Дисертації: "CONTROL SIGNAL"

1

Renfrew, David T. "TRAFFIC SIGNAL CONTROL WITH ANT COLONY OPTIMIZATION." DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/190.

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Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users’ delays. Ant Colony Optimization (ACO) is a metaheuristic based on the behavior of ant colonies searching for food. ACO has successfully been used to solve many NP-hard combinatorial optimization problems and its stochastic and decentralized nature fits well with traffic flow networks. This thesis investigates the application of ACO to minimize user delay at traffic intersections. Computer simulation results show that this new approach outperforms conventional fully actuated control under the condition of high traffic demand.

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2

Zhang, Yihua. "An Evaluation of Transit signal Priority and SCOOT Adaptive Signal control." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33051.

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Cities worldwide are faced with the challenge of improving transit service in urban areas using lower cost means. Transit signal priority is considered to be one of the most effective ways to improve the service of transit vehicles. Transit signal priority has become a very popular topic in transportation in the past 20 to 30 years and it has been implemented in many places around the world. In this thesis, transit signal priority strategies are categorized and an extensive literature review on past research on transit signal priority is conducted. Then a case study on Columbia Pike in Arlington (including 21 signalized intersections) is conducted to assess the impacts of integrating transit signal priority and SCOOT adaptive signal control. At the end of this thesis, an isolated intersection is designed to analyze the sensitivity of major parameters on performance of the network and transit vehicles.

The results of this study indicate that the prioritized vehicles usually benefit from any priority scheme considered. During the peak period, the simulations clearly indicate that these benefits are typically obtained at the expense of the general traffic. While buses experience reductions in delay, stops, fuel consumption, and emissions, the opposite typically occurs for the general traffic. Furthermore, since usually there are significantly more cars than buses, the negative impacts experienced by the general traffic during this period outweigh in most cases the benefits to the transit vehicles, thus yielding overall negative impacts for the various priority schemes considered. For the off-peak period, there are no apparent negative impacts, as there is more spare capacity to accommodate approaching transit vehicles at signalized intersections without significantly disrupting traffic operations.

It is also shown in this study that it is generally difficult to improve the system-wide performance by using transit priority when the signal is already optimized according to generally accepted traffic flow criteria. In this study it is also observed that the system-wide performance decreases rapidly when transit dwell time gets longer.
Master of Science

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3

Al-Mudhaffar, Azhar. "Impacts of Traffic Signal Control Strategies." Doctoral thesis, Stockholm : Division of transports and logistics, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4268.

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4

Niittymäki, Jarkko. "Fuzzy traffic signal control principles and applications /." Espoo, Finland : Helsinki University of Technology, 2002. http://lib.hut.fi/Diss/2002/isbn9512257017/isbn9512257017.pdf.

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Dissertation for the degree of Doctor of Science in Technology--Helsinki University of Technology, Espoo, 2002.
"ISSN 0781-5816." Includes bibliographical references (p. 65-71). Available online as a PDF file via the World Wide Web.

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5

Yung, Sheung Kai. "Signal processing in local sensor validation." Thesis, University of Oxford, 1992. https://ora.ox.ac.uk/objects/uuid:974f513e-a556-4503-bae8-91460f10d3e3.

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Sensor integrity plays a crucial role in automatic control and system monitoring, both in achieving performance and guaranteeing safety. Conventional approaches in sensor failure detection demand precise process models and abundant central computing power. This thesis describes the development and the evaluation of a novel local sensor validation scheme which is independent of the underlying process and is applicable to a wide variety of sensors. A signal-based in-situ sensor validation scheme is proposed. Typical sensor failures are classified according to their signal patterns. To avoid the ambiguity between genuine failures and legitimate measurand variations, a pair of decomposition filters are designed to partition the sensor output; and attention is focused on characteristics beyond the measurement signal bandwidth, which is the only essential process-related variable required. In addition, the application of decimating filters is explored, both as a relief to the analog anti-aliasing filter and as an enhancement in signal discretization. An expression is derived relating the oversampling rate and the attainable improvement in signal resolution. Based on a period of failure-free observation, a whitening filter is identified by modelling the decomposed sensor signal as a stochastic time-series. Significant progress is achieved by a deliberate injection of bandlimited random noise to ensure signal stationarity and to avoid inadmissible leakage of measurement signal into the innovation sequence. The adopted failure detection strategy is primarily innovation-based. Pertinent sensor signal information is extracted recursively by a collection of efficient and robust signal processing algorithms. Its validity is continuously monitored by statistical tests on which a series of precursory failure alarms are formulated. Any aberration detected is then diagnosed under the supervision of a simple rule-based system. The practicality, efficacy and flexibility of the proposed scheme are successfully demonstrated by a bench-top thermocouple experiment and extensive synthetic simulations.

