Download or read book Dynamic Network wide Traffic Signal Optimization written by M. E. Ting Lu and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Dynamic Network wide Traffic Signal Optimization written by and published by . This book was released on 2015 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Signal Optimization in Large Networks written by Nicholas Vlahos and published by . This book was released on 1987 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Signal Timing Optimization in Large Networks written by Nicholas J. Vlahos and published by . This book was released on 1987 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Network Traffic Signal Control with Short term Origin Destination Demand in a Connected Vehicle Environment Via Mobile Edge Computing written by Can Zhang and published by . This book was released on 2021 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops and analyzes centralized and decentralized network-level traffic signal control system under in a connected vehicle (CV) environment with mobile edge computing (MEC). The goal is to provide a framework of decentralized signal control (DSC) system especially for real-time control and large-scale traffic network. Short-term origin-destination (OD) demand is used as an input given that the technological paradigm assumed is within the CV environment, unlike most previous works that look at network control but in a current technological paradigm. Considering short-term OD demand as inputs, a queue-based dynamic traffic assignment (DTA) model is proposed to predict traffic dynamics in traffic networks with signal control. Although DTA has been an effective tool to describe traffic dynamics for traffic optimization, and many researchers have considered traffic signal control in their models, signal timings have been simplified without considering complex, but realistic, phase sequence and duration restrictions. This work formulates traffic signal timing as a component of the link performance function with three control variables: cycle length, phase split, and offset. In addition, both user-optimal (UO) and system-optimal (SO) DTA problems are solved within a single corridor network. Finally, this thesis provides a simulation-based framework of both centralized and decentralized signal control to solve the network-level traffic signal control optimization problem. For the centralized system, this work solves the issue of optimal control using a three-step naïve method. Because the optimization of large-scale network traffic signals is a Nondeterministic Polynomial Time (NP)-complete problem, the centralized system is further decomposed into a decentralized system where the network is divided into subnetworks. - Each subnetwork has its own agent that optimizes signals within the subnetwork. The proposed control systems are applied to a set of test scenarios constructed using different demand levels in different grid networks. This work also investigates the impact of network decomposition strategy on the signal control system performance. Results show that network decomposition with smaller subnetworks results in less Computational Time (CT), but also increased Average Travel Time (ATT) and Total Travel Delay (TTD). This thesis contributes to the literature by a queue-based DTA model for traffic network with real traffic signal timing plan, a simulation-based framework of DSC system within the MEC-enabled CV environment, and a scalable and extendable decomposition method for a DSC system.

Download or read book Breakdown in Traffic Networks written by Boris S. Kerner and published by Springer. This book was released on 2017-05-26 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a detailed investigation of breakdowns in traffic and transportation networks. It shows empirically that transitions from free flow to so-called synchronized flow, initiated by local disturbances at network bottlenecks, display a nucleation-type behavior: while small disturbances in free flow decay, larger ones grow further and lead to breakdowns at the bottlenecks. Further, it discusses in detail the significance of this nucleation effect for traffic and transportation theories, and the consequences this has for future automatic driving, traffic control, dynamic traffic assignment, and optimization in traffic and transportation networks. Starting from a large volume of field traffic data collected from various sources obtained solely through measurements in real world traffic, the author develops his insights, with an emphasis less on reviewing existing methodologies, models and theories, and more on providing a detailed analysis of empirical traffic data and drawing consequences regarding the minimum requirements for any traffic and transportation theories to be valid. The book - proves the empirical nucleation nature of traffic breakdown in networks - discusses the origin of the failure of classical traffic and transportation theories - shows that the three-phase theory is incommensurable with the classical traffic theories, and - explains why current state-of-the art dynamic traffic assignments tend to provoke heavy traffic congestion, making it a valuable reference resource for a wide audience of scientists and postgraduate students interested in the fundamental understanding of empirical traffic phenomena and related data-driven phenomenology, as well as for practitioners working in the fields of traffic and transportation engineering.

Download or read book Modeling Dynamic Transportation Networks written by Bin Ran and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to summarize our recent progress in dynamic trans portation network modeling. It concentrates on ideal dynamic network models based on actual travel times and their corresponding solution algorithms. In contrast, our first book DynamIc Urban Transportation Network Models - The ory and Implications for Intelligent Vehicle-Hzghway Systems (Springer-Verlag, 1994) focused on instantaneous dynamic network models. Comparing the two books, the major differences can be summarized as follows: 1. This book uses the variational inequality problem as the basic formulation approach and considers the optimal control problem as a subproblem for solution purposes. The former book used optimal control theory as the basic formulation approach, which caused critical problems in some circumstances. 2. This book focuses on ideal dynamic network models based on actual travel times. The former book focused on instantaneous dynamic network models based on currently prevailing travel times. 3. This book formulates a stochastic dynamic route choice model which can utilize any possible route choice distribution function instead of only the logit function. 4. This book reformulates the bilevel problem of combined departure time/ route choice as a one-level variational inequality. 5. Finally, a set of problems is provided for classroom use. In addition, this book offers comprehensive insights into the complexity and challenge of applying these dynamic network models to Intelligent Trans portation Systems (ITS). Nevertheless, the models in this text are not yet fully evaluated and are subject to revision based on future research.

