460 research outputs found
A feedback linearization approach for coordinated traffic flow management in highway systems
No full textIn this paper, a control solution to reduce congestion in highway traffic systems is presented. The aim is to produce a control strategy characterized by low computational cost, so that real-time implementation can be attained. The adopted model to describe traffic dynamics is the METANET model. A particular spatio-temporal derivative relationship, describing how control signals (ramp metering and variable speed limits) and disturbances effects propagate along the highway system, is highlighted in the paper. This relationship is the basis of a proposition providing the essential tool for relative degree calculation in generic highway systems. Utilizing this proposition, a feedback linearization-based control law is developed. The control design is completed by employing a linear MPC, which allows for complying with the physical constraints. The performance of the proposed method is evaluated by conducting comprehensive simulation studies, also considering a real-world traffic system. The computational costs are analyzed by comparing the developed methodology with a nonlinear MPC-based approach. Simulation evidence confirms that the proposed method can provide satisfactory solutions for coordinating RM and VSL in highway systems. Such solutions are compatible with real-time implementation
Large-scale traffic signal control and multimodal network design
No full textTraffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved in the long term by creating more road space. Instead, network capacity can be increased by maximizing efficiency of traffic operations and road space use. Several methods can be employed for this purpose, including optimization of public transportation systems operations and intelligent, adaptive traffic signal control. This thesis contributes to the existing research in these directions, by developing and evaluating new modeling, optimization and adaptive signal control approaches, aiming at improving mobility in highly-congested, large-scale networks, while considering the dynamic characteristics of congestion propagation. The problem of optimal Dedicated Bus Lanes (DBL) location assignment in large networks with existing bus systems of fixed operational characteristics is addressed in chapter 2. A combinatorial optimization problem is formulated on the basis of an enhanced version of Store-and-Forward paradigm, a dynamic, queue-based macroscopic traffic model, able to properly capture the dynamics of backwards propagation of congestion due to queue spill-backs. Changes in mode choice equilibrium are considered in the evaluation of candidate solutions. An algorithmic scheme based on Local Search, problem-specific heuristics and Large Neighborhood Search (LNS) metaheuristic is developed to address the complex problem. Various destroy and repair operators for LNS are proposed, together with a learning process for assessing the importance of links in terms of receiving DBL, and a network decomposition strategy for accelerating the solution process for very large networks. A two-layer hierarchical traffic-responsive signal control framework is proposed in chapter 3, combining aggregated multi-region perimeter control (PC) with distributed Max Pressure (MP) control in isolated intersections. Partial deployment of MP in subsets of network nodes is performed and a methodology for identifying critical nodes for MP control based on node traffic characteristics is developed, in the scope of reducing MP implementation cost. Various node layouts of different network penetration rates are evaluated, both in independent MP application and as part of the combined framework. Simulation experiments are performed for a large-scale network of more than 1500 links and 900 intersections for two scenarios resulting in moderately and highly congested states, respectively. Results provide meaningful insights in terms of both independent and combined application of PC and efficient MP control. Under congested conditions, a properly selected subset of critical intersections with MP produces better performance than installing MP everywhere. Adding PC with MP creates even more significant improvements. Finally, detailed analysis of total remaining travel distance in multi-region networks is performed via microscopic simulation, in the scope of evaluating the benefits of utilizing the recently proposed M-Model, which is disconnected from the steady-state approximation of conventional PL model, in aggregated MFD-based network control applications. Results indicate significant potential improvement in terms of accuracy of prediction, especially in cases of highly-dynamic traffic evolution patterns.LUT
Data Set of PLOS Computational Paper PCOMPBIOL-D-18-02181R1
No full textFigures Data of PLOS Computational paper:Modeling of the axon plasma membrane structure and its effects on protein diffusionAuthors: Yihao Zhang, Anastasios V. Tzingounis, and George LykotrafitisCorresponding Author: George Lykotrafitis, Ph.D.University of ConnecticutStorss, CT UNITED STATES</div
The state of modern Greek language as spoken in Victoria
No full textDeposited with permission of the author. © 1986 Dr. Anastasios TamisThis thesis reports a sociolinguistic study, carried out between 1981 and 1984, of the state of the Modern Greek (MG) language in Australia, as spoken by native-speaking first-generation Greek immigrants in Victoria. Particular emphasis is given to the analysis of those characteristics of the linguistic behaviour of these Greek Australians which can be attributed to the contact with English and to other environmental, social and linguistic influence. (For complete abstract open document
Real-time Estimation of Critical Values of the Macroscopic Fundamental Diagram for Maximum Network Throughput
No full textPerimeter flow control or gating has recently been found to be a practical and efficient control scheme in mitigating traffic congestion in urban road networks. This control scheme aims at stabilising the accumulation of vehicles (or a proxy of accumulation, e.g. average occupancy or density) of the macroscopic or network fundamental diagram near critical accumulation to achieve maximum network throughput. Nevertheless, the maximum throughput (capacity flow) in urban road networks may be observed over a range of accumulation-values. In this work, an extension of a previously proposed real-time feedback perimeter flow control strategy is proposed that allows the automatic monitoring of the critical accumulation to help maintain the accumulation near the optimal range of accumulation-values, while network’s throughput is maximised. To this end, we design a Kalman filter-based estimation algorithm that utilises real-time measurements of circu- lating flow and accumulation of vehicles to produce estimates of the currently prevailing critical accumulation. The developed strategy may be valuable whenever the network fundamental dia- gram is not well defined and the critical accumulation cannot accurately be specified or is subject change due to traffic-responsive signal control, traffic composition (e.g. cars versus buses), or non- recurrent day-to-day traffic patterns. We use real experimental data from an urban area with 70 sensors and show that the area exhibits a fundamental diagram with low scatter. We demonstrate that the fundamental diagram is reproduced under different days but its shape and critical occu- pancy depend on the applied semi-real-time signal control and the distribution of congestion in the network. Preliminary results from the application of the estimation algorithm to the experimental data indicate good estimation accuracy and performance, and rapid tracking behaviour
New historical evidence for Anastasios Emm. Papas
No full textNo AbstractThe author’s attention has been drawn to the existence of this historicalevidence in the National Archives of Vienna, by his friend the writer EteoclesGregoriadis together with the numbers of the relevant files. Most of the documents were written in the old German script. Thus the author asked for the help of his friend and former colleague at the University of Thessaloniki and director of the Goethe Institute, Graf Kurt v. Posadowsky, for reading andstudying those documents. Without his help this study would have been impossible. This new evidence concerns the sojourn of Anastasios Papas·—son of Emmanuel Papas, leading figure of the Greek Revolution—in Austria andGermany between the 3rd January and 11th March 1822. There is informationabout his short imprisonment in Trieste, after his arival from Vienna. He then visits various towns in Germany and after negotiations with the Philhellene professor Fr. Thiersch in Munich, he purchases large quantities of ammunition to be despatched to Greece. He finally arrives in Greece early in 1824, and takes part—together with his three brothers who were already fighting—in the struggle for the liberation of the common great fartheland
Real-Time Estimation of Critical Vehicle Accumulation for Maximum Network Throughput
Full text linkPerimeter traffic flow control has recently been found to be a practical and efficient control scheme in mitigating traffic congestion in urban road networks. This control scheme aims at stabilising the accumulation of vehicles of the socalled network fundamental diagram near critical accumulation to achieve maximum network throughput. Nevertheless, the maximum throughput in urban road networks may be observed over a range of accumulation-values. In this work, an adaptive perimeter flow control strategy is proposed that allows the automatic monitoring of the critical accumulation to help maintain the accumulation near the optimal range of accumulation-values, while network's throughput is maximised. To this end, we design a Kalman filter-based estimation scheme that utilises real-time measurements of circulating flow and accumulation of vehicles to produce estimates of the currently prevailing critical accumulation. We use real data from an urban area with 70 sensors and show that the area exhibits a network fundamental diagram with low scatter. We demonstrate that the fundamental diagram is reproduced under different days but its shape and critical occupancy depend on the applied semi-real-time signal control and the distribution of congestion in the network. Results from the application of the estimation algorithm to the experimental data indicate good estimation accuracy and performance, and rapid tracking behaviour
Adaptive physics-informed trajectory reconstruction exploiting driver behavior and car dynamics
No full textAs more and more trajectory data become available, their analysis creates unprecedented opportunities for traffic flow investigations. However, observed physical quantities like speed or acceleration are often measured having unrealistic values. Furthermore, observation devices have different hardware and software specifications leading to heterogeneity in noise levels and limiting the efficiency of trajectory reconstruction methods. Typical strategies prune, smooth, or locally modify vehicle trajectories to infer physically plausible quantities. The filtering strength is usually heuristic. Once the physical quantities reach plausible values, additional improvement is impossible without ground truth data. This paper proposes an adaptive physics-informed trajectory reconstruction framework that iteratively detects the optimal filtering magnitude, minimizing local acceleration variance under stable conditions and ensuring compatibility with feasible vehicle acceleration dynamics and common driver behavior characteristics. Assessment is performed using both synthetic and real-world data. Results show a significant reduction in the speed error and invariability of the framework to different data acquisition devices. The last contribution enables the objective comparison between drivers with different sensing equipment
Nonlinear Model Predictive Control for Coordinated Traffic Flow Management in Highway Systems
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