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6

Nunes, Catarina Sofia da Costa. "Advanced signal processing and control in anaesthesia." Thesis, University of Sheffield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251478.

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7

Coeymans-Avaria, Juan Enrique. "Traffic signal systems in a developing country." Thesis, University of Southampton, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305939.

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8

Cadet, Gerard Nivard. "Traffic signal control - a neural network approach." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/1963.

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Artificial Neural Networks (ANNs) have been proven to be an important development in a variety of problem solving areas. Increasing research activity in ANN applications has been accompanied by equally rapid growth in the commercial mainstream use of ANNs. However, there is relatively little research of practical application of ANNs taking place in the field of transportation engineering. The central idea of this thesis is to use Artificial Neural Network Software Autonet in connection with Highway Capacity Software to estimate delay. Currently existing signal control system are briefly discussed and their short coming presented. As a relative new mathematical model, Neural Network offers an attractive alternative and hold considerable potential for use in traffic signal control. It is more adaptive to the change in traffic patterns that take place at isolated intersections. ANN also provides the traffic engineer more flexibility in term of optimizing different measures of effectiveness. This thesis focuses on a better quality signal control system for traffic engineering using Artificial Neural Networks. An analysis in terms of mean, variance and standard deviation of the traffic data is also presented.

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9

Allee, Susan J. "Neuroendocrine control of a dynamic communication signal." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/1093.

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Multiple physiological systems regulate the electric communication signal of the weakly electric gymnotiform fish, Brachyhypopomuspinnicaudatus. Fish were injected with neuroendocrine probes which identified pharmacologically relevant serotonin (5-HT) receptors similar to the mammalian 5-HT1AR and 5-HT2AR. Peptide hormones of the hypothalamic-pituitary-adrenal/interrenal axis also augment the electric waveform. These results indicate that the central serotonergic system interacts with the hypothalamic-pituitaryinterrenal system to regulate communication signals in this species. The same neuroendocrine probes were tested in females before and after introducing androgens to examine the relationship between sex steroid hormones, the serotonergic system, melanocortin peptides, and EOD modulations. Androgens caused an increase in female B. pinnicaudatus responsiveness to other pharmacological challenges, particularly to the melanocortin peptide adrenocorticotropic hormone (ACTH). A forced social challenge paradigm was administered to determine if androgens are responsible for controlling the signal modulations these fish exhibit when they encounter conspecifics. Males and females responded similarly to this social challenge construct, however introducing androgens caused implanted females to produce more exaggerated responses. These results confirm that androgens enhance an individual's capacity to produce an exaggerated response to challenge, however another unidentified factor appears to regulate sex-specific behaviors in this species. These results suggest that the rapid electric waveform modulations B. pinnicaudatus produces in response to conspecifics are situation-specific and controlled by activation of different serotonin receptor types and the subsequent effect on release of pituitary hormones.

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10

Wang, Qichao. "Street Traffic Signal Optimal Control for NEMA Controllers." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/101552.

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This dissertation aims to reduce urban traffic congestion with street traffic signal control. The traffic signal controllers in the U.S. follow the National Electrical Manufacturing Association Standards (NEMA Standards). In a NEMA controller, the control parameters for a coordinated control are cycle, green splits, and offset. This dissertation proposed a virtual phase-link concept and developed a macroscopic model to describe the dynamics of a traffic network. The coordinated optimal splits control problem was solved using model predictive control. The outputs of the solution are the green splits that can be used in NEMA controllers. I compared the proposed method with a state-of-the-practice signal timing software under coordinated-actuated control settings. It was found that the proposed method significantly outperformed the benchmarking method. I compared the proposed NEMA-based virtual phase-link model and a Max Pressure controller model using Vissim. It was found that the virtual phase-link method outperformed two control strategies and performed close, but not as good as, the Max Pressure control strategy. The disadvantage of the virtual phase-link method stemmed from the waste of green time during a fixed control cycle length and the delay which comes from the slowing down of platoon during a road link to allow vehicles to switch lanes. Compared to the Max Pressure control strategy, the virtual phase-link method can be implemented by any traffic controller that follows the NEMA standards. The real-time requirement of the virtual phase-link method is not as strict as the Max Pressure control strategy. I introduced the offsets optimization into the virtual phase-link method. I modeled the traffic arrival pattern based on the optimization results from the virtual phase-link control method. I then derived a phase delay function based on the traffic arrival pattern. The phase delay function is a function of the offset between two consecutive intersections. This phase delay function was then used for offsets optimization along an arterial. I tested the offsets optimization method against a base case using microscopic simulations. It was found that the proposed offset optimization method can significantly reduce vehicle delays.
Doctor of Philosophy

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11

Brown, Derek William. "Systolic algorithm design for control and signal processing." Thesis, Queen's University Belfast, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337644.

