the designed switch time. Experimental, numerical, and analytical solutions agree that the optimal switch timing of these semi-active techniques depends on frequency. A closed-form solution for the optimal switch timing is derived in terms of well-known, non-dimensional parameters.
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Date Issued: 2016
Identifier: CFE0006336, ucf:51555
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006336

Title: Enhancing the effectiveness of Human-Robot teaming with a closed-loop system.
Creator: Teo, Grace, Szalma, James, Jentsch, Florian, Hancock, Peter, Matthews, Gerald, Reinerman, Lauren, University of Central Florida
Abstract / Description: With the development in robotics and the increasing deployment of robots, human-robot teams are set to be a mainstay in the future. However, our understanding of the effectiveness and impact of this new form of teaming is limited. Previous experience with technology and automa-tion has shown that technological aids do not always result in the intended consequences of im-proved performance and alleviation of workload and stress. No doubt a large part of this is due to the fact that the...
Show moreWith the development in robotics and the increasing deployment of robots, human-robot teams are set to be a mainstay in the future. However, our understanding of the effectiveness and impact of this new form of teaming is limited. Previous experience with technology and automa-tion has shown that technological aids do not always result in the intended consequences of im-proved performance and alleviation of workload and stress. No doubt a large part of this is due to the fact that the relationships among taskload, workload and performance are complex as hu-man operators interact dynamically with tasks and technology. Measures of workload are also varied and differentially sensitive. There is also the added challenge posed by multi-tasking envi-ronments which typify most real-world situations. Given all this, efforts in designing technologi-cal aids, such as an adaptive robot aid in the context of human-robot teaming, would require a workload model that reflects the intricate relationship between taskload and the individual opera-tor's experience of workload. Such a model can then be used to drive a closed-loop system on which adaptive robot aiding can be based. The present research sought to investigate the effec-tiveness of a closed-loop system, based on a model of workload, in enhancing performance in a simulated military mission involving a human-robot team. Results showed that adaptive robot aid driven by workload needs as assessed by physiological measures resulted in greater improve-ments in performance compared to robot aid that was imposed by the system.
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Date Issued: 2015
Identifier: CFE0006403, ucf:51485
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006403

Title: The Effect of Repeated Sprint Training in Hypoxia and Beta-Alanine Supplementation On Exercise Performance.
Creator: Wang, Ran, Hoffman, Jay, Fukuda, David, Stout, Jeffrey, Kang, Jie, University of Central Florida
Abstract / Description: The primary objective of this study was to evaluate the synergistic effects of repeated sprint training in hypoxia (RSH) and beta-alanine supplementation on performance in recreationally active men. Participants were randomly assigned to one of the following groups: hypoxia + beta-alanine (HB, n = 10), hypoxia + placebo (HP, n = 9), normoxia + beta-alanine (NB, n = 11) and normoxia + placebo (NP, n = 8). All participants completed a total of 8 training sessions (each consisting of 3 sets of 5...
Show moreThe primary objective of this study was to evaluate the synergistic effects of repeated sprint training in hypoxia (RSH) and beta-alanine supplementation on performance in recreationally active men. Participants were randomly assigned to one of the following groups: hypoxia + beta-alanine (HB, n = 10), hypoxia + placebo (HP, n = 9), normoxia + beta-alanine (NB, n = 11) and normoxia + placebo (NP, n = 8). All participants completed a total of 8 training sessions (each consisting of 3 sets of 5 (&)#215; 10-s sprints at a resistance of 7.5% of body mass, with 20-s rest intervals between sprints) over 4 weeks on a cycle ergometer either in hypoxia (Oxygen fraction: FiO2 = 14.2%) or normoxia (FiO2 = 20.9%). Participants were instructed to consume a daily dosage of 6.4g (two 800 mg tablets ingested 4 times per day at 3-4 hour intervals) of either beta-alanine or placebo. Changes in performance in a graded exercise test (GXT), repeated sprint test (RST) and 3-min all-out test (3MT) were examined before and after 28-days of training and supplementation. Aerobic performance was measured by maximal oxygen consumption (VO2max), peak power output (PPO). Exercise intolerance was assessed from critical power (CP), oxygen consumption (VO2RCP) and power output (PRCP) at respiratory compensation point. Exercise capacity was measured by total work (TW) during 3MT. Anaerobic capacity was evaluated via anaerobic working capacity (AWC), heart rate response to RST (RST_HR60) and lactate responses to RST (RST_La) and 3MT (3MT_La). Repeated sprint performance was estimated through average power output of the last sprint (RST_AP5) and all sprints (RST_AP). No between-group differences were observed for training volume or supplementation compliance. Anthropometric and hematological measures remain unchanged before and after intervention in all groups. A main effect of altitude was shown for VO2RCP, PRCP, RST_AP5, RST_HR60, and TW, with post-intervention values in the hypoxia groups significantly (p (<) 0.05) higher (lower for RST_HR60) than the normoxia groups. A main effect of beta-alanine was detected in AWC, with post-intervention values in the beta-alanine groups being significantly (p (<) 0.05) higher than the placebo groups. Results of this investigation demonstrated that RSH and beta-alanine benefit performance from different perspectives. RSH improved aerobic performance, exercise tolerance, cardiovascular recovery and exercise capacity, while beta-alanine supplementation maintained anaerobic working capacity in recreationally-trained men during the four-week repeated sprint training intervention.
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Date Issued: 2017
Identifier: CFE0006961, ucf:51633
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006961

