Download or read book Optimization of Urban Traffic Control Strategies by a Network Design Model written by Wu Sun and published by . This book was released on 1999 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The efficiency of congested urban transportation networks can be improved by implementing appropriate traffic control strategies, such as signal control timing, turning movement control; implementation of one-way traffic policies, lane distribution controls etc. In this dissertation, the following strategies are addressed: 1) Intersection left turn addition/deletion, 2) Lane designation, . and 3) Signal optimization. The analogy between the network design problem (NDP) and the optimization of traffic control strategies motivated the formulation of an urban transportation network design problem (UTNDP) to optimize traffic control strategies. An UTNDP is a typical bi-level programming program, where the lower level problem is a User Equilibrium (UE) traffic assignment problem, while the upper level problem is a 0-1 integer programming problem. The upper level of an UTNDP model is used to represent the choices of the transportation authority. The lower level problem captures the travelers' behavior. The objective function of the UTNDP is to minimize the total UE travel time. In this dissertation, a realistic travel time estimation procedure based on the 1997 HCM which takes account the effects of the above factors is proposed. The UTNDP is solved through a hybrid simulated annealing-TABU heuristic search strategy that was developed specifically for this problem. TABU lists are used to avoid cycling, and the Simulated Annealing step is used to select moves such that an annealing equilibrium state is achieved so that a reasonably good solution is guaranteed. The computational experiments are conducted on four test networks to demonstrate the feasibility and effectiveness of the UTNDP search strategy. Sensitivity analyses are also conducted on TABU list length, Markov chain increasing rate and control parameter dropping rate, and the weight coefficients of the HEF, which is composed of the current link v/c ratio, the historical contribution factor, and the random factor.

Download or read book Urban Traffic Networks written by Nathan H. Gartner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problems of urban traffic in the industrially developed countries have been at the top of the priority list for a long time. While making a critical contribution to the economic well being of those countries, transportation systems in general and highway traffic in particular, also have detrimental effects which are evident in excessive congestion, high rates of accidents and severe pollution problems. Scientists from different disciplines have played an important role in the development and refinement of the tools needed for the planning, analysis, and control of urban traffic networks. In the past several years, there were particularly rapid advances in two areas that affect urban traffic: 1. Modeling of traffic flows in urban networks and the prediction of the resulting equilibrium conditions; 2. Technology for communication with the driver and the ability to guide him, by providing him with useful, relevant and updated information, to his desired destination.

Download or read book Urban Traffic Control bus Priority System Seminar written by United States. Federal Highway Administration and published by . This book was released on 1975 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Network Design And Optimization For Smart Cities written by Panos M Pardalos and published by World Scientific. This book was released on 2017-05-03 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference text is a collection of important research findings on the latest developments in network modeling for optimization of smart cities. Such models can be used from outlining the fundamental concepts of urban development to the description and optimization of physical networks, such as power, water or telecommunications. Networks help us understand city economics and various aspects of human interactions within cities with particular applications in quality of life and the flow of people and goods. Finally, the natural environment and even the climate of cities can be modeled and managed as networks.

Download or read book Demand responsive Decentralized Urban Traffic Control written by Nathan H. Gartner and published by . This book was released on 1985 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Interplay of Urban Traffic Route Guidance Network Control and Driver Response written by Inchul Yang and published by . This book was released on 2011 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Much effort has been made in the past on the supply side to relieve road traffic congestion which undermines the mobility in urban networks and brings heavy social costs, but building additional roadway capacity is no longer considered a viable option. A better alternative is the efficient management of existing networks, for which we can envisage new possibilities that emerge in light of the recent increase in the use of private providers' digital map and traffic information systems. These systems have evolved mostly without much public sector influence, but some paradigm shift is needed for thinking about the directions of future developments that will show societal benefits also open up private-sector opportunities. In this context, we develop a multi-agent advanced traffic management and information systems (ATMIS) framework with day-to-day dynamics where private agencies are included as traffic information service providers (ISPs) together with public agencies handling the traffic control and the users (drivers) as the decision-makers. One important paradigm shift is that the emergence of private ISPs makes it possible to obtain path-based data via retrieval of individual trajectory diaries and current position information from their subscribers. The availability of such path-based data can bring about the development of new path-based ATMIS algorithms. Such new algorithms can be capable of taking into account the routing effects of advanced traveler information systems (ATIS). Under the assumption that the traffic management center (TMC) has some (even approximate) knowledge of the ISPs' optimal strategies, it is possible to design optimal route guidance and control strategies (ORGCS) that takes into account the anticipated ISP reactions in terms of route-level flows. In light of these issues, we develop a routing-based real-time cycle-free network-wide signal control scheme (R2CFNet) that uses path-based data. The scheme also allows the avoidance of day-to-day games between ISPs and signal control through the use of weights on the queue delays in the control objective function. The weights are essentially operator parameters designed to incorporate ORGCS and day-to-day behavior. The proposed control scheme, of course, responds to detected traffic (demand) rates on a real-time basis in response to the control delays on network routes. Another theoretical advance in the research is in the development of a modeling scheme that uses a new optimization algorithm for a convergent simulation-based dynamic traffic assignment (DTA) model. This model incorporates a Gradient Projection (GP) algorithm, as opposed to the traditionally-used Method of Successive Averages (MSA), and it displays significantly better convergence characteristics. A consistent day-to-day dynamic framework is also developed, incorporating an elaborate microscopic simulation model to capture traffic network performance, to study network dynamics under multiple private ISPs and the new signal control scheme. The results of parametric simulations have shown that the proposed framework is capable of effectively capturing the effects of the interplay of urban traffic route guidance, network control and user response. It is seen that an appropriate combination of ATIS market penetration rate and the special-purpose signal control settings could divert some portion of travel demand to different routes. This is achieved by constraining the signal settings to conform to certain longer-term strategies. The performance and efficiency of the components of the proposed framework such as the DTA model, the day-to-day dynamics model and the R2CFNet control scheme have been investigated through various numerical experiments that show promising results. Lastly, several future topics of relevance to the framework are discussed.