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12

Cai, C. "Adaptive traffic signal control using approximate dynamic programming." Thesis, University College London (University of London), 2010. http://discovery.ucl.ac.uk/20164/.

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This thesis presents a study on an adaptive traffic signal controller for real-time operation. An approximate dynamic programming (ADP) algorithm is developed for controlling traffic signals at isolated intersection and in distributed traffic networks. This approach is derived from the premise that classic dynamic programming is computationally difficult to solve, and approximation is the second-best option for establishing sequential decision-making for complex process. The proposed ADP algorithm substantially reduces computational burden by using a linear approximation function to replace the exact value function of dynamic programming solution. Machine-learning techniques are used to improve the approximation progressively. Not knowing the ideal response for the approximation to learn from, we use the paradigm of unsupervised learning, and reinforcement learning in particular. Temporal-difference learning and perturbation learning are investigated as appropriate candidates in the family of unsupervised learning. We find in computer simulation that the proposed method achieves substantial reduction in vehicle delays in comparison with optimised fixed-time plans, and is competitive against other adaptive methods in computational efficiency and effectiveness in managing varying traffic. Our results show that substantial benefits can be gained by increasing the frequency at which the signal plans are revised. The proposed ADP algorithm is in compliance with a range of discrete systems of resolution from 0.5 to 5 seconds per temporal step. This study demonstrates the readiness of the proposed approach for real-time operations at isolated intersections and the potentials for distributed network control.

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13

Davol, Angus P. (Angus Putnam) 1976. "Modeling of traffic signal control and transit signal priority strategies in a microscopic simulation laboratory." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/84303.

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14

Ozmen, Ozlem. "Multi-criteria decision based left-turn signal control guideline." abstract and full text PDF (UNR users only), 2009. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3387816.

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15

Binder, Bernd. "Design principles and control mechanisms of signal transduction networks." Doctoral thesis, [S.l. : s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975655868.

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16

Ridley, Raymond Bryan. "A new small-signal model for current-mode control." access full-text online access from Digital dissertation consortium, 1990. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?9116643.

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17

Alkadry, Abdulkader. "Traffic signal central control, a methodology to determine effectiveness." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36905.pdf.

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18

Laan, Marten Derk van der. "Signal sampling techniques for data acquisition in process control." [S.l. : [Groningen] : s.n.] ; [University Library Groningen] [Host], 1995. http://irs.ub.rug.nl/ppn/138454876.

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19

Ridley, Raymond B. "A new small-signal model for current-mode control." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-07282008-135124/.

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20

Kuhlman, Michael Joseph. "Mixed-Signal Sensing, Estimation and Control for Miniature Robots." Thesis, University of Maryland, College Park, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=1541601.

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Control of miniature mobile robots in unconstrained environments is an ongoing challenge. Miniature robots often exhibit nonlinear dynamics and obstacle avoidance introduces significant complexity in the control problem. In order to allow for coordinated movements, the robots must know their location relative to the other robots; this is challenging for very small robots operating under severe power and size constraints. This drastically reduces on-board digital processing power and suggests the need for a robust, compact distance sensor and a mixed-signal control system using Extended Kalman Filtering and Randomized Receding Horizon Control to support decentralized coordination of autonomous mini-robots. Error analysis of the sensor suggests that system clock timing jitter is the dominant contributor for sensor measurement uncertainty. Techniques for system identification of model parameters and the design of a mixed-signal computer for mobile robot position estimation are presented.

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21

Van, Vuren Thomas. "The interaction between signal control policies and route choice." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293761.

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22

Russell, Bruce David. "Signal processing for on-line control of paste extrusion." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615909.

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23

Rajvanshi, Kshitij. "Multi-Modal Smart Traffic Signal Control Using Connected Vehicles." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin147981730919519.

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24

Shih, Pang-shi. "TRAFFIC SIGNAL CONTROL WITH SWAM INTELLIGENCE ANT COLONY OPTIMIZATION." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1039.

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Traffic signal control with swam intelligence ant colony optimization Pang-shi Shih Ant colony optimization (ACO) is a meta-heuristic based on the indirect communication of a colony of artificial ants mediated by pheromone trails with collaboration and knowledge-sharing mechanism during their food-seeking process. ACO has been successfully applied to solve many NP-hard combinational optimization problems such as travel salesman problem, quadratic problem, just to name a few. In this research, we apply the ACO algorithm to the traffic signal control in order to minimize the user delay at a traffic intersection. Simulation results from our computational experiments indicate that ACO provides better performance during high traffic demand, compared to the conventional Fully Actuated Control (FAC). Keywords: Ant colony optimization (ACO), meta-heuristic, the traffic signal control, user delay

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25

Safar, Felix G. "Signal compression and reconstruction using multiple bases representation." Thesis, This resource online, 1988. http://scholar.lib.vt.edu/theses/available/etd-06112009-063321/.