Title: Reduced Susceptibility of Deformation due to Vibrational and Gravitational Effects on a Focus Variable Adaptive Lens.
Creator: Relina, Victoriya, Wu, Shintson, Likamwa, Patrick, Delfyett, Peter, University of Central Florida
Abstract / Description: Orthodox optical devices, such as lenses, mirrors, and prisms, are composed of solid-state materials, which although well studied and implemented ubiquitously are severely limited in their adaptable properties. An arguably new field of adaptive optics has emerged to further expand photonic manipulation competences of optical components. Fluid-based adaptive optical components were introduced as early as 1968; such components have the ability to change the shape of their interface surface,...
Show moreOrthodox optical devices, such as lenses, mirrors, and prisms, are composed of solid-state materials, which although well studied and implemented ubiquitously are severely limited in their adaptable properties. An arguably new field of adaptive optics has emerged to further expand photonic manipulation competences of optical components. Fluid-based adaptive optical components were introduced as early as 1968; such components have the ability to change the shape of their interface surface, thus allowing for a variable curvature profile. The method of manipulation varies greatly, as does the range of surface deformations. A solid-state optical component is affected by system vibration variation only (difference in vibration from one component to the other due to damping effect). By comparison, two large limiting factors of a fluid-based adaptive optical component are the effect of local vibrations on the surface of the device and gravitational effect (when the optical axis of a lens is positioned parallel to gravitational pull). Such a gravitational effect has been mitigated by the invention of the mechanical electrowetting lens, which uses density matching of two liquids that make up an adaptive lens. However, this configuration creates an extra limiting factor of density matching two optically clear fluids with a desirable transmission spectrum. This method can also become bulky when a large aperture is needed. In this thesis, two adaptive lens systems are explored. Principles of operation, performance, limitations, as well as future improvements are studied and theorized. The first lens uses an optically clear elastomer as the substrate of an adaptive lens and a primitive mechanical manipulation to turn a plano(-)plano lens into a plano(-)convex lens. The second lens is composed of an optically clear gel rather than a fluid. Both methods exhibit excellent optical properties regardless of the orientation about the gravitational pull and significantly limit local vibration affects simply by the physical nature of the chosen materials.
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Date Issued: 2013
Identifier: CFE0004739, ucf:49841
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004739

