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Lyapunov-Based Control Design for Uncertain MIMO Systems
Title
Lyapunov-Based Control Design for Uncertain MIMO Systems.
Creator
Wang, Zhao, Behal, Aman, Boloni, Ladislau, Haralambous, Michael, University of Central Florida
Abstract / Description
In this dissertation. we document the progress in the control design for a class of MIMO nonlinear uncertain system from five papers. In the first part, we address the problem of adaptive control design for a class of multi-input multi-output (MIMO)nonlinear systems. A Lypaunov based singularity free control law, which compensates for parametric uncertainty in both the drift vector and the input gain matrix, is proposed under the mild assumption that the signs of the leading minors of...
Show moreIn this dissertation. we document the progress in the control design for a class of MIMO nonlinear uncertain system from five papers. In the first part, we address the problem of adaptive control design for a class of multi-input multi-output (MIMO)nonlinear systems. A Lypaunov based singularity free control law, which compensates for parametric uncertainty in both the drift vector and the input gain matrix, is proposed under the mild assumption that the signs of the leading minors of thecontrol input gain matrix are known. Lyapunov analysis shows global uniform ultimate boundedness (GUUB) result for the tracking error under full state feedback (FSFB). Under the restriction that only the output vector is available for measurement, an output feedback (OFB) controller is designed based on a standard high gain observer (HGO) (-) stability under OFB is fostered by the uniformity of the FSFB solution. Simulation results for both FSFB and OFB controllers demonstrate the ef?cacy of the MIMO control design in the classical 2-DOF robot manipulator model.In the second part, an adaptive feedback control is designed for a class of MIMO nonlinear systems containing parametric uncertainty in both the drift vector and the input gain matrix, which is assumed to be full-rank and non-symmetric in general. Based on an SDU decomposition of the gain matrix, a singularity-free adaptive tracking control law is proposed that is shown to be globally asymptotically stable (GAS) under full-state feedback. Output feedback results are facilitated via the use of a high-gain observer (HGO). Under output feedback control, ultimate boundedness of the error signals is obtained (&)#241; the size of the bound is related to the size of the uncertainty in the parameters. An explicit upper bound is also provided on the size of the HGO gain constant.In third part, a class of aeroelastic systems with an unmodeled nonlinearity and external disturbance is considered. By using leading- and trailing-edge control surface actuations, a full-state feedforward/feedback controller is designed to suppress the aeroelastic vibrations of a nonlinear wing section subject to external disturbance. The full-state feedback control yields a uniformly ultimately bounded result for two-axis vibration suppression. With the restriction that only pitching and plunging displacements are measurable while their rates are not, a high-gain observer is used to modify the full-state feedback control design to an output feedback design. Simulation results demonstrate the ef ? cacy of the multi-input multi-output control toward suppressing aeroelastic vibration and limit cycle oscillations occurring in pre and post? utter velocity regimes when the system is subjected to a variety of external disturbance signals. Comparisons are drawn with a previously designed adaptive multi-input multi-output controller.In the fourth part, a continuous robust feedback control is designed for a class of high-order multi-input multi-output (MIMO) nonlinear systems with two degrees of freedom containing unstructured nonlinear uncertainties in the drift vector and parametric uncertainties in the high frequency gain matrix, which is allowed to be non-symmetric in general. Given some mild assumptions on the system model, a singularity-free continuous robust tracking control law is designed that is shown to be semi-globally asymptotically stable under full-state feedback through a Lyapunov stability analysis. The performance of the proposed algorithm have been verified on a two-link robot manipulator model and 2-DOF aeroelastic model.
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Date Issued
2012
Identifier
CFE0004345, ucf:49420
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004345
DESIGN OF AN ADAPTIVE AUTOPILOT FOR AN EXPENDABLE LAUNCH VEHICLE
Title
DESIGN OF AN ADAPTIVE AUTOPILOT FOR AN EXPENDABLE LAUNCH VEHICLE.