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26

Obenberger, Jon T. "Methodology to Assess Traffic Signal Transition Strategies Employed to Exit Preemption Control." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26198.

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Enabling vehicles to preempt the normal operation of traffic signals has the potential to improve the safety and efficiency of both the requesting vehicle and all of the other vehicles. Little is known about which strategy is the most effective to exit from preemption control and transition back to the traffic signals normal timing plan. Common among these traffic signal transition strategies is the method of either increasing or decreasing the cycle length of the signal timing plan, as the process followed to return to the coordination point of the effected signal timing plan, to coordinate its operation with adjacent traffic signals. This research evaluates commonly available transition strategies: best way, long, short, and hold strategies. The major contribution of this research is enhancing the methodology to evaluate the impacts of using these alternative transition strategies. Part of this methodology consists of the â software-in-the-loopâ simulation tool which replicates the stochastic characteristics of traffic flow under different traffic volume levels. This tool combines the software from a traffic signal controller (Gardner NextPhase Suitcase Tester, version 1.4B) with a microscopic traffic simulation model (CORSIM, TSIS 5.2 beta version). The research concludes that a statistically significant interaction exists between traffic volume levels and traffic signal transition strategies. This interaction eliminates the ability to determine the isolated effects of either the transition strategies on average travel delay and average travel time, or the effects of changes in traffic volume levels on average travel delay and average travel time. Conclusions, however, could be drawn on the performance of different transition strategies for specific traffic volume levels. As a result, selecting the most effective transition strategy needs to be based on the traffic volume levels and conditions specific to each traffic signal or series of coordinated traffic signals. The research also concludes that for the base traffic volume and a 40% increase in traffic volume, the most effective transition strategies are the best way, long or hold alternatives. The best way was the most effective transition strategy for a 20% increase in traffic volume. The least effective strategy is the short transition strategy for both the base and 40% increase in traffic volume, and the long and short for a 20% increase in traffic volume. Further research needs to be conducted to assess the performance of different transition strategies in returning to coordinated operation under higher levels of traffic volume (e.g., approaching or exceeding congested flow regime), with varying cycle lengths, with different signal timing plans, and when different roadway geometric configurations (e.g., turn lanes, length of turn lanes, number of lanes, spacing between intersections) are present.
Ph. D.

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27

Abbassi, Hadj Ahmed. "Control of an electromagnetic suspension system using TMS 32020 digital signal processor." Thesis, University of Reading, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303466.

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28

Tsiknakis, E. "Novel excitaion waveforms and signal processing for electromagnetic flowmetering." Thesis, University of Bradford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234251.

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29

Mehta, Mehul. "Power control for a mobile satellite system." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245306.

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30

Beak, Byungho, and Byungho Beak. "Systematic Analysis and Integrated Optimization of Traffic Signal Control Systems in a Connected Vehicle Environment." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/626304.

