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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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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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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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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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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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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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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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Chow, Lee-Fang. "Integrating adaptive queue-responsive traffic signal control with dynamic traffic assignment." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0001280.
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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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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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Yulianto, Budi. "Application of fuzzy logic to traffic signal control under mixed traffic conditions." Thesis, University of Newcastle Upon Tyne, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440572.
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Lee, Chungwon. "Combined traffic signal control and traffic assignment : algorithms, implementation and numerical results /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.
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Al-Malik, Mohammed Saleh. "An investigation and development of a combined traffic signal control-traffic assignment model." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/21425.
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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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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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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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Abdelfatah, Akmal Saad. "Time-dependent signal control and system optimal traffic assignment in congested vehicular traffic networks /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.
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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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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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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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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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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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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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Shelby, Steven Gebhart. "Design and evaluation of real-time adaptive traffic signal control algorithms." Diss., The University of Arizona, 2001. http://hdl.handle.net/10150/279933.
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This dissertation investigates methods of real-time adaptive traffic signal control in the context of single isolated intersection and coordinated urban network applications. A primary goal in this dissertation is to identify and address scenarios where real-time optimized controllers do not maintain competitive performance with off-line calibrated, vehicle-actuated control techniques. An extensive literature review is supplemented by subsequent simulation experiments. Several strategies were implemented and evaluated, including OPAC, PRODYN, COP, ALLONS-D, Webster's optimized fixed-time control, and vehicle-actuated control. In particular, evaluation is based on simulation of a single, isolated intersection, where all algorithms are required to adopt the exact, deterministic traffic model used by the simulation. This approach eliminates confounding factors in comparison of algorithms, such as detector placement and disparate traffic models, focusing evaluation on the efficiency of the algorithms and their ultimate performance in terms of vehicle delay. A new algorithm is developed, employing neuro-dynamic programming techniques, also known as reinforcement learning techniques. Several very effective pruning strategies are also constructed. The final product is a very efficient algorithm capable of solving problems up to 2000 times faster than the most efficient previously published algorithm tested, with an 8% decrease in delay. This algorithm is then extended to a generalized, multi-ring control formulation. Simulation results with a standard dual-ring, eight-phase controller demonstrate that efficient, real-time solutions are achieved with a corresponding 12--22% reduction in delay relative to dual-ring, vehicle-actuated control. The real-time optimized, multi-ring controller is finally extended for urban network applications, expanding the objective function to consider downstream performance measures, and adopt standard, vehicle-actuated type coordination constraints. Control on an 8-intersection arterial is evaluated using a CORSIM simulation over a range of traffic conditions. Results are compared with TRANSYT optimized fixed-time control, coordinated vehicle-actuated control, and RHODES. Two regimes of control are revealed, where cyclic coordination constraints provide a significant benefit, and where they prevent more effective control. An adaptive coordination layer is prescribed as a unifying architecture with the potential of obtaining effective control under both regimes. The adaptive control layer specification is explicitly distinguished from existing algorithms, such as SCOOT, SCATS, and VFC-OPAC.
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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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Fkadu, Kebede Aregay. "Evaluation of Adaptive Traffic Signal Control Using Traffic Simulation : A case study in Addis Ababa, Ethiopia." Thesis, KTH, Transportplanering, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-277842.
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One of the most significant urban transport problems is traffic congestion. All major cities both in developed and developing countries are facing the problem due to increasing travel demand caused by increasing urbanization and the attendant economic and population growth. Recognizing the growing burden of traffic congestion, community leaders and transportation planners in Addis Ababa are still actively promoting large-scale road constructions to alleviate traffic congestion. Although Intelligent Transportation Systems(ITS) applications seem to have the potential to improve signalization performance, highly congested intersections in Addis Ababa are still controlled by a timed signal and manual operation. Moreover, these pre-timed signal controls are functioning sub-optimally as they are not being regularly monitored and updated to cope with varying traffic demands. Even though the benefits are well known theoretically, at the time of writing of this thesis, Adaptive Traffic Signal Controllers (ATSC) haven’t been deployed in Ethiopia and no research has been conducted to demonstrate and quantify their effectiveness. This master’s research thesis, therefore, intends to fill the identified gap, by undertaking a microscopic traffic simulation investigation, to evaluate the benefits of adopting a Traffic-responsive Urban Control (TUC) strategy and optimizing traffic signal timings. For the purpose of this study, an oversaturated three-intersection test corridor located in the heart of Addis Ababa city is modeled in VISSIM using real-world traffic data. After validating the calibrated model, the corridor was evaluated with the existing pre-timed, TRANSYT optimized pre-timed plan and TUC strategy. Multiple simulation runs were then made for each scenario alternatives and various measures of effectiveness were considered in the evaluation process. Simulation evaluation has demonstrated an average delay reduction of 24.17% when the existing pre-timed alternative is compared to TRANSYT optimized plan and 35% when compared to the TUC strategy. Overall evaluation results indicate that deploying the TUC strategy and optimizing the aging pre-timed signal plans exhibits a significant flow improvement. It is expected that the result of the thesis work will be an input for future comprehensive policy development processes.
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Venkatakrishnan, C. S. "Analysis and optimization of terminal area air traffic control operations." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13716.
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Gunaratne, Chanaka Sujidhara Rajasinghe. "Traffic-based SIR measurement for power control in W-CDMA." Thesis, University of Surrey, 2002. http://epubs.surrey.ac.uk/844316/.
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Accurate and fast power control is perhaps the most important aspect in W-CDMA, in particular on the uplink. This thesis describes the work earned out to evaluate and enhance the link-level performance of closed-loop power control (CLPC) for the UMTS-FDD uplink. Factors that influence the performance of the CLPC scheme amongst others include the round-trip delay, UE (User Equipment) speed, dynamic range of the handset, the level of diversity available at the receiver and the accuracy of SIR (Signal-to-Interference-plus-Noise Ratio) estimation and channel estimation. The above-mentioned performance improvement is obtained by focussing on the SIR measurement aspect of the power control scheme, and to this end, two new signal quality estimation techniques are proposed and evaluated. Based on the two algorithms, a further comparison is made to investigate the effects of SIR measurement before and after RAKE combining of the signal. Firstly, an improved Eb/N0 estimator is proposed and its performance evaluated both in a stationary (Gaussian) as well as a Rayleigh channel. The improvement in the estimator's performance is obtained by the addition of a smoothing filter to an existing algorithm. The improved algorithm, based on maximum likelihood estimation, is shown to improve the performance of CLPC with an average gain of 0.25 dB (i.e. the average gain for a range of UE speeds) in the power control error (PCE) in a narrowband channel, over the performance without the filter; the algorithm would also offer gains in the wideband channel when the SIR measurement is done before RAKE-combining of the signal. The second algorithm is a traffic-based SIR measurement scheme, so-called because it uses a dedicated traffic channel for the SIR measurement, and hence specific to UMTS-FDD. Again, using the standard deviation of the PCE as the performance metric, it is shown that this scheme achieves gains in the PCE of up to 1.4dB (1.15dB on average) for the 4.75-12.2kbps speech service and up to 2.75dB (2.5dB on average) for 144kbps data, both in UMTS Vehicular environments. The gains achieved are with respect to the performance obtainable with the SIR measurement technique proposed by 3GPP (using dedicated pilot symbols), and they translate to improvements in the CDMA capacity at system-level. Furthermore, the algorithm, which currently assumes perfect blind rate detection, provides a higher improvement in the performance of CLPC for higher data rates (as the figures exemplify), which is an additional advantage since higher data-rate users cause more interference to the network by transmitting higher powers. Results obtained using the PCE performance metric also indicate that the higher path diversity available in W-CDMA (compared to narrowband systems) does not necessarily convert to improved system performance, especially when combining weak taps in the channel, i.e. the performance either stays the same or somewhat degrades. Finally, using the uncoded bit error rate (BER) as the performance metric, two further SIR measurement techniques, both based on variations of the two algorithms discussed earlier, are proposed and compared. The Pre-RAKE scheme, in which the SIR measurement is carried out before RAKE combining of the signal vs. the Post-RAKE scheme where the measurement is carried out after, are compared. The overestimation problem that occurs with the Pre-RAKE scheme is highlighted; hence, it is concluded that Post-RAKE schemes offer superior performance over their Pre-RAKE counterparts. The work has highlighted several issues that need careful consideration as far as SIR measurement is concerned, whether it be for power control or any other radio resource management technique; the overestimation problem which occurs for low SIR values as well as the issue of the number of symbols available for the measurement, can contribute significantly to the SIR measurement error, degrading the performance of CLPC in turn. In addition, it is also useful to have an idea of how much the true SIR can vary within the duration of measurement. Last but not least, the little or no improvement in performance obtained when combining weak taps is attributed to the performance and robustness of the channel estimation algorithms employed; they tend to add more noise than signal power to the RAKE-combined signal when used to combine paths with low Eb/N0 values. The SIR measurement algorithms proposed and discussed in this thesis can be implemented directly in UMTS receivers. On the other hand, the knowledge and information contained herein and the logical approaches considered can lead to the development of new ideas as well as new algorithms.
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Pohlmann, Tobias [Verfasser]. "New Approaches for Online Control of Urban Traffic Signal Systems / Tobias Pohlmann." Aachen : Shaker, 2011. http://d-nb.info/1080764917/34.
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Robles, Danny. "Optimal signal control with multiple objectives in traffic mobility and environmental impacts." Thesis, KTH, Trafik och logistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-101927.
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The increasing number of motor vehicles in urban areas worldwide requires a smart traffic management establishing sustainability on the traffic system. Traffic signal control is a powerful tool in this field since it can control flow patterns in urban areas. Historically, traffic signal optimization was applied to satisfy the goals in mobility of traffic systems e.g. measured by travel delay, stops etc., and very little is known if such a strategy would be optimal for system sustainability in terms of emission and fuel usage. The thesis focus on finding the trade-offs between mobility and impact measures and compares these with approximated real signal strategies. The research objective of the thesis is to create a multi-objective computa- tional framework based on the integration of a microscopic traffic simulation model with a micro scale fuel and emission model. The proposed framework is able to implement mobility and impact objectives in a multi-objective opti- mization process. The microscopic traffic model VISSIM is used to simulate the traffic and two different emission models, CMEM and VT-Micro, are used to estimate the vehicular emissions and fuel consumption. The optimization is based on NSGA ii, a multi-objective genetic algorithm. The proposed framework is demonstrated by conducting two case studies, a single intersection in Wuhan and two coordinated intersections in Stockholm. The investigated objectives used in the optimizations are network delay, av- erage number of stops and average fuel consumption. Moreover, the best solution of each objective is subjected to a emission evaluation. Due to time consuming optimization processes, an upper limit of iterations is set for both cases. All simulations are based on 60 minutes of traffic simulations with additional 15 minutes for warm up. The study shows that the proposed framework is successful in finding signal control strategies producing better values of the investigated objectives com- pared to the real signal approximations. One could also see apparent trade-off between mobility and sustainability depending on the selected objectives.
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Raphael, J. "An exploration of traffic signal control using multi-agent market-based mechanisms." Thesis, University of Liverpool, 2018. http://livrepository.liverpool.ac.uk/3021623/.
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Traffic congestion is a major issue on many urban road networks around the world. The distributed and stochastic nature of traffic has attracted the multi-agent and market mechanism community to the traffic domain which has resulted in many novel approaches to both traffic control and traffic assignment. However, the real-world application of many market-based traffic control systems remains in question because they require technology that has not yet been developed, e.g., autonomous cars. This thesis focuses on the use of market mechanisms for traffic control, more specifically, the application of market principles set forth in market-based multi-robot systems to the traffic domain. Thus, the primary goal of this thesis is the design, implementation and evaluation of a multi-agent market-based traffic control system which does not rely on vehicle agents and other major changes to vehicles or transportation infrastructure. Evaluation of the traffic control system is conducted on two grid-based maps using six different traffic scenarios. The traffic scenarios represent various traffic patterns which include changes in traffic intensity and direction. The traffic scenarios are simulated in SUMO, an open source, macro traffic simulator. Additionally, performance is measured using three metrics: travel time, traffic density, and number of stops. This thesis makes five contributions: (i) demonstration of the efficacy of a novel multi-agent market-based traffic control methodology; (ii) demonstration of the efficacy of a market-based technique for dynamic coalition formation; (iii) analysis of three key traffic control parameters used by SCOOT, a popular urban adaptive traffic control mechanism used in over a dozen countries; (iv ) development of a Python implementation of SCOOT for use on SUMO and (v) a thorough evaluation of the novel market-based mechanisms introduced here, along with SCOOT and a reinforcement-learning traffic controller, over a variety of road traffic conditions. This thesis provides a unique insight into the behaviour of three key traffic control parameters and results show that the novel market-based mechanism has the potential to improve traffic performance in traffic conditions that are less than ideal for SCOOT.
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Urban, Brian L. "Propagation analysis of a 900 MHz spread spectrum centralized traffic signal control system." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5242/.
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The objective of this research is to investigate different propagation models to determine if specified models accurately predict received signal levels for short path 900 MHz spread spectrum radio systems. The City of Denton, Texas provided data and physical facilities used in the course of this study. The literature review indicates that propagation models have not been studied specifically for short path spread spectrum radio systems. This work should provide guidelines and be a useful example for planning and implementing such radio systems. The propagation model involves the following considerations: analysis of intervening terrain, path length, and fixed system gains and losses.
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Dwivedi, Pooja Bimalkant. "Study and Evaluation of IntelliDrive Technology for Traffic Responsive Control Strategies." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/76929.
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IntelliDrive is an initiative developed by United States Department of Transportation (USDOT) that aims to enable safe, interoperable networked wireless communications among vehicles, the infrastructure, and passengers' personal communications devices. IntelliDrive technology has the ability to provide data that would be helpful in enhancement of the existing traffic management applications. IntelliDrive data has attributes that cannot be measured using traditional surveillance technology and which can be used for the development of new traffic management and traveler information applications. The traffic responsive plan selection (TRPS) mode of operation is used in coordinated traffic network to improve the performance of the system. This mode of operation has the ability to implement the best possible timing plan for the existing traffic conditions by switching between timing plans. The data from IntelliDrive technology can be utilized in the traffic responsive mode to improve the system performance by reducing the overall delay in the system. This paper proposes a system that can be used to integrate the data obtained from the IntelliDrive technology to the traffic responsive mode of operation. The proposed method utilizes the number of stops and delay of the vehicles in an intersection as a basis for the implementation of the best timing plan for the prevailing traffic condition. The study shows that using the IntelliDrive based TRPS results in the selection of the traffic plan that minimizes the delay of the system and thus results in better system performance compared to the traditional traffic responsive mechanism.Master of Science
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Lee, Hanbong. "Tradeoff evaluation of scheduling algorithms for terminal-area air traffic control." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45254.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2008.Includes bibliographical references (p. 117-120).
The terminal-area surrounding an airport is an important component of the air transportation system, and efficient and robust terminal-area schedules are essential for successfully meeting the projected increase in air traffic demand. Aircraft arrival schedules are subject to a variety of operational constraints, such as minimum separation requirements for safety, required arrival time-windows, limited deviation from a nominal or FCFS sequence, and precedence constraints on the arrival order. With these constraints, there is a range of desirable objectives associated with multiple stakeholders that could be optimized in these schedules. The schedules should also be robust against the uncertainty around the terminal-area. A dynamic programming algorithm for determining the minimum cost arrival schedule, given the aircraft-dependent delay costs, is presented in this thesis. The proposed approach makes it possible to determine various tradeoffs between multiple objectives in terminal-area operations. The comparison of schedules that maximize throughput to those that minimize average delay shows that the benefit from maximizing throughput could be at the expense of an increase in average delay, and that minimizing average delay is the more advantageous of the two objectives in most cases. A comprehensive analysis of the tradeoffs between throughput and fuel costs, and throughput and operating costs is conducted, accounting for both the cost of delay (as reported by the airlines) and the cost of speeding-up when possible (from models of aircraft performance). It is also demonstrated that the proposed aircraft scheduling algorithm can be applied to the optimization problem for the coupled operations of arrivals and departures on a single runway.
(cont.) Using the same framework, a dynamic programming algorithm for robust scheduling in terminal-area is also developed. This algorithm is designed to minimize the possibility that an air traffic controller has to intervene the initially determined schedule under the uncertainty of the landing time accuracy due to the aircraft equipage. The result from the proposed approach is a tradeoff curve between runway throughput and robustness.
by Hanbong Lee.
S.M.
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Wright, Steven Douglas. "A linear programming approach to path flow estimation in SCOOT controlled road networks." Thesis, University of Newcastle Upon Tyne, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337371.
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Zhang, Yunlong. "Optimal traffic control for a freeway corridor under incident conditions." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-06062008-145027/.
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Calle, Laguna Alvaro Jesus. "Isolated Traffic Signal Optimization Considering Delay, Energy, and Environmental Impacts." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/74238.
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Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This thesis includes two studies that develop new formulations to compute the optimum cycle length of isolated intersections, considering measures of effectiveness such as vehicle delay, fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model against simulated data. The microscopic simulation software, INTEGRATION, was used to simulate two-phase and four-phase isolated intersections over a range of cycle lengths, traffic demand levels, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) were derived from the simulation software. The cycle lengths that minimized the various measures of effectiveness were then used to develop the proposed formulations. The first research effort entailed recalibrating the Webster model to the simulated data to develop a new delay, fuel consumption, and emissions formulation. However, an additional intercept was incorporated to the new formulations to enhance the Webster model. The second research effort entailed updating the proposed model against four study intersections. To account for the stochastic and random nature of traffic, the simulations were then run with twenty random seeds per scenario. Both efforts noted its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths optimized for vehicle delay only. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle demands.Master of Science
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Abdelaziz, Sherif Lotfy Abdel Motaleb. "Study and Evaluation of Traffic Responsive Control on a Large Arterial Network." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/34298.
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Traffic responsive mode of operation with its two mechanisms, threshold-based and pattern matching, is considered one of the effective and efficient signal control modes. This operation mode is underutilized due to its cumbersome configuration procedure. The research presented in this thesis aims to give some guidelines regarding traffic responsive and issues that might improve the system performance.
Four different issues related to traffic responsive are considered: The first issue is the generation of different traffic scenarios that drive the design of the system. This point is not limited to traffic responsive only but it is more general for different traffic engineering applications that need different traffic scenarios. The second issue is presenting an approach to implement traffic responsive control mode of operation in a large arterial network in Northern Virginia. Pattern matching mechanism is used for this application. Compared to time-of-day control mode, traffic responsive control saves up to 26.94% of the average delay and 21.13% of average number of stops for Reston Parkway network.
The third issue is an attempt to improve the current threshold mechanism by relaxing the threshold constraints and using variable thresholds for different levels of plan selection parameters. The last issue is a study for the pedestrian effect on the performance of networks operating by traffic responsive control. The effects of pedestrian calls and pedestrian phases on traffic responsive control are compared and the results shows that pedestrian calls are better for low pedestrian volumes while pedestrian phases are better for high pedestrian volumes.Master of Science
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Han, Rubi. "Incorporating Socio-Economic Factors in Traffic Management and Control." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56685.
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Traffic Congestion is a critical problem in large urban areas. In this thesis, six different control strategies aiming to alleviate congestion are performed through TRANSIMS simulation in the city of Alexandria. Main objective of this thesis is to study and explore the impacts of these control strategy in terms of system performance. Macroscopic Fundamental Diagrams has been used during research to present traffic movement and evaluate traffic performance. This thesis also look at the outcome of each strategy at different household income group in the city. The attention are drawn to the importance of taking socio-economic impact in traffic management decisions. Some of the control strategies presented in this thesis have different impacts on different income groups in the city, while other control strategies have similar impacts (negative, or inconclusive) on different groups in Alexandria city. The thesis gives the conclusions on the impact of selecting different signal control strategies.Master of Science
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Nassir, Neema. "Optimal Integrated Dynamic Traffic Assignment and Signal Control for Evacuation of Large Traffic Networks with Varying Threat Levels." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/297042.
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This research contributes to the state of the art and state of the practice in solving a very important and computationally challenging problem in the areas of urban transportation systems, operations research, disaster management, and public policy. Being a very active topic of research during the past few decades, the problem of developing an efficient and practical strategy for evacuation of real-sized urban traffic networks in case of disasters from different causes, quickly enough to be employed in immediate disaster management scenarios, has been identified as one of the most challenging and yet vital problems by many researchers. More specifically, this research develops fast methods to find the optimal integrated strategy for traffic routing and traffic signal control to evacuate real-sized urban networks in the most efficient manner. In this research a solution framework is proposed, developed and tested which is capable of solving these problems in very short computational time. An efficient relaxation-based decomposition method is proposed, implemented for two evacuation integrated routing and signal control model formulations, proven to be optimal for both formulations, and verified to reduce the computational complexity of the optimal integrated routing and signal control problem. The efficiency of the proposed decomposition method is gained by reducing the integrated optimal routing and signal control problem into a relaxed optimal routing problem. This has been achieved through an insight into intersection flows in the optimal routing solution: in at least one of the optimal solutions of the routing problem, each street during each time interval only carries vehicles in at most one direction. This property, being essential to the proposed decomposition method, is called "unidirectionality" in this dissertation. The conditions under which this property exists in the optimal evacuation routing solution are identified, and the existence of unidirectionality is proven for: (1) the common Single-Destination System-Optimal Dynamic Traffic Assignment (SD-SODTA) problem, with the objective to minimize the total time spent in the threat area; and, (2) for the single-destination evacuation problem with varying threat levels, with traffic models that have no spatial queue propagation. The proposed decomposition method has been implemented in compliance with two widely-accepted traffic flow models, the Cell Transmission Model (CTM) and the Point Queue (PQ) model. In each case, the decomposition method finds the optimal solution for the integrated routing and signal control problem. Both traffic models have been coded and applied to a realistic real-size evacuation scenario with promising results. One important feature that is explored is the incorporation of evacuation safety aspects in the optimization model. An index of the threat level is associated with each link that reflects the adverse effects of traveling in a given threat zone on the safety and health of evacuees during the process of evacuation. The optimization problem is then formulated to minimize the total exposure of evacuees to the threat. A hypothetical large-scale chlorine gas spill in a high populated urban area (downtown Tucson, Arizona) has been modeled for testing the evacuation models where the network has varying threat levels. In addition to the proposed decomposition method, an efficient network-flow solution algorithm is also proposed to find the optimal routing of traffic in networks with several threat zones, where the threat levels may be non-uniform across different zones. The proposed method can be categorized in the class of "negative cycle canceling" algorithms for solving minimum cost flow problems. The unique feature in the proposed algorithm is introducing a multi-source shortest path calculation which enables the efficient detection and cancellation of negative cycles. The proposed method is proven to find the optimal solution, and it is also applied to and verified for a mid-size test network scenario.