Download or read book Models for Vehicular Traffic on Networks written by Mauro Garavello and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Formulation and Evaluation of a Methodology for Network wide Signal Optimization written by Shiow-Min Lin and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT (cont.): The solution algorithm for the methodology developed in this study is based entirely on dynamic programming, and it is capable of performing network-wide signal optimization. It has been shown more computationally efficient without compromising global optimality. In addition, a heuristic search procedure has been developed. It can significantly reduce the computation and still generate comparable results. Both solution algorithms have been implemented and evaluated in a simulation testing environment, and the simulation results indicate significant improvements compared to a well-timed fixed-time control and an actuated signal. The methodology developed in this study provides a feasible computational framework that can be applied to a dynamic urban traffic control in conjunction with Advanced Traffic Management Systems and Advanced Traveler Information Systems for network-wide signal optimization.

Download or read book The Multi Agent Transport Simulation MATSim written by Andreas Horni and published by Ubiquity Press. This book was released on 2016-08-10 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations. The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.

Download or read book Enhanced Traffic Signal Operation Using Connected Vehicle Data written by Ehsan Bagheri and published by . This book was released on 2017 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: As traffic on urban road network increases, congestion and delays are becoming more severe. At grade intersections form capacity bottlenecks in urban road networks because at these locations, capacity must be shared by competing traffic movements. Traffic signals are the most common method by which the right of way is dynamically allocated to conflicting movements. A range of traffic signal control strategies exist including fixed time control, actuated control, and adaptive traffic signal control (ATSC). ATSC relies on traffic sensors to estimate inputs such as traffic demands, queue lengths, etc. and then dynamically adjusts signal timings with the objective to minimize delays and stops at the intersection. Despite, the advantages of these ATSC systems, one of the barriers limiting greater use of these systems is the large number of traffic sensors required to provide the essential information for their signal timing optimization methodologies. A recently introduced technology called connected vehicles will make vehicles capable of providing detailed information such as their position, speed, acceleration rate, etc. in real-time using a wireless technology. The deployment of connected vehicle technology would provide the opportunity to introduce new traffic control strategies or to enhance the existing one. Some work has been done to-date to develop new ATSC systems on the basis of the data provided by connected vehicles which are mainly designed on the assumption that all vehicles on the network are equipped with the connected vehicle technology. The goals of such systems are to: 1) provide better performance at signalized intersections using enhanced algorithms based on richer data provided by the connected vehicles; and 2) reduce (or eliminate) the need for fixed point detectors/sensors in order to reduce deployment and maintenance costs. However, no work has been done to investigate how connected vehicle data can improve the performance of ATSC systems that are currently deployed and that operate using data from traditional detectors. Moreover, achieving a 100% market penetration of connected vehicles may take more than 30 years (even if the technology is mandated on new vehicles). Therefore, it is necessary to provide a solution that is capable of improving the performance of signalized intersections during this transition period using connected vehicle data even at low market penetration rates. This research examines the use of connected vehicle data as the only data source at different market penetration rates aiming to provide the required inputs for conventional adaptive signal control systems. The thesis proposes various methodologies to: 1) estimate queues at signalized intersections; 2) dynamically estimate the saturation flow rate required for optimizing the timings of traffic signals at intersections; and 3) estimate the free flow speed on arterials for the purpose of optimizing offsets between traffic signals. This thesis has resulted in the following findings: 1. Connected vehicle data can be used to estimate the queue length at signalized intersections especially for the purpose of estimating the saturation flow rate. The vehicles' length information provided by connected vehicles can be used to enhance the queue estimation when the traffic composition changes on a network. 2. The proposed methodology for estimating the saturation flow rate is able to estimate temporally varying saturation flow rates in response to changing network conditions, including lane blockages and queue spillback that limit discharge rates, and do so with an acceptable range of errors even at low level of market penetration of connected vehicles. The evaluation of the method for a range of traffic Level of Service (LOS) shows that the maximum observed mean absolute relative error (6.2%) occurs at LOS F and when only 10% of vehicles in the traffic stream are connected vehicles. 3. The proposed method for estimating the Free Flow Speed (FFS) on arterial roads can provide estimations close to the known ground truth and can respond to changes in the FFS. The results also show that the maximum absolute error of approximately 4.7 km/h in the estimated FFS was observed at 10% market penetration rate of connected vehicles. 4. The results of an evaluation of an adaptive signal control system based on connected vehicle data in a microsimulation environment show that the adaptive signal control system is able to adjust timings of signals at intersections in response to changes in the saturation flow rate and free flow speed estimated from connected vehicle data using the proposed methodologies. The comparison of the adaptive signal control system against a fixed time control at 20% and 100% CV market penetration rates shows improvements in average vehicular delay and average number of stops at both market penetration rates and though improvements are larger for 100% CV LMP, approximately 70% of these improvements are achieved at 20% CV LMP.