Title: bio-inspired attitude control of micro air vehicles using rich information from airflow sensors.
Creator: Shen, He, Xu, Yunjun, Lin, Kuo-Chi, Kauffman, Jeffrey, An, Linan, University of Central Florida
Abstract / Description: Biological phenomena found in nature can be learned and customized to obtain innovative engineering solutions. In recent years, biologists found that birds and bats use their mechanoreceptors to sense the airflow information and use this information directly to achieve their agile flight performance. Inspired by this phenomenon, an attitude control system for micro air vehicles using rich amount of airflow sensor information is proposed, designed and tested. The dissertation discusses our...
Show moreBiological phenomena found in nature can be learned and customized to obtain innovative engineering solutions. In recent years, biologists found that birds and bats use their mechanoreceptors to sense the airflow information and use this information directly to achieve their agile flight performance. Inspired by this phenomenon, an attitude control system for micro air vehicles using rich amount of airflow sensor information is proposed, designed and tested. The dissertation discusses our research findings on this topic. First, we quantified the errors between the calculated and measured lift and moment profiles using a limited number of micro pressure sensors over a straight wing. Then, we designed a robust pitching controller using 20 micro pressure sensors and tested the closed-loop performance in a simulated environment. Additionally, a straight wing was designed for the pressure sensor based pitching control with twelve pressure sensors, which was then tested in our low-speed wind tunnel. The closed-loop pitching control system can track the commanded angle of attack with a rising time around two seconds and an overshoot around 10%. Third, we extended the idea to the three-axis attitude control scenarios, where both of the pressure and shear stress information are considered in the simulation. Finally, a fault tolerant controller with a guaranteed asymptotically stability is proposed to deal with sensor failures and calculation errors. The results show that the proposed fault tolerant controller is robust, adaptive, and can guarantee an asymptotically stable performance even in case that 50% of the airflow sensors fail in flight.
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Date Issued: 2014
Identifier: CFE0005711, ucf:50150
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005711

Title: OPTIMIZING THE DESIGN OF MULTIMODAL USER INTERFACES.
Creator: Reeves, Leah, Stanney, Kay, University of Central Florida
Abstract / Description: Due to a current lack of principle-driven multimodal user interface design guidelines, designers may encounter difficulties when choosing the most appropriate display modality for given users or specific tasks (e.g., verbal versus spatial tasks). The development of multimodal display guidelines from both a user and task domain perspective is thus critical to the achievement of successful human-system interaction. Specifically, there is a need to determine how to design task information...
Show moreDue to a current lack of principle-driven multimodal user interface design guidelines, designers may encounter difficulties when choosing the most appropriate display modality for given users or specific tasks (e.g., verbal versus spatial tasks). The development of multimodal display guidelines from both a user and task domain perspective is thus critical to the achievement of successful human-system interaction. Specifically, there is a need to determine how to design task information presentation (e.g., via which modalities) to capitalize on an individual operator's information processing capabilities and the inherent efficiencies associated with redundant sensory information, thereby alleviating information overload. The present effort addresses this issue by proposing a theoretical framework (Architecture for Multi-Modal Optimization, AMMO) from which multimodal display design guidelines and adaptive automation strategies may be derived. The foundation of the proposed framework is based on extending, at a functional working memory (WM) level, existing information processing theories and models with the latest findings in cognitive psychology, neuroscience, and other allied sciences. The utility of AMMO lies in its ability to provide designers with strategies for directing system design, as well as dynamic adaptation strategies (i.e., multimodal mitigation strategies) in support of real-time operations. In an effort to validate specific components of AMMO, a subset of AMMO-derived multimodal design guidelines was evaluated with a simulated weapons control system multitasking environment. The results of this study demonstrated significant performance improvements in user response time and accuracy when multimodal display cues were used (i.e., auditory and tactile, individually and in combination) to augment the visual display of information, thereby distributing human information processing resources across multiple sensory and WM resources. These results provide initial empirical support for validation of the overall AMMO model and a sub-set of the principle-driven multimodal design guidelines derived from it. The empirically-validated multimodal design guidelines may be applicable to a wide range of information-intensive computer-based multitasking environments.
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Date Issued: 2007
Identifier: CFE0001636, ucf:47237
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001636