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Feng, Yiheng. "Intelligent Traffic Control in a Connected Vehicle Environment." Diss., The University of Arizona, 2015. http://hdl.handle.net/10150/578411.
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Signal control systems have experienced tremendous development both in hardware and in control strategies in the past 50 years since the advent of the first electronic traffic signal control device. The state-of-art real-time signal control strategies rely heavily on infrastructure-based sensors, including in-pavement or video based loop detectors for data collection. With the emergence of connected vehicle technology, mobility applications utilizing vehicle to infrastructure (V2I) communications enable the intersection to acquire a much more complete picture of the nearby vehicle states. Based on this new source of data, traffic controllers should be able to make "smarter" decisions. This dissertation investigates the traffic signal control strategies in a connected vehicle environment considering mobility as well as safety. A system architecture for connected vehicle based signal control applications under both a simulation environment and in the real world has been developed. The proposed architecture can be applied to applications such as adaptive signal control, signal priority including transit signal priority (TSP), freight signal priority (FSP), emergency vehicle preemption, and integration of adaptive signal control and signal priority. Within the framework, the trajectory awareness of connected vehicles component processes and stores the connected vehicle data from Basic Safety Message (BSM). A lane level intersection map that represents the geometric structure was developed. Combined with the map and vehicle information from BSMs, the connected vehicles can be located on the map. Some important questions specific to connected vehicle are addressed in this component. A geo-fencing area makes sure the roadside equipment (RSE) receives the BSM from only vehicles on the roadway and within the Dedicated Short-range Communications (DSRC) range. A mechanism to maintain anonymity of vehicle trajectories to ensure privacy is also developed. Vehicle data from the trajectory awareness of connected vehicles component can be used as the input to a real-time phase allocation algorithm that considers the mobility aspect of the intersection operations. The phase allocation algorithm applies a two-level optimization scheme based on the dual ring controller in which phase sequence and duration are optimized simultaneously. Two objective functions are considered: minimization of total vehicle delay and minimization of queue length. Due to the low penetration rate of the connected vehicles, an algorithm that estimates the states of unequipped vehicles based on connected vehicle data is developed to construct a complete arrival table for the phase allocation algorithm. A real-world intersection is modeled in VISSIM to validate the algorithms. Dangerous driving behaviors may occur if a vehicle is trapped in the dilemma zone which represents one safety aspect of signalized intersection operation. An analytical model for estimating the number of vehicles in dilemma zone (NVDZ) is developed on the basis of signal timing, arterial geometry, traffic demand, and driving characteristics. The analytical model of NVDZ calculation is integrated into the signal optimization to perform dilemma zone protection. Delay and NVDZ are formulated as a multi-objective optimization problem addressing efficiency and safety together. Examples show that delay and NVDZ are competing objectives and cannot be optimized simultaneously. An economic model is applied to find the minimum combined cost of the two objectives using a monetized objective function. In the connected vehicle environment, the NVDZ can be calculated from connected vehicle data and dilemma zone protection is integrated into the phase allocation algorithm. Due to the complex nature of traffic control systems, it is desirable to utilize traffic simulation in order to test and evaluate the effectiveness and safety of new models before implementing them in the field. Therefore, developing such a simulation platform is very important. This dissertation proposes a simulation environment that can be applied to different connected vehicle related signal control applications in VISSIM. Both hardware-in-the-loop (HIL) and software-in-the-loop (SIL) simulation are used. The simulation environment tries to mimic the real world complexity and follows the Society of Automotive Engineers (SAE) J2735 standard DSRC messaging so that models and algorithms tested in the simulation can be directly applied in the field with minimal modification. Comprehensive testing and evaluation of the proposed models are conducted in two simulation networks and one field intersection. Traffic signal priority is an operational strategy to apply special signal timings to reduce the delay of certain types of vehicles. The common way of serving signal priority is based on the "first come first serve" rule which may not be optimal in terms of total priority delay. A priority system that can serve multiple requests with different priority levels should perform better than the current method. Traditionally, coordination is treated in a different framework from signal priority. However, the objectives of coordination and signal priority are similar. In this dissertation, adaptive signal control, signal priority and coordination are integrated into a unified framework. The signal priority algorithm generates a feasible set of optimal signal schedules that minimize the priority delay. The phase allocation algorithm considers the set as additional constraints and tries to minimize the total regular vehicle delay within the set. Different test scenarios including coordination request, priority vehicle request and combination of coordination and priority requests are developed and tested.
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Sarasua, Wayne Alexander. "SIG-GIS : a GIS based traffic signal coordination and information management system." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/19085.
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Ho, Tin Kin. "Optimal control of traffic flow at a conflict area in railway network." Thesis, University of Birmingham, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.633131.
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A railway network may contain various kinds of track configurations. Some sections of tracks can be approached by traffic from two or more directions and there will be dispute as to the assignments of right of way. A traffic conflict occurs when two or more trains are approaching the same section of track, which is termed a conflict area, and they need to alter their progress to avoid collision. If the timetable is fully observed, there should not be any conflicts. However, when a train has been delayed for some reason, it may approach a conflict area so late that the progress of other train(s) near the conflict area is affected. Delays will then be inflicted on the trains involved as a result of conflict. Current practices to assign the right of way at conflict areas usually achieve an orderly and safe passage of the trains, but do not attempt to reduce the delays imposed on the trains. As the demands on the quality of railway services are always rising, any causes of delays should be avoided or at least the delays minimised. This thesis describes the development of a delay-optimised traffic controller which resolves the conflicts in a railway network by producing a policy of right-of-way assignments with minimum total weighted delay imposed on the trains. Dynamic programming is employed to conduct the optimisation process. In order to evaluate the costs during optimisation, an event-based traffic flow model is used to simulate the consequences of certain assignments of right-of-way. Various tests have been carried out to assess the performance of the controller under different traffic conditions. It has been shown that the policies produced by the controller inflict about 10 % less total weighted delays on the trains when compared with a commonly used practice, first come-first served. Hence, while the controller can produce policies with minimal delays imposed on the trains, first come-first served is in fact a reasonable means to deal with a single converging junction. Furthermore, the controller is capable of producing the optimal policies for most conflicts within 2-3 seconds so that it can be used in real-time applications.
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Han, Yunong. "Load-aware traffic control in software-defined enterprise Wireless Local Area Networks." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/22379/.
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With the growing popularity of Bring Your Own Device (BYOD), modern enterprise Wireless Local Area Networks (WLANs) deployments always consist of multiple Access Points (APs) to meet the fast-increasing demand for wireless access. In order to avoid network congestion which leads to issues such as suboptimal Quality of Service (QoS) and degraded user Quality of Experience (QoE), intelligent network traffic control is needed. Software Defined Networking (SDN) is an emerging architecture and intensively discussed as one of the most promising technologies to simplify network management and service development. In the SDN architecture, network management is directly programmable because it is decoupled from forwarding layer. Leveraging SDN to the existing enterprise WLANs framework, network services can be flexibly implemented to support intelligent network traffic control. This thesis studies the architecture of software-defined enterprise WLANs and how to improve network traffic control from a client-side and an AP-side perspective. By extending an existing software-defined enterprise WLANs framework, two adaptive algorithms are proposed to provide client-based mobility management and load balancing. Custom protocol messages and AP load metric are introduced to enable the proposed adaptive algorithms. Moreover, a software-defined enterprise WLAN system is designed and implemented on a testbed. A load-aware automatic channel switching algorithm and a QoS-aware bandwidth control algorithm are proposed to achieve AP-based network traffic control. Experimental results from the testbed show that the designed system and algorithms significantly improve the performance of traffic control in enterprise WLANs in terms of network throughput, packet loss rate, transmission delay and jitter.
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Xie, Yuanchang. "Development and evaluation of an arterial adaptive traffic signal control system using reinforcement learning." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2480.
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Enea, Gabriele. "Simulation-Based Study to Quantify Data-Communication Benefits in Congested Airport Terminal Area." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/31206.