Download or read book Optimal Integrated Dynamic Traffic Assignment and Signal Control for Evacuation of Large Traffic Networks with Varying Threat Levels written by Neema Nassir and published by . This book was released on 2013 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Robustness Approach to the Integrated Network Design Problem Signal Optimization and Dynamic Traffic Assignment Problem written by Ampol Karoonsoontawong and published by . This book was released on 2007 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extensive numerical experiments are conducted to assess the performance of the metaheuristic algorithms, demonstrate the worthiness of the proposed robust formulations and show the benefit of the integrated approach over the sequential approach. The proposed models and metaheuristic algorithms are tested on limited transportation networks.

Download or read book Adaptive Dynamic Programming Single and Multiple Controllers written by Ruizhuo Song and published by Springer. This book was released on 2018-12-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.

Download or read book Traffic Signal Timing Optimization Using Simulation and Dynamic Programming written by Gyana Ranjan Parija and published by . This book was released on 1991 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Integrating Adaptive Queue responsive Traffic Signal Control with Dynamic Traffic Assignment written by Lee-Fang Chow and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT (con't) : Improvements to DTA methods include formulating the dynamic user-optimal route choice model as a variational inequality (VI) model, calculating the expected travel time on each link using a simulation model, applying a relaxation algorithm to produce an equivalent optimization formulation of the VI model, and developing a solution algorithm which can be implemented using existing traffic software. There is not much hope for developing exact solution algorithms to solve these two models simultaneously because of the computational complexity of the non-linear programs. Therefore, a heuristic procedure involving an iterative optimization assignment is used to solve the combined models. A computerized procedure was developed to implement the solution procedures and a numerical example of a traffic network was prepared to test the program. An accepted traffic simulation model, CORSIM 5.1, was used to validate the results for both static and dynamic optimizations. The test results showed that dynamic traffic assignment with adaptive traffic-responsive signal settings reduced the network-wide delays by nearly 15%.

Download or read book Traffic Signal Timing Optimization with Connected Vehicles written by Wan Li and published by . This book was released on 2019 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advent and deployment of Connected vehicle (CV) and Vehicle-to-everything (V2X) communications offer the potential to significantly improve the efficiency of traffic signal control systems. The knowledge of vehicle trajectories in the network allows for optimal signal setting and significant improvements in network performance compared to existing traffic signal control systems. This research aims to develop a framework, including modeling techniques, algorithms, and testing strategies, for urban traffic signal optimization with CVs. The objective is to improve the safety, mobility, and sustainability of all vehicles in the study areas utilizing CV data, i.e., real time information on vehicles' locations and speeds, as well as communications to the signal control systems. The proposed framework is able to optimize traffic signal timing for a single intersection and along a corridor under various market penetration of CVs. Under full penetration rate of CVs, the signal timing optimization and coordination problems are first formulated in a centralized scheme as a mixed-integer nonlinear programing (MINLP). Due to the complexity of the model, the problem is decomposed into two levels: an intersection level to optimize phase durations using dynamic programing (DP) and a corridor level to optimize the offsets of all intersections. Under medium-to-high penetration rates of CVs, Kalman filter methods are applied to estimate trajectories of unequipped vehicles given the available trajectories of CVs. The estimated trajectories combined with CV trajectories are utilized in the trajectory-based signal timing optimization process. Under relatively low penetration rates of CVs, a Deep Intersection Spatial Temporal Network (DISTN) is developed to predict short-term movement-based traffic volumes. The predicted volumes are used in a volume-based adaptive signal control method to calculate signal timing parameters. Comprehensive testing and validation of the proposed methods are conducted in traffic simulation and with real world CV (probe vehicle) data. The testing tasks aim to validate that the developed methods are computationally manageable and have the potential to be implemented in CV-based traffic signal applications in the real world.