Download or read book Multi model Simulation based Optimization Applied to Urban Transportation written by Krishna Kumar Selvam and published by . This book was released on 2014 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation agencies often resort to the use of traffic simulation models to evaluate the impacts of changes in network design or network operations. They often have multiple traffic simulation tools that cover the network area where changes are to be made. Nonetheless, these multiple simulators may differ in their modeling assumptions (e.g., macroscopic versus microscopic), in their reliability (e.g., quality of their calibration) as well as in their modeling scale (e.g., city-scale model versus regional-scale model). The choice of which simulation model to rely on, let alone of how to combine their use, is intricate. A larger-scale model may, for instance, capture more accurately the local-global interactions; yet may do so at a greater computational cost. This thesis proposes a methodology that enables the simultaneous use of multiple traffic simulation models. We propose a simulation-based optimization algorithm that embeds information from simulation models with different levels of accuracy and with different levels of computational efficiency. The algorithm combines the use of high-accuracy low-efficiency models with low-accuracy high-efficiency models. This combination leads to an algorithm that can identify points (e.g., network designs, traffic management strategies) with good performance at a reduced computational cost. We evaluate the performance of the algorithm with a traffic signal control problem on a small network, as well a large-scale city network. We show that the proposed algorithm identifies signal plans with excellent performance, i.e., with reduced average trip travel times, while doing so with a reduction in the computational cost.

Download or read book Urban Traffic Control Bus Priority System Seminar written by and published by . This book was released on 1900 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Control Systems Handbook written by and published by . This book was released on 1976 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook, which was developed in recognition of the need for the compilation and dissemination of information on advanced traffic control systems, presents the basic principles for the planning, design, and implementation of such systems for urban streets and freeways. The presentation concept and organization of this handbook is developed from the viewpoint of systems engineering. Traffic control studies are described, and traffic control and surveillance concepts are reviewed. Hardware components are outlined, and computer concepts, and communication concepts are stated. Local and central controllers are described, as well as display, television and driver information systems. Available systems technology and candidate system definition, evaluation and implementation are also covered. The management of traffic control systems is discussed.

Download or read book Optimization Models and Methods for Equilibrium Traffic Assignment written by Alexander Krylatov and published by Springer Nature. This book was released on 2019-11-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is focused on the discussion of the traffic assignment problem, the mathematical and practical meaning of variables, functions and basic principles. This work gives information about new approaches, methods and algorithms based on original methodological technique, developed by authors in their publications for the past several years, as well as corresponding prospective implementations. The book may be of interest to a wide range of readers, such as civil engineering students, traffic engineers, developers of traffic assignment algorithms etc. The obtained results here are to be used in both practice and theory. This book is devoted to the traffic assignment problem, formulated in a form of nonlinear optimization program. The most efficient solution algorithms related to the problem are based on its structural features and practical meaning rather than on standard nonlinear optimization techniques or approaches. The authors have carefully considered the meaning of the traffic assignment problem for efficient algorithms development.