Creator
Plaisted, Clinton, Leonessa, Alexander, University of Central Florida
Abstract / Description
This study investigates the use of a Model Reference Adaptive Control (MRAC) direct approach to solve the attitude control problem of an Expendable Launch Vehicle (ELV) during its boost phase of flight. The adaptive autopilot design is based on Lyapunov Stability Theory and provides a useful means for controlling the ELV in the presence of environmental and dynamical uncertainties. Several different basis functions are employed to approximate the nonlinear parametric uncertainties in the...
Show moreThis study investigates the use of a Model Reference Adaptive Control (MRAC) direct approach to solve the attitude control problem of an Expendable Launch Vehicle (ELV) during its boost phase of flight. The adaptive autopilot design is based on Lyapunov Stability Theory and provides a useful means for controlling the ELV in the presence of environmental and dynamical uncertainties. Several different basis functions are employed to approximate the nonlinear parametric uncertainties in the system dynamics. The control system is designed so that the desire dresponse to a reference model would be tracked by the closed-loop system. The reference model is obtained via the feedback linearization technique applied to the nonlinear ELV dynamics. The adaptive control method is then applied to a representative ELV longitudinal motion, specifically the 6th flight of Atlas-Centaur launch vehicle (AC-6) in 1965. The simulation results presented are compared to that of the actual AC-6 post-flight trajectory reconstruction. Recommendations are made for modification and future applications of the method for several other ELV dynamics issues, such as control saturation, engine inertia, flexible body dynamics, and sloshing of liquid fuels.
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Date Issued
2008
Identifier
CFE0002006, ucf:47616
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002006
ADAPTIVE EFFICIENCY OPTIMIZATION FOR DIGITALLY CONTROLLED DC-DC CONVERTERS
Title
ADAPTIVE EFFICIENCY OPTIMIZATION FOR DIGITALLY CONTROLLED DC-DC CONVERTERS.
Creator
AL-HOOR, WISAM, Batarseh, Issa, University of Central Florida
Abstract / Description
The design optimization of DC-DC converters requires the optimum selection of several parameters to achieve improved efficiency and performance. Some of these parameters are load dependent, line dependent, components dependent, and/or temperature dependent. Designing such parameters for a specific load, input and output, components, and temperature may improve single design point efficiency but will not result in maximum efficiency at different conditions, and will not guarantee improvement...
Show moreThe design optimization of DC-DC converters requires the optimum selection of several parameters to achieve improved efficiency and performance. Some of these parameters are load dependent, line dependent, components dependent, and/or temperature dependent. Designing such parameters for a specific load, input and output, components, and temperature may improve single design point efficiency but will not result in maximum efficiency at different conditions, and will not guarantee improvement at that design point because of the components, temperature, and operating point variations. The ability of digital controllers to perform sophisticated algorithms makes it easy to apply adaptive control, where system parameters can be adaptively adjusted in response to system behavior in order to achieve better performance and stability. The use of adaptive control for power electronics is first applied with the Adaptive Frequency Optimization (AFO) method, which presents an auto-tuning adaptive digital controller with maximum efficiency point tracking to optimize DC-DC converter switching frequency. The AFO controller adjusts the DC-DC converter switching frequency while tracking the converter minimum input power point, under variable operating conditions, to find the optimum switching frequency that will result in minimum total loss and thus the maximum efficiency. Implementing variable switching frequencies in digital controllers introduces two main issues, namely, limit cycle oscillation and system instability. Dynamic Limit Cycle Algorithms (DLCA) is a dynamic technique tailored to improve system stability and to reduce limit cycle oscillation under variable switching frequency operation. The convergence speed and stability of AFO algorithm is further improved by presenting the analysis and design of a digital controller with adaptive auto-tuning algorithm that has a variable step size to track and detect the optimum switching frequency for a DC-DC converter. The Variable-Step-Size (VSS) algorithm is theoretically analyzed and developed based on buck DC-DC converter loss model and directed towered improving the convergence speed and accuracy of AFO adaptive loop by adjusting the converter switching frequency with variable step size. Finally, the efficiency of DC-DC converters is a function of several variables. Optimizing single variable alone may not result in maximum or global efficiency point. The issue of adjusting more than one variable at the same time is addressed by the Multivariable Adaptive digital Controller (MVAC). The MVAC is an adaptive method that continuously adjusts the DC-DC converter switching frequency and dead-time at the same time, while tracking the converter minimum input power, to find the maximum global efficiency point under variable conditions. In this research work, all adaptive methods were discussed, theoretically analyzed and its digital control algorithm along with experimental implementations were presented.
