| Vorliegende Sprache |
eng |
| ISBN |
978-1-4614-6242-2 |
| Name |
Ukkusuri, Satish V. |
| Ozbay, Kaan |
| Name ANZEIGE DER KETTE |
Ozbay, Kaan |
| T I T E L |
Advances in Dynamic Network Modeling in Complex Transportation Systems |
| Verlagsort |
New York, NY |
| Verlag |
Springer |
| Erscheinungsjahr |
2013 |
| 2013 |
| Umfang |
Online-Ressource (X, 316 p. 92 illus., 63 illus. in color, digital) |
| Reihe |
Complex Networks and Dynamic Systems ; 2 |
| Notiz / Fußnoten |
Description based upon print version of record |
| Weiterer Inhalt |
Advances in Dynamic Network Modeling in Complex Transportation Systems; Preface; Contents; Chapter 1 Dynamic Traffic Assignment: A Survey of Mathematical Models and Techniques; 1.1 Introduction; 1.2 Mathematical Programming-based Static Traffic Assignment Model; 1.2.1 User-Equilibrium; 1.2.1.1 Mathematical Programming Formulation; 1.2.1.2 Equivalence with Wardrop User-Equilibrium Condition; 1.2.2 System Optimal Solution; 1.2.2.1 Mathematical Programming Formulation; 1.2.2.2 Equivalence with Marginal User-Equilibrium Condition; 1.2.3 Numerical Schemes. 1.3 Variational Inequality-based Static Traffic Assignment Model1.4 Projected Dynamical Systems: Dynamic Variational Equation Model; 1.4.1 Dynamic Route Choice; 1.5 Dynamic Traffic Assignment; 1.5.1 Dynamic Traffic Assignment: Discrete Time; 1.5.2 Dynamic Traffic Assignment: Continuous Time; 1.6 Travel Time and FIFO Issue; 1.7 Macroscopic Model for DTA; 1.7.1 Greenshield's Model; 1.7.2 Generalized/Weak Solution for the LWR Model; 1.7.2.1 Generalized Solutions; 1.7.2.2 Weak Solutions; 1.7.3 Scalar Initial-Boundary Problem; 1.7.4 Macroscopic (PDE) Traffic Network; 1.7.5 Travel Time Dynamics. 1.8 Simulation-Based DTA1.8.1 Iterations for User-Equilibrium; 1.8.2 Calibration from Field Data; 1.9 Traffic Operation Design and Feedback Control; 1.10 Conclusions; References; Chapter 2 The Max-Pressure Controller for Arbitrary Networks of Signalized Intersections; 2.1 Introduction; 2.2 Network Calculus for a Single Queue; 2.3 Performance Bounds for a Single Intersection; 2.3.1 Analysis of a Single Movement; 2.3.2 Analysis of All Movements at an Intersection; 2.3.3 Work-Conserving Controllers; 2.3.3.1 Actuating Single Phase Intersections; 2.3.3.2 Two Counter-Examples. 2.3.3.3 The Adaptive Controller Problem2.4 Performance Bounds for a Network of Intersections; 2.4.1 Network Model; 2.4.2 Performance of Fixed-Cycle Controller; 2.4.3 Max-Pressure Controller; 2.4.4 Two Extensions of Max-Pressure Controller; 2.5 Discussion; 2.5.1 Intuition; 2.5.2 Comparison with Other Designs; 2.5.3 Model Limitations; 2.5.4 Future Work; 2.6 Conclusion; A Proof of Lemma 1; B Proof of Theorem 1; C Proof of Theorem 4; D Proof of (2.56); E Proof of (2.81); References. Chapter 3 Coordinated Feedback-Based Freeway Ramp Metering Control Strategies ``C-MIXCROS and D-MIXCROS'' that Take Ramp Queues into Account3.1 Introduction; 3.2 Motivation; 3.3 Description of the Coordinated Version of MIXCROS; 3.4 Freeway Traffic Model; 3.5 The Control Objective; 3.6 Coordinated MIXCROS Control Law; 3.7 Derivation of the Discrete Version of Coordinated MIXCROS Control Law; 3.7.1 Decoupled Control: D-MIXCROS; 3.7.2 Coupled Control: C-MIXCROS; 3.8 Macroscopic Simulation Model; 3.9 Microscopic Simulation Model; 3.10 Conclusions; References. Chapter 4 Solving the Integrated Corridor Control Problem Using Simultaneous Perturbation Stochastic Approximation. Dynamic Traffic Assignment: A Survey of Mathematical Models and Techniques -- The Max-pressure Controller for Arbitrary Networks of Signalized Intersections -- Coordinated Feedback-Based Freeway ramp Metering Control Strategies "C-MIXCROS and D-MIXROS" that Take Ramp Queues into Account -- Solving the Integrated Corridor Control Problem Using Simultaneous Perturbation Stochastic Approximation -- Analyses of Arterial Travel Times based on Probe Data -- A Multibuffer Model for LWR Road Networks -- Cell-based Dynamic Equilibrium Models -- Information Impacts on Traveler Behavior and Network Performance: State of Knowledge and Future Directions -- Modeling Within-Day Activity Rescheduling Decisions under Time-Varying Network Conditions -- Dynamic Navigation in Direction-Dependent Environments -- An Approach to Assess the Impact of Dynamic Congestion in Vehicle Routing Problems -- Incident Duration Prediction with Hybrid Tree-based Quantile Regression. |