Download or read book Modeling Uncertainty in Large scale Urban Traffic Networks written by Xueyu Gao and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent work has proposed using aggregate relationships between urban traffic variables--i.e., Macroscopic Fundamental Diagrams (MFDs)--to describe aggregate traffic dynamics in urban networks. This approach is particularly useful to unveil and explore the effects of various network-wide control strategies. The majority of modeling work using MFDs hinges upon the existence of well-defined MFDs without consideration of uncertain behaviors. However, both empirical data and theoretical analysis have demonstrated that MFDs are expected to be uncertain due to inherent instabilities that exist in traffic networks. Fortunately, sufficient amounts of adaptive drivers who re-route to avoid congestion have been proven to help eliminate the instability of MFDs. Unfortunately, drivers cannot re-route themselves adaptively all the time as routing choices are controlled by multiple factors, and the presence of adaptive drivers is not something that traffic engineers can control. Since MFDs have shown promise in the design and control of urban networks, it is important to seek another strategy to mitigate or eliminate the instability of MFDs. Furthermore, it is necessary to develop a framework to account for the uncertain phenomena that emerges on the macroscopic, network-wide level to address these unavoidable stochastic behaviors.This first half of this work investigates another strategy to eliminate inherent network instabilities and produce more reliable MFDs that is reliable and controllable from an engineering perspective--the use of adaptive traffic signals. A family of adaptive signal control strategies is examined on two abstractions of an idealized grid network using an interactive simulation and analytical model. The results suggest that adaptive traffic signals should provide a stabilizing influence that provides more well-defined MFDs. Adaptive signal control also both increases average flows and decreases the likelihood of gridlock when the network is moderately congested. The benefits achieved at these moderately congested states increase with the level of signal adaptivity. However, when the network is extremely congested, vehicle movements become more constrained by downstream congestion and queue spillbacks than by traffic signals, and adaptive traffic signals appear to have little to no effect on the network or MFD. When a network is extremely congested, other strategies should be used to mitigate the instability, like adaptively routing drivers. Therefore, without sufficient amounts of adaptive drivers, the instability of MFDs could be somewhat controlled, but it cannot be eliminated completely. This is results in more reliable MFDs until the network enters heavily congested states. The second half of this work uses stochastic differential equations (SDEs) to depict the evolutionary dynamics of urban network while accounting for unavoidable uncertain phenomena. General analytical solutions of SDEs only exist for linear functions. Unfortunately, most MFDs observed from simulation and empirical data follow non-linear functions. Even the most simplified theoretical model is piecewise linear with breakpoints that cannot be readily accommodated by the linear SDE approach. To overcome this limitation, the SDE well-known solutions are used to develop an approximate solution method that relies on the discretization of the continuous state space. This process is memoryless and results in the development of a computationally efficient Markov Chain (MC) framework. The MC model is also supported by a well-developed theory which facilitates the estimation of future states or steady state equilibrium conditions in a network that explicitly accounts for MFD uncertainty. Due to the fact that current formalization of Markov Chains is restricted with a countable state space, some assumptions which redefine the traffic state and stochastic dynamic process need to be set for the MC model application in dynamic traffic analysis. These assumptions could be sabotaged by inappropriate parameter selections, producing excessive errors in analytical solutions. Therefore, a parametric study is performed here to illustrate how to select two key parameters, i.e. bin size and time interval to optimize the MC models and minimize errors.The major advantage of MC models is its wide flexibility, which has been demonstrated by showing how this method could well handle a wide variety of variables. A family of numerical tests are designed to include instability of MFD model, stochastic traffic demand, different city layouts and different forms of MFDs in the scenarios under static metering strategies. The results suggest that analytical solutions derived from MC models could accurately predict the future traffic state at any moment. Furthermore, the theoretical analysis also illustrates that Markov chains could easily model dynamic traffic control based on traffic state and pre-determined time-varying strategies by adjusting the transition matrix. Overall, the developed MC models are promising in the dynamic analysis of complicated urban network control under uncertainty for which simpler algebraic solutions do not exist.

Download or read book Network flow simulation for urban traffic control system written by and published by . This book was released on 1974 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Urban Transportation Networks written by Yosef Sheffi and published by Prentice Hall. This book was released on 1984 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analytical methodology optimal control in urban traffic networks final report written by and published by . This book was released on 1972 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimization and Games for Controllable Markov Chains written by Julio B. Clempner and published by Springer Nature. This book was released on 2023-12-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.

Download or read book Urban Traffic Control Via Adaptive Optimization Techniques and Multi band Modeling written by Edward Shou Kong Chien and published by . This book was released on 1976 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hybrid Optimization in Urban Traffic Networks written by Han-Ngee Tan and published by . This book was released on 1979 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: