Transportation Network Analysis

Transportation Network Analysis

Author: M. G. H. Bell

Publisher: John Wiley & Sons

Published: 1997-04-21

Total Pages: 240

ISBN-13:

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Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.


Transportation Network Modeling and Calibration

Transportation Network Modeling and Calibration

Author: Mansoureh Jeihani

Publisher: Momentum Press

Published: 2017-09-11

Total Pages: 174

ISBN-13: 1606508946

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This book introduces transportation engineering students and junior engineers to the concept of transportation network modeling, network coding, model calibration and validation, and model evaluation. Transportation scientists employ modeling and simulation techniques to capture the complexities of transportation systems and develop and assess solutions to alleviate existing and future transportation-related problems. This book introduces transportation engineering students and junior engineers to the concept of transportation network modeling, network coding, model calibration and validation, and model evaluation. Travel demand models are sensitive to demographic changes and can explain and forecast how a new transportation supply system leads to a new transportation demand pattern. This book also describes how demand models evolved from trip-based to the newer generation of activity-based and agent-based to overcome some of the shortcomings of the four-step approach and improve models’ prediction power.


Modeling Dynamic Transportation Networks

Modeling Dynamic Transportation Networks

Author: Bin Ran

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 365

ISBN-13: 3642802303

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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.


Advances in Dynamic Network Modeling in Complex Transportation Systems

Advances in Dynamic Network Modeling in Complex Transportation Systems

Author: Satish V. Ukkusuri

Publisher: Springer Science & Business Media

Published: 2013-03-21

Total Pages: 322

ISBN-13: 1461462436

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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.


Schedule-Based Modeling of Transportation Networks

Schedule-Based Modeling of Transportation Networks

Author: Nigel H. M. Wilson

Publisher: Springer Science & Business Media

Published: 2008-10-22

Total Pages: 319

ISBN-13: 0387848126

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"Schedule-Based Modeling of Transportation Networks: Theory and Applications" follows the book Schedule-Based Dynamic Transit Modeling, published in this series in 2004, recognizing the critical role that schedules play in transportation systems. Conceived for the simulation of transit systems, in the last few years the schedule-based approach has been expanded and applied to operational planning of other transportation schedule services besides mass transit, e.g. freight transport. This innovative approach allows forecasting the evolution over time of the on-board loads on the services and their time-varying performance, using credible user behavioral hypotheses. It opens new frontiers in transportation modeling to support network design, timetable setting, and investigation of congestion effects, as well as the assessment of such new technologies, such as users system information (ITS technologies).