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Traffic signal control systems have been tremendously improved since the first colored traffic signal light was installed in London in December 1868. There are many different types of traffic signal control systems that can be categorized into three major control types: fixed-time, actuated, and adaptive. Choosing a proper traffic signal system is very important since there exists no perfect signal control strategy that fits every traffic network. One example is traffic signal coordination, which is the most widely used traffic signal control system. It is believed that performance measures, such as travel times, vehicle delay, and number of stops, can be enhanced by synchronizing traffic signals over a corridor. However, it is not always true that the coordination will have the same benefits for all the traffic in the network. Most of the research on coordination has focused only on strengthening the major movement along the coordinated routes without considering system-wide impacts on other traffic. Therefore, before implementing a signal control system to a specific traffic network, a thorough investigation should be conducted to see how the control strategy may impact the entire network in terms of the objectives of each type of traffic control system. This dissertation first considers two different kinds of systematic performance analyses for traffic signal control systems. Then, it presents two types of signal control strategies that account for current issues in coordination and priority control systems, respectively. First, quantitative analysis of smooth progression for traffic flow is investigated using connected vehicle technology. Many studies have been conducted to measure the quality of progression, but none has directly considered smooth progression as the significant factor of coordination, despite the fact that the definition of coordination states that the goal is to have smooth traffic flow. None of the existing studies concentrated on measuring a continuous smooth driving pattern for each vehicle in terms of speed. In order to quantify the smoothness, this dissertation conducts an analysis of the speed variation of vehicles traveling along a corridor. A new measure is introduced and evaluated for different kinds of traffic control systems. The measure can be used to evaluate how smoothly vehicles flow along a corridor based on the frequency content of vehicle speed. To better understand the impact of vehicle mode, a multi-modal analysis is conducted using the new measure. Second, a multi-modal system-wide evaluation of traffic signal systems is conducted. This analysis is performed for traffic signal coordination, which is compared with fully actuated control in terms of a systematic assessment. Many optimization models for coordination focus mainly on the objective of the coordinated route and do not account for the impacts on side street movements or other system-wide impacts. In addition, multi-modality is not considered in most optimized coordination plans. Thus, a systematic investigation of traffic signal coordination is conducted to analyze the benefits and impacts on the entire system. The vehicle time spent in the system is measured as the basis of the analysis. The first analysis evaluates the effect of coordination on each route based on a single vehicle mode (regular passenger vehicles). The second analysis reveals that how multi-modality affects the performance of the entire system. Third, in order to address traffic demand fluctuation and traffic pattern changes during coordination periods, this dissertation presents an adaptive optimization algorithm that integrates coordination with adaptive signal control using data from connected vehicles. Through the algorithm, the coordination plan can be updated to accommodate the traffic demand variation and remain optimal over the coordination period. The optimization framework consists of two levels: intersection and corridor. The intersection level handles phase allocation in real time based on connected vehicle trajectory data, while the corridor level deals with the offsets optimization. The corridor level optimization focuses on the performance of the vehicle movement along the coordinated phase, while at the intersection level, all movements are considered to create the optimal signal plan. The two levels of optimizations apply different objective functions and modeling methodologies. The objective function at the intersection level is to minimize individual vehicle delay for both coordinated and non-coordinated phases using dynamic programming (DP). At the corridor level, a mixed integer linear programming (MILP) is formulated to minimize platoon delay for the coordinated phase. Lastly, a peer priority control strategy, which is a methodology that enhances the multi modal intelligent traffic signal system (MMITSS) priority control model, is presented based on peer-to-peer (P2P) and dedicated short range communication (DSRC) in a connected vehicle environment. The peer priority control strategy makes it possible for a signal controller to have a flexible long-term plan for prioritized vehicles. They can benefit from the long-term plan within a secured flexible region and it can prevent the near-term priority actions from having a negative impact on other traffic by providing more flexibility for phase actuation. The strategy can be applied to all different modes of vehicles such as transit, freight, and emergency vehicles. Consideration for far side bus stops is included for transit vehicles. The research that is presented in this dissertation is constructed based on Standard DSRC messages from connected vehicles such as Basic Safety Messages (BSMs), Signal Phasing and Timing Messages (SPaTs), Signal Request Messages (SRMs), and MAP Messages, defined by Society of Automotive Engineers (SAE) (SAE International 2016).

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31

Matthews, S. R. "Harmonic control on power systems." Thesis, Queen's University Belfast, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295421.

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32

Chiou, Suh-Wen. "Optimisation of area traffic control for equilibrium network flows." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299926.

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33

Elkfafi, Magdy. "Intelligent signal processing of evoked potentials for control of anaesthesia." Thesis, University of Sheffield, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364186.

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34

Wong, Sze Chun. "Phase-based optimisation of signal timings for area traffic control." Thesis, University College London (University of London), 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262573.

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35

Staats, Richard C. (Richard Charles). "Integration of predictive routing information with dynamic traffic signal control." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35433.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
Includes bibliographical references (leaves 306-310).
by Richard C. Staats.
Ph.D.

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36

Olshevsky, Alexander. "Efficient information aggregation strategies for distributed control and signal processing." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62427.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 129-136).
This thesis will be concerned with distributed control and coordination of networks consisting of multiple, potentially mobile, agents. This is motivated mainly by the emergence of large scale networks characterized by the lack of centralized access to information and time-varying connectivity. Control and optimization algorithms deployed in such networks should be completely distributed, relying only on local observations and information, and robust against unexpected changes in topology such as link failures. We will describe protocols to solve certain control and signal processing problems in this setting. We will demonstrate that a key challenge for such systems is the problem of computing averages in a decentralized way. Namely, we will show that a number of distributed control and signal processing problems can be solved straightforwardly if solutions to the averaging problem are available. The rest of the thesis will be concerned with algorithms for the averaging problem and its generalizations. We will (i) derive the fastest known averaging algorithms in a variety of settings and subject to a variety of communication and storage constraints (ii) prove a lower bound identifying a fundamental barrier for averaging algorithms (iii) propose a new model for distributed function computation which reflects the constraints facing many large-scale networks, and nearly characterize the general class of functions which can be computed in this model.
by Alexander Olshevsky.
Ph.D.

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37

McCool, Paul. "Surface myoelectric signal analysis and enhancement for improved prosthesis control." Thesis, University of Strathclyde, 2014. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=23209.