Title: SIGNAL PROCESSING OF AN ECG SIGNALIN THE PRESENCE OF A STRONG STATIC MAGNETIC FIELD.
Creator: Gupta, Aditya, Weeks, Arthur, University of Central Florida
Abstract / Description: This dissertation addresses the problem of elevation of the T wave of an electrocardiogram (ECG) signal in the magnetic resonance imaging (MRI). In the MRI, due to the strong static magnetic field the interaction of the blood flow with this strong magnetic field induces a voltage in the body. This voltage appears as a superimposition at the locus of the T wave of the ECG signal. This looses important information required by the doctors to interpret the ST segment of the ECG and detect...
Show moreThis dissertation addresses the problem of elevation of the T wave of an electrocardiogram (ECG) signal in the magnetic resonance imaging (MRI). In the MRI, due to the strong static magnetic field the interaction of the blood flow with this strong magnetic field induces a voltage in the body. This voltage appears as a superimposition at the locus of the T wave of the ECG signal. This looses important information required by the doctors to interpret the ST segment of the ECG and detect diseases such as myocardial infarction. This dissertation aims at finding a solution to the problem of elevation of the T wave of an ECG signal in the MRI. The first step is to simulate the entire situation and obtain the magnetic field dependent T wave elevation. This is achieved by building a model of the aorta and simulating the blood flow in it. This model is then subjected to a static magnetic field and the surface potential on the thorax is measured to observe the T wave elevation. The various parameters on which the T wave elevation is dependent are then analyzed. Different approaches are used to reduce this T wave elevation problem. The direct approach aims at computing the magnitude of T wave elevation using magneto-hydro-dynamic equations. The indirect approach uses digital signal processing tools like the least mean square adaptive filter to remove the T wave elevation and obtain artifact free ECG signal in the MRI. Excellent results are obtained from the simulation model. The model perfectly simulates the ECG signal in the MRI at all the 12 leads of the ECG. These results are compared with ECG signals measured in the MRI. A simulation package is developed in MATLAB based on the simulation model. This package is a graphical user interface allowing the user to change the strength of magnetic field, the radius of the aorta and the orientation of the aorta with respect to the heart and observe the ECG signals with the elevation at the 12 leads of the ECG. Also the artifacts introduced due to the magnetic field can be removed by the least mean square adaptive filter. The filter adapts the ECG signal in the MRI to the ECG signal of the patient outside the MRI. Before the adaptation, the heart rate of the ECG outside the MRI is matched to the ECG in the MRI by interpolation or decimation. The adaptive filter works excellently to remove the T wave artifacts. When the cardiac output of the patient changes, the simulation model is used along with the adaptive filter to obtain the artifact free ECG signal.
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Date Issued: 2007
Identifier: CFE0001857, ucf:47389
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0001857

Title: ADAPTIVE SELF-REGULATION AND ORGANIZATIONAL POLITICS: INVESTIGATING THE EFFECTS IN THE ACCOUNTING PROFESSION.
Creator: Howell, Sharon, Peggy D. Dwyer, Robin W. Roberts, University of Central Florida
Abstract / Description: The purpose of this dissertation is to investigate whether or not perceptions of organizational politics mediate the relationships between accountants' personality and interpersonal traits and their perceptions of a superior's leadership ability and performance. An accountant who has a higher degree of confidence in his or her superior's abilities is more likely to be committed to a given project, resulting in a better project outcome. This benefits the client and ultimately society as a...
Show moreThe purpose of this dissertation is to investigate whether or not perceptions of organizational politics mediate the relationships between accountants' personality and interpersonal traits and their perceptions of a superior's leadership ability and performance. An accountant who has a higher degree of confidence in his or her superior's abilities is more likely to be committed to a given project, resulting in a better project outcome. This benefits the client and ultimately society as a whole. This study contributes to the accounting and psychology literatures because extant research views perceptions of leadership ability and performance from the perspective of the individual agent, with little or no recognition that social action and interaction shape and mold both the individual agent's actions and perceptions of those actions. Perceived leadership and perceived performance are important in accounting for several reasons. First, individuals act in part in relation and response to the expectations of others. Thus, the perception of effective leadership and performance is gained by meeting the expectations of others. Secondly, accountants with reputations for effectiveness have been found to be more successful in their careers. Finally, the reputation for effectiveness in performance and leadership ability has been shown to increase those abilities. This study draws on the adaptive self-regulation framework as well as other theoretical models of perceived performance. The study results indicate that certain manageable personality, interpersonal, and contextual variables affect how accountants view the level of organizational politics within the workplace. In turn, the accountant's view of the organizations' politics is shown to very strongly affect how the accountant perceives his or her superiors' performance and leadership ability.
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Date Issued: 2005
Identifier: CFE0000507, ucf:46458
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0000507

