A Mathematical Model for Traffic Forecasting
Author: Peter S. Loubal
Publisher:
Published: 1968
Total Pages: 208
ISBN-13:
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Author: Peter S. Loubal
Publisher:
Published: 1968
Total Pages: 208
ISBN-13:
DOWNLOAD EBOOKAuthor: Michael Freitag
Publisher: Springer Nature
Published: 2021-12-02
Total Pages: 322
ISBN-13: 303088662X
DOWNLOAD EBOOKThis open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions.
Author: David Tong Yong Lee
Publisher:
Published: 1972
Total Pages: 296
ISBN-13:
DOWNLOAD EBOOKAuthor: Jiahao Wang
Publisher:
Published: 2021
Total Pages:
ISBN-13:
DOWNLOAD EBOOKIntelligent Transportation Systems (ITS) have attracted an increasing amount of attention in recent years. Thanks to the fast development of vehicular computing hardware, vehicular sensors and citywide infrastructures, many impressive applications have been proposed under the topic of ITS, such as Vehicular Cloud (VC), intelligent traffic controls, etc. These applications can bring us a safer, more efficient, and also more enjoyable transportation environment. However, an accurate and efficient traffic flow prediction system is needed to achieve these applications, which creates an opportunity for applications under ITS to deal with the possible road situation in advance. To achieve better traffic flow prediction performance, many prediction methods have been proposed, such as mathematical modeling methods, parametric methods, and non-parametric methods. It is always one of the hot topics about how to implement an efficient, robust and accurate vehicular traffic prediction system. With the help of Machine Learning-based (ML) methods, especially Deep Learning-based (DL) methods, the accuracy of the prediction model is increased. However, we also noticed that there are still many open challenges under ML-based vehicular traffic prediction model real-world implementation. Firstly, the time consumption for DL model training is relatively huge compared to parametric models, such as ARIMA, SARIMA, etc. Second, it is still a hot topic for the road traffic prediction that how to capture the special relationship between road detectors, which is affected by the geographic correlation, as well as the time change. The last but not the least, it is important for us to implement the prediction system in the real world; meanwhile, we should find a way to make use of the advanced technology applied in ITS to improve the prediction system itself. In our work, we focus on improving the features of the prediction model, which can be helpful for implementing the model in the real word. Firstly, we introduced an optimization strategy for ML-based models' training process, in order to reduce the time cost in this process. Secondly, We provide a new hybrid deep learning model by using GCN and the deep aggregation structure (i.e., the sequence to sequence structure) of the GRU. Meanwhile, in order to solve the real-world prediction problem, i.e., the online prediction task, we provide a new online prediction strategy by using refinement learning. In order to further improve the model's accuracy and efficiency when applied to ITS, we provide a parallel training strategy by using the benefits of the vehicular cloud structure.
Author: Fouzi Harrou
Publisher: Elsevier
Published: 2021-10-05
Total Pages: 270
ISBN-13: 0128234334
DOWNLOAD EBOOKRoad Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems. - Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring - Uses methods based on video and time series data for traffic modeling and forecasting - Includes case studies, key processes guidance and comparisons of different methodologies
Author: Martin Treiber
Publisher: Springer Science & Business Media
Published: 2012-10-11
Total Pages: 505
ISBN-13: 3642324592
DOWNLOAD EBOOKThis textbook provides a comprehensive and instructive coverage of vehicular traffic flow dynamics and modeling. It makes this fascinating interdisciplinary topic, which to date was only documented in parts by specialized monographs, accessible to a broad readership. Numerous figures and problems with solutions help the reader to quickly understand and practice the presented concepts. This book is targeted at students of physics and traffic engineering and, more generally, also at students and professionals in computer science, mathematics, and interdisciplinary topics. It also offers material for project work in programming and simulation at college and university level. The main part, after presenting different categories of traffic data, is devoted to a mathematical description of the dynamics of traffic flow, covering macroscopic models which describe traffic in terms of density, as well as microscopic many-particle models in which each particle corresponds to a vehicle and its driver. Focus chapters on traffic instabilities and model calibration/validation present these topics in a novel and systematic way. Finally, the theoretical framework is shown at work in selected applications such as traffic-state and travel-time estimation, intelligent transportation systems, traffic operations management, and a detailed physics-based model for fuel consumption and emissions.
Author: Alan J. Horowitz
Publisher: Transportation Research Board
Published: 2006
Total Pages: 125
ISBN-13: 0309097657
DOWNLOAD EBOOKTRB's National Cooperative Highway Research Program (NCHRP) Synthesis 358: Statewide Travel Forecasting Models examines statewide travel forecasting models designed to address planning needs and provide forecasts for statewide transportation, including passenger vehicle and freight movements. The report explores the types and purposes of models being used, integration of state and urban models, data requirements, computer needs, resources (including time, funding, training, and staff), limitations, and overall benefits. The report includes five case studies, two that focus on passenger components, two on freight components, and one on both passenger and freight.
Author: Gabriella Puppo
Publisher: Springer Nature
Published: 2021-03-31
Total Pages: 102
ISBN-13: 3030665607
DOWNLOAD EBOOKThe book originates from the mini-symposium "Mathematical descriptions of traffic flow: micro, macro and kinetic models" organised by the editors within the ICIAM 2019 Congress held in Valencia, Spain, in July 2019. The book is composed of five chapters, which address new research lines in the mathematical modelling of vehicular traffic, at the cutting edge of contemporary research, including traffic automation by means of autonomous vehicles. The contributions span the three most representative scales of mathematical modelling: the microscopic scale of particles, the mesoscopic scale of statistical kinetic description and the macroscopic scale of partial differential equations.The work is addressed to researchers in the field.
Author: David A. Hensher
Publisher: Elsevier Science Limited
Published: 2007-09-14
Total Pages: 826
ISBN-13:
DOWNLOAD EBOOKSince 2000, there has been an exponential amount of research completed in the field of transport modelling thereby creating a need for an expanded and revised edition of this book. National transport models have taken on the new modelling methods and there have been theoretical and empirical advances in performance measurement. Coverage will include current demand methods, data issues, valuation, cost and performance, and updated traffic models. Supplementary case studies will illustrate how modelling can be applied to the study of the different transport modes and the infrastructures that support them.The second edition of this handbook will continue to be an essential reference for researchers and practitioners in the field. All contributions are by leading experts in their fields and there is extensive cross-referencing of subject matter. This book features expanded coverage on emerging trends and updated case studies. It addresses models for specific applications (i.e. parking, national traffic forecasting, public transport, urban freight movements, and logistics management).
Author: Alexander Palagin
Publisher: Springer
Published: 2019-07-17
Total Pages: 268
ISBN-13: 303025741X
DOWNLOAD EBOOKThis book presents current investigations in the field of mathematical modeling and simulation to support the development of intelligent information systems in domains such as ecology and geology, manufacturing, project management, and safety of distributed information systems. The book will be of interest to developers of modern high-tech software complexes for situational control centers, based on mathematical modeling and simulation methods. In addition, it will appeal to software engineers and programmers, offering them new implementation and application methods. Gathering the latest research, prepared by leading scholars, and identifying promising new directions for solving complex scientific and practical problems, the book presents selected outcomes of the 14th International Scientific-Practical Conference, MODS2019, held in Chernihiv, Ukraine, on June 24 to 26, 2019.