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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).
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.
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Over the last two centuries, the development of modern transportation has significantly transformed human life. The main theme of this book is to understand the complexity of transportation development and model the process of network growth including its determining factors, which may be topological, morphological, temporal, technological, economic, managerial, social or political. Using multidimensional concepts and methods, the authors develop a holistic framework to represent network growth as an open and complex process with models that demonstrate in a scientific way how numerous independent decisions made by entities such as travelers, property owners, developers, and public jurisdictions could result in a coherent network of facilities on the ground. Models are proposed from innovative perspectives including self-organization, degeneration, and sequential connection to interpret the evolutionary growth of transportation networks in explicit consideration of independent economic and regulatory initiatives. Employing these models, the authors survey a series of topics ranging from network hierarchy and topology to first mover advantage. The authors demonstrate, with a wide spectrum of empirical and theoretical evidence, that network growth follows a path that is not only logical in retrospect, but also predictable and manageable from a planning perspective. In the larger scheme of innovative transportation planning, this book provides a re-consideration of conventional planning practice and sets the stage for further development on the theory and practice of the next-generation, evolutionary planning approach in transportation, making it of interest to scholars and practitioners alike in the field of transportation .
The Intelligent Systems Series encompasses theoretical studies, design methods, and real-world implementations and applications. It publishes titles in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. Titles focus on professional and academic reference works and handbooks. This volume, Advances in Artificial Transportation Systems and Simulation, covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; and V2V and V2I communications. The readership for the series is broad, reflecting the wide range of intelligent systems interest and application, but focuses on engineering (in particular automation, control, mechatronics, robotics, transportation, automotive, aerospace), electronics and electronic design, and computer science. - Provides researchers and engineers with up to date research results and state-of-the art technologies in the area of intelligent vehicles and transportation systems - Includes case studies plus surveys of the latest research - Covers hot topics including driver assistance systems; cooperative vehicle-highway systems; collision avoidance; pedestrian protection; image, radar and lidar signal processing; V2V and V2I communications
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.
Each chapter in Equilibrium and Advanced Transportation Modelling develops a topic from basic concepts to the state-of-the-art, and beyond. All chapters relate to aspects of network equilibrium. Chapter One advocates the use of simulation models for the representation of traffic flow movements at the microscopic level. Chapter Two presents travel demand systems for generating trip matrices from activity-based models, taking into account the entire daily schedule of network users. Chapter Three examines equilibrium strategic choices adopted by the passengers of a congested transit system, carefully addressing line selection at boarding and transfer nodes. Chapter Four provides a critical appraisal of the traditional process that consists in sequentially performing the tasks of trip generation, trip distribution, mode split and assignment, and its impact on the practice of transportation planning. Chapter Five gives an insightful overview of stochastic assignment models, both in the static and dynamic cases. Chapters Six and Seven investigate the setting of tolls to improve traffic flow conditions in a congested transportation network. Chapter Eight provides a unifying framework for the analysis of multicriteria assignment models. In this chapter, available algorithms are summarized and an econometric perspective on the estimation of heterogeneous preferences is given. Chapter Nine surveys the use of hyperpaths in operations research and proposes a new paradigm of equilibrium in a capacitated network, with an application to transit assignment. Chapter Ten analyzes the transient states of a system moving towards equilibrium, using the mathematical framework of projected dynamical systems. Chapter Eleven discusses an in-depth survey of algorithms for solving shortest path problems, which are pervasive to any equilibrium algorithm. The chapter devotes special attention to the computation of dynamic shortest paths and to shortest hyperpaths. The final chapter considers operations research tools for reducing traffic congestion, in particular introducing an algorithm for solving a signal-setting problem formulated as a bilevel program.
This comprehensive textbook/reference provides an in-depth overview of the key aspects of transportation analysis, with an emphasis on modeling real transportation systems and executing the models. Topics and features: presents comprehensive review questions at the end of each chapter, together with detailed case studies, useful links, references and suggestions for further reading; supplies a variety of teaching support materials at the book’s webpage on Springer.com, including a complete set of lecture slides; examines the classification of models used for multimodal transportation systems, and reviews the models and evaluation methods used in transportation planning; explains traffic assignment to road networks, and describes computer simulation integration platforms and their use in the transportation systems sector; provides an overview of transportation simulation tools, and discusses the critical issues in the design, development and use of the simulation models.