Title: Leveraging Help Requests in POMDP Intelligent Tutors.
Creator: Folsom-Kovarik, Jeremiah, Sukthankar, Gita, Schatz, Sarah, Gonzalez, Avelino, Shumaker, Randall, Schatz, Sarah, University of Central Florida
Abstract / Description: Intelligent tutoring systems (ITSs) are computer programs that model individual learners and adapt instruction to help each learner differently. One way ITSs differ from human tutors is that few ITSs give learners a way to ask questions. When learners can ask for help, their questions have the potential to improve learning directly and also act as a new source of model data to help the ITS personalize instruction. Inquiry modeling gives ITSs the ability to answer learner questions and refine...
Show moreIntelligent tutoring systems (ITSs) are computer programs that model individual learners and adapt instruction to help each learner differently. One way ITSs differ from human tutors is that few ITSs give learners a way to ask questions. When learners can ask for help, their questions have the potential to improve learning directly and also act as a new source of model data to help the ITS personalize instruction. Inquiry modeling gives ITSs the ability to answer learner questions and refine their learner models with an inexpensive new input channel.In order to support inquiry modeling, an advanced planning formalism is applied to ITS learner modeling. Partially observable Markov decision processes (POMDPs) differ from more widely used ITS architectures because they can plan complex action sequences in uncertain situations with machine learning. Tractability issues have previously precluded POMDP use in ITS models. This dissertation introduces two improvements, priority queues and observation chains, to make POMDPs scale well and encompass the large problem sizes that real-world ITSs must confront. A new ITS was created to support trainees practicing a military task in a virtual environment. The development of the Inquiry Modeling POMDP Adaptive Trainer (IMP) began with multiple formative studies on human and simulated learners that explored inquiry modeling and POMDPs in intelligent tutoring. The studies suggest the new POMDP representations will be effective in ITS domains having certain common characteristics.Finally, a summative study evaluated IMP's ability to train volunteers in specific practice scenarios. IMP users achieved post-training scores averaging up to 4.5 times higher than users who practiced without support and up to twice as high as trainees who used an ablated version of IMP with no inquiry modeling. IMP's implementation and evaluation helped explore questions about how inquiry modeling and POMDP ITSs work, while empirically demonstrating their efficacy.
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Date Issued: 2012
Identifier: CFE0004506, ucf:49262
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0004506

Title: FACTORS INFLUENCING EFFECTIVENESS OF INTERORGANIZATIONAL NETWORKS AMONG CRISIS MANAGEMENT ORGANIZATIONS: A COMPARATIVE PERSPECTIVE.
Creator: Sahin, Bahadir, Wan, Thomas, University of Central Florida
Abstract / Description: Crisis management has become one of the most important public policy areas in recent decades with greater numbers of manmade and natural disasters. History showed that well-implemented crisis management policies can save lives and reduce costs in a disaster. Literature offered various suggestions for more effective crisis management policies with different techniques utilizing different theoretical frameworks. Informal relationships among crisis management employees were suggested to have a...
Show moreCrisis management has become one of the most important public policy areas in recent decades with greater numbers of manmade and natural disasters. History showed that well-implemented crisis management policies can save lives and reduce costs in a disaster. Literature offered various suggestions for more effective crisis management policies with different techniques utilizing different theoretical frameworks. Informal relationships among crisis management employees were suggested to have a positive impact on crisis management effectiveness. Yet it was not demonstrated with advanced statistical tools if there is such a relationship. This study considers crisis management effort as a network effort and employs complex adaptive systems theory in order to understand factors influencing effectiveness of crisis management networks. Complex adaptive systems theory presents that more open communication lines in a given network or an organization would increase effectiveness of it since inner processes of the network or organization would obtain more information from the chaotic environment. Quality of informal relationships (casual relationships, social capital etc.) was hypothesized as a tool to open more communication lines within an agency which would eventually increase effectiveness of the network constructed by the organization. Based on the theoretical framework, adaptiveness capacity of the agencies was also tested in order to understand a correlation between adaptation and effectiveness of crisis management networks. Multiple case-study method was employed to identify incidents that can represent crisis management in full perspective. Terrorist attacks carried upon by the same terrorist network hit New York in 2001, Istanbul in 2003, Madrid in 2004, and London in 2005 were selected. First response phase of crisis management and policy changes after and before the attacks were discussed. Public administration processes and other social-economical conditions of countries were examined in terms of crisis management structure. Names of key agencies of selected crisis management systems were suggested by a social network analysis tool-UCINET. Six key agencies per incident were targeted for surveys. Surveys included a nine-item-quality of informal relationships, four-item-adaptiveness capability, and ten-item-perceived effectiveness of crisis management networks-scales. Respondents were asked to fill in online surveys where they could refer to their colleagues in the same incidents. 230 respondents were aimed and 246 survey responses were obtained as a result. Surveys formed a structural equation model representing 23 observed factors and 2 latent constructs. Confirmatory factor analysis was utilized to validate hypothesis-driven conceptual models. Quality of informal relationships was found to have a significant positive impact on perceived crisis management network effectiveness (Standardized regression coefficient = .39). Two of the adaptiveness variables, openness to change and intra-organizational training were also positively correlated with the dependent variable of the study (Standardized regression coefficient = .40 and .26 respectively). Turkish and American groups' differences suggested a social-economical difference in societies. Majority of the respondents were some type of managers which made it possible to generalize the results for all phases of crisis management. Discussions suggested improved informal relationships among crisis management employees to provide a better crisis management during an extreme event. Collaborative social events were offered to improve crisis management effectiveness. An agency's openness to change proposed that a crisis management organization should be flexible in rules and structureto gain more efficacy. The other adaptiveness variable, intra-organizational training efforts were proposed to have certain influence on effectiveness of crisis management network. Factors built latent construct of perceived crisis management effectiveness were also found out to be important on crisis management, which of some are ability to carry out generic crisis management functions, mobilize personnel and resources efficiently, process information adequately, blend emergent and established entities, provide appropriate reports for news media etc. Study contributed to the complex adaptive system theory since the fundamentals of the theory were tested with an advanced quantitative method. Non-linear relationships within a system were tested in order to reveal a correlation as the theory suggested, where the results were convincingly positive. Crisis management networks' effectiveness was demonstrated to be validated by a ten-item-scale successfully. Future research might utilize more disaster cases both natural and manmade, search for impact of different communication tools within a system, and look at the relationships among members of crisis management networks instead looking within an organization.
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Date Issued: 2009
Identifier: CFE0002709, ucf:48173
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0002709