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In this thesis, novel signal processing and machine learning techniques are presented in the field of myoelectric control. Specifically, algorithms for activity detection, noise identification and noise reduction are introduced, evaluated and discussed. The ultimate aim has been to develop algorithms to improve the performance of prosthetic control systems that use myoelectric signals. Such systems must be an ability to distinguish between electromyographic signals and background noise. For this, the behaviour of One-Dimensional Local Binary Pattern histograms were used to identify the presence of myoelectric activity in recorded signals that originated from electrode sensors on the surface of the skin. This technique was compared against two other activity detection methods and it was found to give better performance in some circumstances. In particular, a lower False Positive Rate was achieved. Noise is always present in myoelectric signals, and if it can be identified then step s can be taken to quantify and/or mitigate it. Pattern recognition was used to identify a single noise type in pre-recorded myoelectric signals. A set of Radial Basis Function Support Vector Machines were trained and tested on clean myoelectric signals that have been artificially contaminated with five typical noise types. The behaviour of the features and the nature of the confusion are discussed. Identification was shown to be possible, but confusion between noise types grew as the SNR increased. Spectral Enhancement, which is normally used on speech signals, is applied to myoelectric signals in an attempt to mitigate noise. Spectral Enhancement based on Improved Minima Controlled Recursive Averaging (IMCRA) was found to improve the classification accuracy, and by corollary the signal quality, with signals that had white noise artificially added (which can be present in recorded myoelectric signals) and with intrinsically noisy signals. The improvement was higher when fewer channels were used.

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38

Massahi, Aidin. "Multi-resolution Modeling of Dynamic Signal Control on Urban Streets." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3349.

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Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures.

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39

Leung, Eileen. "Quality control in the biogenesis of the signal recognition particle." Thesis, University of Newcastle upon Tyne, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506530.

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40

Moody, Kacen Paul. "FPGA-Accelerated Digital Signal Processing for UAV Traffic Control Radar." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/8941.

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As an extension of previous work done by Luke Newmeyer in his master's thesis \cite{newmeyer2018efficient}, this report presents an improved signal processing chain for efficient, real-time processing of radar data for small-scale UAV traffic control systems. The HDL design described is for a 16-channel, 2-dimensional phased array feed processing chain and includes mean subtraction, windowing, FIR filtering, decimation, spectral estimation via FFT, cross-correlation, and averaging, as well as a significant amount of control and configuration logic. The design runs near the the max allowable memory bus frequency at 300MHz, and using AXI DMA engines can achieve throughput of 38.3 Gb/s (~0.25% below theoretical 38.4 Gb/s), transferring 2MB of correlation data in about 440us. This allows for a pulse repetition frequency of nearly 2kHz, in contrast to 454Hz from the previous design. The design targets the Avnet UltraZed-EV MPSoC board, which boots custom PetaLinux images. API code and post-processing algorithms run in this environment to interface with the FPGA control registers and further process frames of data. Primary configuration options include variable sample rate, window coefficients, FIR filter coefficients, chirp length, pulse repetition interval, decimation factor, number of averaged frames, error monitoring, three DMA sampling points, and DMA ring buffer transfers. The result is a dynamic, high-speed, small-scale design which can process 16 parallel channels of data in real time for 3-dimensional detection of local UAV traffic at a range of 1000m.

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41

Maslekar, Nitin. "Adaptive Traffic Signal Control System Based on Inter-Vehicular Communication." Rouen, 2011. http://www.theses.fr/2011ROUES046.

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Traffic signal control, which is an integral part of Intelligent Transportation System (ITS), plays an important role in regulating vehicular flow at road intersections. With the increase of vehicular traffic, there has been a significant degradation in the functional efficiency of signal systems. Traditional systems are not capable of adjusting the timing pattern in accordance with vehicular demand. This results in excessive delays for road users. Hence it is necessary to develop dynamic systems that can adjust the timing patterns according to traffic demand. Of the various available techniques, Vehicular Adhoc Networks (VANETs) are attracting considerable attention from the research community and the automotive industry to implement dynamic systems. In this context, exchanging data among vehicles is one of the key technological enablers through which the density of vehicles approaching the intersection can be predicted. This requires extensive collaboration between vehicles. Inherent properties and limitations of VANETs, distributing information among the vehicles is a very challenging task. In this thesis, an adaptive traffic signal control system based on car-to-car communication (VANETs) is proposed. To achieve this, a data dissemination technique titled, Clustering in DiRectIon in Vehicular Environment (C-DRIVE) is implemented. In C-DRIVE, the formation of clusters is based on the direction metric. Precisely this metric defines the direction a vehicle will travel after crossing the intersection. To attain stability within the clusters and to have accurate estimation of the density of vehicles, two policies are adapted. In the first policy, a clusterhead switching mechanism is defined. In the second method, termed as Modified C-DRIVE (MC-DRIVE), the clusterhead election policy is modified. In this modification the election policy is based on the stable cluster length. Once the clusters are formed, the elected cluster head will compute the density in its clusters and transmits the information to the traffic signal controller (TSC). With the density information of different lanes approaching the intersection, at the TSC an optimal cycle length is computed using the modified Webster’s model and based on the demand, required green splits are allotted to the various phase. The efficiency of this method is advocated through simulation results which show that the waiting time for vehicles and queue length at intersections are considerably reduced. It is also shown that the proposed solution is collision free at intersections. The proposed system is compared with a classic pre-timed system and an adaptive fuzzy logic system. The simulations also show that the data convergence time and the communication delay between vehicles and traffic signals do not compromise the efficiency of the system.