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Date Issued
2009
Identifier
CFE0002838, ucf:48072
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002838
Lyapunov-Based Robust and Adaptive Control Design for nonlinear Uncertain Systems
Title
Lyapunov-Based Robust and Adaptive Control Design for nonlinear Uncertain Systems.
Creator
Zhang, Kun, Behal, Aman, Haralambous, Michael, Xu, Yunjun, Boloni, Ladislau, Marzocca, Piergiovanni, University of Central Florida
Abstract / Description
The control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in...
Show moreThe control of systems with uncertain nonlinear dynamics is an important field of control scienceattracting decades of focus. In this dissertation, four different control strategies are presentedusing sliding mode control, adaptive control, dynamic compensation, and neural network for a nonlinear aeroelastic system with bounded uncertainties and external disturbance. In Chapter 2, partial state feedback adaptive control designs are proposed for two different aeroelastic systems operating in unsteady flow. In Chapter 3, a continuous robust control design is proposed for a class of single input and single output system with uncertainties. An aeroelastic system with a trailingedge flap as its control input will be considered as the plant for demonstration of effectiveness of the controller. The controller is proved to be robust by both athematical proof and simulation results. In Chapter 3, a robust output feedback control strategy is discussed for the vibration suppression of an aeroelastic system operating in an unsteady incompressible flowfield. The aeroelastic system is actuated using a combination of leading-edge (LE) and trailing-edge (TE) flaps in the presence of different kinds of gust disturbances. In Chapter 5, a neural-network based model-free controller is designed for an aeroelastic system operating at supersonic speed. The controller is shown to be able to effectively asymptotically stabilize the system via both a Lyapunov-based stability proof and numerical simulation results.
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Date Issued
2015
Identifier
CFE0005748, ucf:50110
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005748
Microgrid Control and Protection: Stability and Security
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
bio-inspired attitude control of micro air vehicles using rich information from airflow sensors
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
STUDY OF DESIGN FOR RELIABILITY OF RF AND ANALOG CIRCUITS
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
Arterial-level real-time safety evaluation in the context of proactive traffic management
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
Applications of Deep Learning Models for Traffic Prediction Problems
Title
Applications of Deep Learning Models for Traffic Prediction Problems.
Creator
Rahman, Rezaur, Hasan, Samiul, Abdel-Aty, Mohamed, Zaki Hussein, Mohamed, University of Central Florida
Abstract / Description
Deep learning coupled with existing sensors based multiresolution traffic data and future connected technologies has immense potential to improve traffic operation and management. But to deal with complex transportation problems, we need efficient modeling frameworks for deep learning models. In this study, we propose two different modeling frameworks using Deep Long Short-Term Memory Neural Network (LSTM NN) model to predict future traffic state (speed and signal queue length). In our first...
Show moreDeep learning coupled with existing sensors based multiresolution traffic data and future connected technologies has immense potential to improve traffic operation and management. But to deal with complex transportation problems, we need efficient modeling frameworks for deep learning models. In this study, we propose two different modeling frameworks using Deep Long Short-Term Memory Neural Network (LSTM NN) model to predict future traffic state (speed and signal queue length). In our first problem, we present a modeling framework using deep LSTM NN model to predict traffic speeds in freeways during regular traffic condition as well as under extreme traffic demand, such as a hurricane evacuation. The approach is tested using real-world traffic data collected during hurricane Irma's evacuation for the interstate 75 (I-75), a major evacuation route in Florida. We perform several experiments for predicting speeds for 5 min, 10 min, and 15 min ahead of current time. The results are compared against other traditional prediction models such as K-Nearest Neighbor, Analytic Neural Network (ANN), Auto-Regressive Integrated Moving Average (ARIMA). We find that LSTM-NN performs better than these parametric and non-parametric models. Apart from the improvement in traffic operation, the proposed method can be integrated with evacuation traffic management systems for a better evacuation operation. In our second problem, we develop a data-driven real-time queue length prediction technique using deep LSTM NN model. We consider a connected corridor where information from vehicle detectors (located at the intersection) will be shared to consecutive intersections. We assume that the queue length of an intersection in the next cycle will depend on the queue length of the target and two upstream intersections in the current cycle. We use InSync Adaptive Traffic Control System (ATCS) data to train a Long Short-Term Memory Neural Network model capturing time-dependent patterns of a queue of a signal. To select the best combination of hyperparameters, we use sequential model-based optimization (SMBO) technique. Our experiment results show that the proposed modeling framework performs very well to predict the queue length. Although we run our experiments predicting the queue length for a single movement, the proposed method can be applied for other movements as well. Queue length prediction is a crucial part of an ATCS to optimize control parameters and this method can improve the existing signal optimization technique for ATCS.
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Date Issued
2019
Identifier
CFE0007516, ucf:52654
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007516
Field Evaluation of Insync Adaptive Traffic Signal Control System in Multiple Environments Using Multiple Approaches
Title
Field Evaluation of Insync Adaptive Traffic Signal Control System in Multiple Environments Using Multiple Approaches.
Creator
Shafik, Md Shafikul Islam, Radwan, Essam, Abou-Senna, Hatem, Eluru, Naveen, University of Central Florida
Abstract / Description
Since the beginning of signalization of intersections, the management of traffic congestion is one of most critical challenges specifically for the city and urbanized area. Almost all the municipal agencies struggle to manage the perplexities associated with traffic congestion or signal control. The Adaptive Traffic Control System (ATCS), an advanced and major technological component of the Intelligent Transportation Systems (ITS) is considered the most dynamic and real-time traffic...
Show moreSince the beginning of signalization of intersections, the management of traffic congestion is one of most critical challenges specifically for the city and urbanized area. Almost all the municipal agencies struggle to manage the perplexities associated with traffic congestion or signal control. The Adaptive Traffic Control System (ATCS), an advanced and major technological component of the Intelligent Transportation Systems (ITS) is considered the most dynamic and real-time traffic management technology and has potential to effectively manage rapidly varying traffic flow relative to the current state-of-the-art traffic management practices.InSync ATCS is deployed in multiple states throughout the US and expanding on a large scale. Although there had been several 'Measure of Effectiveness' studies performed previously, the performance of InSync is not unquestionable especially because the previous studies failed to subject for multiple environments, approaches, and variables. Most studies are accomplished through a single approach using simple/na(&)#239;ve before-after method without any control group/parameter. They also lacked ample statistical analysis, historical, maturation and regression artifacts. An attempt to evaluate the InSync ATCS in varying conditions through multiple approaches was undertaken for the SR-434 and Lake Underhill corridor in Orange County, Florida. A before-after study with an adjacent corridor as control group and volume as a control parameter has been performed where data of multiple variables were collected by three distinct procedures. The average/floating-car method was utilized as a rudimentary data collection process and 'BlueMac' and 'InSync' system database was considered as secondary data sources. Data collected for three times a day for weekdays and weekends before and after the InSync ATCS was deployed.Results show variation in both performance and scale. It proved ineffective in some of the cases, especially for the left turns, total intersection queue/delay and when the intersection volumes approach capacity. The results are verified through appropriate statistical analysis.
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Date Issued
2017
Identifier
CFE0006915, ucf:51687
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006915