Title: TOWARD A THEORY OF PRACTICAL DRIFT IN TEAMS.
Creator: Bisbey, Tiffany, Salas, Eduardo, University of Central Florida
Abstract / Description: Practical drift is defined as the unintentional adaptation of routine behaviors from written procedure. The occurrence of practical drift can result in catastrophic disaster in high-reliability organizations (e.g. the military, emergency medicine, space exploration). Given the lack of empirical research on practical drift, this research sought to develop a better understanding by investigating ways to assess and stop the process in high-reliability organizations. An introductory literature...
Show morePractical drift is defined as the unintentional adaptation of routine behaviors from written procedure. The occurrence of practical drift can result in catastrophic disaster in high-reliability organizations (e.g. the military, emergency medicine, space exploration). Given the lack of empirical research on practical drift, this research sought to develop a better understanding by investigating ways to assess and stop the process in high-reliability organizations. An introductory literature review was conducted to investigate the variables that play a role in the occurrence of practical drift in teams. Research was guided by the input-throughput-output model of team adaptation posed by Burke, Stagl, Salas, Pierce, and Kendall (2006). It demonstrates relationships supported by the results of the literature review and the Burke and colleagues (2006) model denoting potential indicators of practical drift in teams. Research centralized on the core processes and emergent states of the adaptive cycle; namely, shared mental models, team situation awareness, and coordination. The resulting model shows the relationship of procedure—practice coupling demands misfit and maladaptive violations of procedure being mediated by shared mental models, team situation awareness, and coordination. Shared mental models also lead to team situation awareness, and both depict a mutual, positive relationship with coordination. The cycle restarts when an error caused by maladaptive violations of procedure creates a greater misfit between procedural demands and practical demands. This movement toward a theory of practical drift in teams provides a conceptual framework and testable propositions for future research to build from, giving practical avenues to predict and prevent accidents resulting from drift in high-reliability organizations. Suggestions for future research are also discussed, including possible directions to explore. By examining the relationships reflected in the new model, steps can be taken to counteract organizational failures in the process of practical drift in teams.
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Date Issued: 2014
Identifier: CFH0004636, ucf:45300
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFH0004636