| Titelhinweis |
Buchausg. u.d.T.ISBN: 978-1-461-46242-2 |
| ISBN |
ISBN 978-1-4614-6243-9 |
| Klassifikation |
KJMD |
| KJT |
| BUS049000 |
| 658.40301 |
| 388.31015118 |
| HD30.23 |
| Kurzbeschreibung |
Dynamic Traffic Assignment: A Survey of Mathematical Models and Techniques -- The Max-pressure Controller for Arbitrary Networks of Signalized Intersections -- Coordinated Feedback-Based Freeway ramp Metering Control Strategies "C-MIXCROS and D-MIXROS" that Take Ramp Queues into Account -- Solving the Integrated Corridor Control Problem Using Simultaneous Perturbation Stochastic Approximation -- Analyses of Arterial Travel Times based on Probe Data -- A Multibuffer Model for LWR Road Networks -- Cell-based Dynamic Equilibrium Models -- Information Impacts on Traveler Behavior and Network Performance: State of Knowledge and Future Directions -- Modeling Within-Day Activity Rescheduling Decisions under Time-Varying Network Conditions -- Dynamic Navigation in Direction-Dependent Environments -- An Approach to Assess the Impact of Dynamic Congestion in Vehicle Routing Problems -- Incident Duration Prediction with Hybrid Tree-based Quantile Regression |
| 2. Kurzbeschreibung |
This edited book focuses on recent developments in Dynamic Network Modeling, including aspects of route guidance and traffic control as they relate to transportation systems and other complex infrastructure networks. Dynamic Network Modeling is generally understood to be the mathematical modeling of time-varying vehicular flows on networks in a fashion that is consistent with established traffic flow theory and travel demand theory. Dynamic Network Modeling as a field has grown over the last thirty years, with contributions from various scholars all over the field. The basic problem which many scholars in this area have focused on is related to the analysis and prediction of traffic flows satisfying notions of equilibrium when flows are changing over time. In addition, recent research has also focused on integrating dynamic equilibrium with traffic control and other mechanism designs such as congestion pricing and network design. Recently, advances in sensor deployment, availability of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states and have contributed to new research problems which advance previous models in dynamic modeling. A recent National Science Foundation workshop on “Dynamic Route Guidance and Traffic Control” was organized in June 2010 at Rutgers University by Prof. Kaan Ozbay, Prof. Satish Ukkusuri , Prof. Hani Nassif, and Professor Pushkin Kachroo. This workshop brought together experts in this area from universities, industry and federal/state agencies to present recent findings in this area. Various topics were presented at the workshop including dynamic traffic assignment, traffic flow modeling, network control, complex systems, mobile sensor deployment, intelligent traffic systems and data collection issues. This book is motivated by the research presented at this workshop and the discussions that followed |
| 1. Schlagwortkette |
Transportsystem |
| Netzwerkmodell |
| Operations Research |
| ANZEIGE DER KETTE |
Transportsystem -- Netzwerkmodell -- Operations Research |
| SWB-Titel-Idn |
381117049 |
| Signatur |
Springer E-Book |
| Bemerkungen |
Elektronischer Volltext - Campuslizenz |
| Elektronische Adresse |
$uhttp://dx.doi.org/10.1007/978-1-4614-6243-9 |
| Internetseite / Link |
Volltext |
| Siehe auch |
Volltext |
