Dynamics and Stochasticity in Transportation Systems : Equations and Examples
Language: English
Published by Elsevier, 2023
- Softcover
- New

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- Title
- Dynamics and Stochasticity in Transportation Systems : Equations and Examples
- Author
- Cantarella, Giulio E.; Fiori, Chiara; Mussone, Lorenzo
- Publisher
- Elsevier
- Publication year
- 2023
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0443219796
- ISBN 13
- 9780443219795
Dynamics and Stochasticity in Transportation Systems Part II: Equations and Examples goes beyond theory and mathematical models to give readers a practical understanding of dynamic and stochastic assignment modeling approaches in transportation systems. After an introduction in Chapter One, following chapters present recent advances, reviews of contents of the corresponding chapters in Giulio Cantarella’s previous book, discussions on numerical examples, comprehensive summaries, and final remarks. Readers will appreciate the fully discussed numerical examples, applications to real cases, review of recent developments and other materials not easily available in the literature, including long proofs. This book bridges mathematical theory with operational needs in a way that no current book does with practical, real-world cases and examples. Academics, researchers, and instructors as well as professionals, practitioners, and consultants will find this a valuable resource for solving network equilibrium problems in transportation systems analysis.
- Covers dynamic aspects of transportation network analysis through application of mathematical models to real cases
- Discusses operational issues of mathematical models for evaluation of traffic and transport demand interventions, giving readers a practical approach to these problems and bridging theoretical and operational aspects together
- Presents recent new developments and the latest research findings since 2019
- Includes numerical examples and applications supported by several figures and tables, allowing the reader to reproduce the presented results
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About the Author
Chiara Fiori is Assistant Professor (tenured track) at the Department of Civil Engineering, University of Salerno, Italy, and she is currently a committee member in the postgraduate education commission, Green Metric program commission and university PNRR (National Recovery and Resilience Plan) commission. Her research interests include sustainable mobility; testing, modeling and simulation of electrified vehicles powertrains (for personal, public and freight mobility) and their impact assessment on eco-routing and electric power grid; integration of microscopic traffic flow and energy consumption models, and effects on traffic control systems; and Multi-Vehicle Dynamic Traffic Assignment. She authored several book chapters and journal articles, including in Elsevier’s Transport Research Part D: Transport and Environment, Transport Research Part C: Emerging Technologies, and Transport Research Part A: Policy and Practice.
Lorenzo Mussone is Associate Professor in Transportation Engineering at Politecnico di Milano, Italy. His main research activities concern modelling of vehicular flow and transport systems by means of different techniques: partial derivative equations for controlling vehicular flow; microscopic approach for dynamic analysis/simulation of flow; neural networks for function approximation; and graph theory for network topology analysis. He has participated in EU programmes and projects funded by the Italian National Council of Research and the Ministry of University. He is member of SIDT (the Italian Society of Transportation Scholars) and IATSS (the International Association for Traffic Safety and Science). He participated in many international conferences, published many scientific papers in international journals, and authored several books and book chapters. He is on the referee panel of many transportation journals and on the editorial board of Accident Analysis and Prevention and Transportation Research Interdisciplinary Perspectives journals.
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