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42

CHIH-HUA, CHANG, and 張智華. "Adaptive Signal Control Under Intelligent Traffic Signal Contorller." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/90941759984416268872.

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43

Vilarinho, Cristina Alexandra Teixeira. "Intelligent traffic signal control." Doctoral thesis, 2019. https://hdl.handle.net/10216/125551.

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44

Vilarinho, Cristina Alexandra Teixeira. "Intelligent traffic signal control." Tese, 2019. https://hdl.handle.net/10216/125551.

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45

Kohls, Airton G. "Flow-based Adaptive Split Signal Control." 2010. http://trace.tennessee.edu/utk_graddiss/716.

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Over the last 35 years many adaptive traffic signal control systems have been developed presenting alternative strategies to improve traffic signal operations. However, less than 1% of all traffic signals in the United States are controlled by adaptive systems today. The extensive infrastructure necessary including reliable communication and complex calibration leads to a time consuming and costly process. In addition, the most recent National Traffic Signal Report Card indicated an overall grade of D for the nation’s traffic signal control and operations. Recent economic adversity adds to the already difficult task of proactively managing aged signal timing plans. Therefore, in an attempt to escape the status quo, a flow based adaptive split signal control model is presented, having the principal objective of updating the split table based solely on real-time traffic conditions and without disrupting coordination. Considering the available typical traffic signal control infrastructure in cities today, a non centralized system is proposed, directed to the improvement of National Electrical Manufacturers Association (NEMA) based systems that are compliant with the National Transportation Communications for Intelligent Transportation System Protocol (NTCIP) standards. The approach encompasses the User Datagram Protocol (UDP) for system communication allowing an external agent to gather flow information directly from a traffic signal controller detector status and use it to better allocation of phase splits. The flow based adaptive split signal control was not able to consistently yield significant lower average vehicle delay than a full actuated signal controller when evaluated on an intersection operating a coordinated timing plan. However, the research proposes the ability of an external agent to seamless control a traffic signal controller using real-time data, suggesting the encouraging results of this research can be improved upon.

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46

Hofmann, David. "Myoelectric Signal Processing for Prosthesis Control." Doctoral thesis, 2014. http://hdl.handle.net/11858/00-1735-0000-0022-5DA2-9.

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47

Beale, Holly C. "Synaptic Signal Transduction and Transcriptional Control." Thesis, 2010. https://thesis.library.caltech.edu/5823/1/HCB_thesis.pdf.

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Synaptic signal transduction regulates synaptic plasticity, and, on a larger scale, memory itself. The aim of this dissertation is to elucidate some of the mechanisms that control synaptic plasticity in the short term by modulating synaptic morphology and in the long term by controlling gene expression.

One modification associated with synaptic plasticity is the change in the size of the spine, the micron-scale structure on the dendrite which supports the synapse. The size and shape of the spine are controlled by the actin cytoskeleton. I studied how stimulation of synaptic receptors drives changes in activation of proteins that regulate actin polymerization. We identified neuron-specific aspects of a canonical actin regulation pathway and characterized activity-regulated phosphatase activity.

Changes in spine size and other events associated with synaptic plasticity can begin within seconds of synaptic stimuli, but persistent changes require gene expression. For example, Arc, an immediate early gene required for changes in synaptic strength to persist, is the only transcript known to be both transcribed in response to synaptic stimulation and translocated specifically to the site of the stimulation. However, the role of Arc in promoting the plasticity of the synapse is still under investigation. We studied its binding partners and found that an interaction demonstrated in non-neuronal cells was not evident in neurons.

We also studied changes in transcription over longer time periods. In order to identify pathways involving the postsynaptic protein densin, we assessed global changes in transcription with RNA-Seq, which uses ultra-high-throughput, short-read sequencing to measure transcript abundance. Compared to wild-type mice, densin knockout mice exhibit increased abundance of CaMKIIα (a densin binding partner), increased abundance of immediate early gene expression including Arc, and downregulated GABA_AR subunits.

In summary, we investigated posttranslational modifications that take place within seconds of stimulation, binding interactions occurring in steady-state conditions in wild-type mice, and homeostatic adaptations to the chronic absence of a gene. These investigations into synaptic signaling illustrate not only the complexity of synapse-related regulatory networks but also the range of time scales they span.