Title: Arterial-level real-time safety evaluation in the context of proactive traffic management.
Creator: Yuan, Jinghui, Abdel-Aty, Mohamed, Eluru, Naveen, Hasan, Samiul, Cai, Qing, Wang, Liqiang, University of Central Florida
Abstract / Description: In the context of pro-active traffic management, real-time safety evaluation is one of the most important components. Previous studies on real-time safety analysis mainly focused on freeways, seldom on arterials. With the advancement of sensing technologies and smart city initiative, more and more real-time traffic data sources are available on arterials, which enables us to evaluate the real-time crash risk on arterials. However, there exist substantial differences between arterials and...
Show moreIn the context of pro-active traffic management, real-time safety evaluation is one of the most important components. Previous studies on real-time safety analysis mainly focused on freeways, seldom on arterials. With the advancement of sensing technologies and smart city initiative, more and more real-time traffic data sources are available on arterials, which enables us to evaluate the real-time crash risk on arterials. However, there exist substantial differences between arterials and freeways in terms of traffic flow characteristics, data availability, and even crash mechanism. Therefore, this study aims to deeply evaluate the real-time crash risk on arterials from multiple aspects by integrating all kinds of available data sources. First, Bayesian conditional logistic models (BCL) were developed to examine the relationship between crash occurrence on arterial segments and real-time traffic and signal timing characteristics by incorporating the Bluetooth, adaptive signal control, and weather data, which were extracted from four urban arterials in Central Florida. Second, real-time intersection-approach-level crash risk was investigated by considering the effects of real-time traffic, signal timing, and weather characteristics based on 23 signalized intersections in Orange County. Third, a deep learning algorithm for real-time crash risk prediction at signalized intersections was proposed based on Long Short-Term Memory (LSTM) and Synthetic Minority Over-Sampling Technique (SMOTE). Moreover, in-depth cycle-level real-time crash risk at signalized intersections was explored based on high-resolution event-based data (i.e., Automated Traffic Signal Performance Measures (ATSPM)). All the possible real-time cycle-level factors were considered, including traffic volume, signal timing, headway and occupancy, traffic variation between upstream and downstream detectors, shockwave characteristics, and weather conditions. Above all, comprehensive real-time safety evaluation algorithms were developed for arterials, which would be key components for future real-time safety applications (e.g., real-time crash risk prediction and visualization system) in the context of pro-active traffic management.
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Date Issued: 2019
Identifier: CFE0007743, ucf:52398
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0007743

adaptation (5)	+ -
Adaptive (4)	+ -
Adaptive Control (4)	+ -
simulation (3)	+ -
Adaptive Automation (2)	+ -

Adaptive Training (2)	+ -
ECG (2)	+ -
Fault-tolerance (2)	+ -
Feedback (2)	+ -
LMS (2)	+ -
Performance (2)	+ -
adaptive filter (2)	+ -
adaptive lens (2)	+ -
adaptive threshold (2)	+ -
stress (2)	+ -
team adaptation (2)	+ -
workload (2)	+ -
3D display (1)	+ -
Adaptable Computer Architecture (1)	+ -
Adaptation (1)	+ -
Adapted Integrated Model (1)	+ -
Adaptive Art (1)	+ -
Adaptive Filter (1)	+ -
Adaptive Instruction (1)	+ -
Adaptive Intelligent User Interfaces (1)	+ -
Adaptive Optics (1)	+ -
Adaptive Quantum Processing (1)	+ -
Adaptive Self-Regulation (1)	+ -
Adaptive Sensing (1)	+ -
Adaptive Traffic Control System (1)	+ -

ETD Collection (74)	+ -
Honors Collection (1)	+ -

University of Central Florida (75)	+ -
Haralambous, Michael (6)	+ -
Jentsch, Florian (5)	+ -
Mikhael, Wasfy (5)	+ -
Behal, Aman (4)	+ -

Shumaker, Randall (4)	+ -
Bowers, Clint (3)	+ -
DeMara, Ronald (3)	+ -
Eluru, Naveen (3)	+ -
Reinerman, Lauren (3)	+ -
Sims, Valerie (3)	+ -
Sivo, Stephen (3)	+ -
Wu, Shintson (3)	+ -
Wu, Xinzhang (3)	+ -
Xu, Yunjun (3)	+ -
Abdel-Aty, Mohamed (2)	+ -
Bai, Haiyan (2)	+ -
Batarseh, Issa (2)	+ -
Boloni, Ladislau (2)	+ -
Burke, Shawn (2)	+ -
Fiore, Stephen (2)	+ -
Fyall, Alan (2)	+ -
Geiger, Christopher (2)	+ -
Hancock, Peter (2)	+ -
Hasan, Samiul (2)	+ -
Hoffman, Eric (2)	+ -
Karwowski, Waldemar (2)	+ -
Kauffman, Jeffrey (2)	+ -
Li, Guifang (2)	+ -
Lin, Mingjie (2)	+ -

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