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The scope of this study was to evaluate the impact of the air traffic controller-to-pilot communication standard known as CPDLC or Data-Communication on the future air traffic operations. The impact was evaluated from the double viewpoint of airport delays and air traffic controllersâ workload. RAMS simulation software is used to perform all the runs and from its output data the values of terminal area delays and controllers workload are obtained. The New York Metroplex terminal area was used as a case study. Because of its complexity, where three major airports (i.e. JFK, Newark, and La Guardia) interact and constraint each other, this area was particularly interesting to be studied and the data analyzed gave a valuable insight on the possible future impact of Data-Communication in congested terminal areas. The results of the study, based on some previous man-in-the-loop simulations performed by the FAA in the nineties, showed that significant potential benefits could be obtained with the complete implementation of such technologies in the workload experienced by air traffic controllers. Moreover some small but not negligible benefits were obtained in the total delays accrued by each airport studied. On the other hand, the simulations of the future demand predicted by the FAA demonstrated that without a significant increment in capacity or limitation on the traffic growth intolerable delays would be recorded across the NAS in the future. For the complexity of the simulation model calibration and for the very time-consuming run time not all the scenarios described in the methodology were tested, demonstrating the weakness of RAMS as a ground simulation model.Master of Science
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Pohlmann, Tobias [Verfasser], and Bernhard [Akademischer Betreuer] Friedrich. "New Approaches for Online Control of Urban Traffic Signal Systems / Tobias Pohlmann ; Betreuer: Bernhard Friedrich." Braunschweig : Technische Universität Braunschweig, 2010. http://d-nb.info/1175827282/34.
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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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Mladenovic, Milos Novica. "Modeling and Assessment of State-Of-The-Art Traffic Control Subsystems." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/32193.
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Traffic signals are one of the vital control elements of traffic management and control systems under purview of Departments of Transportation (DOTs) nationwide. They directly affect mobility, safety, and environmental parameters of the transportation networks. Traffic engineers in DOTs often face pressure for extracting additional benefits from existing signal control equipment, influenced by evident increase in demand and changing traffic patterns. However, they often face difficulties, usually from the maturity of the field equipment, lack of understanding of currently available equipment capabilities, and multitude of market available equipment. Besides issues in everyday operation, the need for improved decision-making process appears during selection and implementation of the future signal-control subsystems. This thesis is focusing on the issues related with the need for extracting additional benefits and improved planning of signal-control equipment deployment. Presented are several methodologies and techniques for modeling and assessing traffic signal controllers and supporting communication infrastructure. Techniques presented in this thesis include Petri Net modeling language, Software-in-the-loop simulation, and Geographical Information Systems. Specific capabilities of listed techniques are coordinated for maximizing their benefits in addressing specific issues. The intended positive effects reflect in enhanced comprehension, numerical representation, and analysis of state-of-the-art signal control subsystems in focus. Frameworks, methodologies, and example cases are presented for each of the specific issues in identified traffic signal subsystems, along with recommendations for further research.Master of Science
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David, Daniel Basil. "The Impacts Of Neighbourhood Traffic Management." Thesis, University of Canterbury. Civil and Natural Resources Engineering, 2012. http://hdl.handle.net/10092/8180.
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A major traffic-related problem faced by residents is speeding, which not only causes safety concerns, but also noise issues. Traffic calming is a much favoured traffic management tool employed by road controlling authorities to primarily reduce vehicle speed, hence improve community liveability.
This research aimed to investigate the impacts of traffic calming on speed, safety and traffic noise. The objectives included developing models for the prediction of speed and noise on traffic-calmed streets, and providing guidance for good design practices.
Speeds of individual vehicles as they approached and crossed traffic calming devices were observed in order to identify the behaviour of individual drivers. Results indicated that the speed hump and the raised angled slow point produced the largest speed reductions and least variation in speeds, while mid-block narrowings had no significant speed changes. Inter-device speed was found to be mainly controlled by the separation between devices.
85th percentile speeds at distances from calming devices were 40 – 45 km/h for vertical deflections and 45 – 55 km/h for horizontal deflections. Speeds on approach to speed humps were found to be influenced by the distance available on the approaches, while operating speed at the speed humps were partly influenced by the hump width relative to the road width.
There was evidence of safety benefits of traffic calming overall, despite mid-block crashes increasing post-calming. However, there was no association between the traffic calming and the crashes, which appeared to probably be due to other factors, human factors in particular.
Noise levels produced by light vehicles across speed humps were in fact lower than on a flat section of road, given their respective mean speeds. At a reference speed of 25 km/h, noise levels produced over the 100 mm hump were 3.6 dBA higher than those produced by the 75 mm hump.