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48

Zhou, Guangwei. "Optimization of adaptive traffic signal control with transit signal priority at isolated intersections using parallel genetic algorithms." 2006. http://digitalcommons.fiu.edu/dissertations/AAI3217586/.

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Thesis (Ph. D.)--Florida International University, 2006.
Includes bibliographical references (p. 146-152). Also available online via the Florida International University Digital Commons website (http://digitalcommons.fiu.edu/).

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49

Zhang, Hui. "Robust tracking control and signal estimation for networked control systems." Thesis, 2012. http://hdl.handle.net/1828/4033.

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Networked control systems (NCSs) are known as distributed control systems (DCSs) which are based on traditional feedback control systems but closed via a real-time communication channel. In an NCS, the control and feedback signals are exchanged among the system’s components in the form of information packages through the communication channel. The research of NCSs is important from the application perspective due to the significant advantages over the traditional point-to-point control. However, the insertion of the communication links would also bring challenges and constraints such as the network-induced delays, the missing packets, and the inter symbol interference (ISI) into the system design. In order to tackle these issues and move a step further toward industry applications, two important design problems are investigated in the control areas: Tracking Control (Chapter 2–Chapter 5) and Signal Estimation (Chapter 6–Chapter8). With the fact that more than 90% of control loops in industry are controlled by proportional-integral-derivative (PID) controllers, the first work in this thesis aims to propose the design algorithm on PID controllers for NCSs. Such a design will not require the change or update of the existing industrial hardware, and it will enjoy the advantages of the NCSs. The second motivation is that, due to the network-induced constraints, there is no any existing work on tuning the PID gains for a general NCS with a state-space model. In Chapter 2, the PID tracking control for multi-variable NCSs subject to time-varying delays and packet dropouts is exploited. The H_infty control is employed to attenuate the load disturbance and the measurement noise. In Chapter 3, the probabilistic delay model is used to design the delay-scheduling tracking controllers for NCSs. The tracking control strategy consists of two parts: (1) the feedforward control can enhance the transient response, and (2) the feedback control is the digital PID control. In order to compensate for the delays on both communication links, the predictive control scheme is adopted. To make full use of the delay information, it is better to use the Markov chain to model the network-induced delays and the missing packets. A common assumption on the Markov chain model in the literature is that the probability transition matrix is precisely known. However, the assumption may not hold any more when the delay is time-varying in a large set and the statistics information on the delays is inadequate. In Chapter 4, it is assumed that the transition matrices are with partially unknown elements. An observer-based robust energy-to-peak tracking controller is designed for the NCSs. In Chapter 5, the step tracking control problem for the nonlinear NCSs is in- vestigated. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy linear model. The control strategy is a modified PI control. With an augmentation technique, the tracking controller design problem is converted into an H_infty optimization problem. The controller parameters can be obtained by solving non-iterative linear matrix inequality conditions. The state estimation problem for networked systems is explored in Chapter 6. At the sensor node, the phenomenon of multiple intermittent measurements is considered for a harsh sensing environment. It is assumed that the network-induced delay is time- varying within a bounded interval. To deal with the delayed external input and the non-delayed external input, a weighted H_infty performance is defined. A Lyapunov- based method is employed to deal with the estimator design problem. When the delay is not large, the system with delayed state can be transformed into delay-free systems. By using the probabilistic delay model and the augmentation, the H_infty filter design algorithm is proposed for networked systems in Chapter 7. Considering the phenomenon of ISI, the signals transmitted over the communication link would distort, that is, the output of the communication link is not the same with the input to the communication link. If the phenomenon occurs in the NCSs, it is desired to reconstruct the signal. In Chapter 8, a robust equalizer design algorithm is proposed to reconstruct the input signal, being robust against the measurement noise and the parameter variations. Finally, the conclusions of the dissertation are summarized and future research topics are presented.
Graduate

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50

Lee, Shih-Chin, and 李仕勤. "Signal Control at Independent Intersections for LRT." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/09450784158053036426.

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碩士
國立中央大學
土木工程研究所
90
Abstract LRT (Light Rail Transit) is part of Medium Capacity Transport System suit developing city, and many advantageous positions such as low cost, enviroenvironment protective, low noise, is a potential transit system . Except consider the type of station ,the right of way and adaptability on LRT for introducting LRT into Taiwan, on the side, has to choise the applicabl signal control system. The main object of this research was to develop LRT signal control system for independent intersection. Using flexible signal control to lower the delay when LRT crossing the intersection. There are three proposals, including fixed-phase signal, fixed-cycle time signal and non- fixed-cycle time signal.This research using Borland C language to solve thses Mathematical Programming Models. Comparing the effects of these proposals, chosing the most effective one . This research use a case study of applying LRT signal control in Hsin Chu, input data about the real intersection, and analyzing the output to judge which proposal is the optimu, and induce conclusions and propositions to be applied in real intersection.

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