Data Driven Intelligent Transportation Systems


Data Driven Intelligent Transportation Systems
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Data Driven Intelligent Transportation Systems


Data Driven Intelligent Transportation Systems
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Author : Zhang, Junping
language : en
Publisher: Academic Press
Release Date : 2014-02-12

Data Driven Intelligent Transportation Systems written by Zhang, Junping and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-12 with Computers categories.


The Series in Intelligent Systems publishes titles that cover state of the art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. The Series 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. 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. Intelligent Transportation Systems (ITS) are rapidly developing in the world and widely used to optimize the transportation management and plan, enhance city and country security, and improve the traffic users’ travel route, safety and health directly or indirectly. To achieve these goals, a large amount of data are collected from a variety of sources related to ITS. Such abundant and various data lead to a revolution of changing ITS to a more powerful and multifunctional Data-driven ITS. As an associate editor in IEEE transactions on Intelligent Transportation Systems and an associate editor in IEEE Intelligent Systems, Junping Zhang surveys the development of Data-driven ITS in detail, discuss some potential issues closely related to ITS and give a roadmap on the future directions, as well as some recent works on the data-driven ITS. An important contribution in this book is that ITS is closely related to up-to-date data-driven techniques such as data mining, machine learning and computer vision, which are less involved in by other previous ITS-related books. For examples, privacy-preserving and people-centric ITS. The first book for the ITS community that focuses on how to utilize data collected from ITS. Data-driven Intelligent Transportation Systems is a rapidly developing topic. This book is the first dedicated to this important topic. • Introduces the latest approaches and techniques I ITYS, including dimension reduction technique such as nonlinear embedding that can address dimensionality, which often impair the effectiveness of ITS. • Includes a range of real word case studies that show how work in ITS, and related areas including machine learning, vision, and data mining can be applied to transportation systems



Data Driven Solutions To Transportation Problems


Data Driven Solutions To Transportation Problems
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Author : Yinhai Wang
language : en
Publisher: Elsevier
Release Date : 2018-12-04

Data Driven Solutions To Transportation Problems written by Yinhai Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-04 with Transportation categories.


Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. Synthesizes the newest developments in data-driven transportation science Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed Useful for both theoretical and technically-oriented researchers



Data Driven Traffic Engineering


Data Driven Traffic Engineering
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Author : Hubert Rehborn
language : en
Publisher: Elsevier
Release Date : 2020-10-23

Data Driven Traffic Engineering written by Hubert Rehborn and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-23 with Transportation categories.


Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory shifts the current focus from using modeling and simulation data for traffic measurements to the use of actual data. The book uses real-world, empirically-derived data from a large fleet of connected vehicles, local observations and aerial observation to shed light on key traffic phenomena. Readers will learn how to develop an understanding of the empirical features of vehicular traffic networks and how to consider these features in emerging, intelligent transport systems. Topics cover congestion patterns, fuel consumption, the influence of weather, and much more. This book offers a unique, data-driven analysis of vehicular traffic in traffic networks, also considering how to apply data-driven insights to the intelligent transport systems of the future. Provides an empirically-driven analysis of traffic measurements/congestion based on real-world data collected from a global fleet of vehicles Applies Kerner’s three-phase traffic theory to empirical data Offers a critical scientific understanding of the underlying concerns of traffic control in automated driving and intelligent transport systems



Mobility Data Driven Urban Traffic Monitoring


Mobility Data Driven Urban Traffic Monitoring
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Author : Zhidan Liu
language : en
Publisher: Springer Nature
Release Date : 2021-05-18

Mobility Data Driven Urban Traffic Monitoring written by Zhidan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-18 with Computers categories.


This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical non-linear traffic correlation modelling-based urban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing framework. Third, in addition to mobility data collected by the public transit systems, the authors present a crowdsensing-based urban traffic monitoring approach. The proposal exploits the lightweight mobility data collected from participatory bus riders to recover traffic statuses through careful data processing and analysis. Last but not the least, the book points out some future research directions, which can further improve the accuracy and efficiency of mobility data-driven urban traffic monitoring at large scale. This book targets researchers, computer scientists, and engineers, who are interested in the research areas of intelligent transportation systems (ITS), urban computing, big data analytic, and Internet of Things (IoT). Advanced level students studying these topics benefit from this book as well.



Handbook Of Mobility Data Mining Volume 3


Handbook Of Mobility Data Mining Volume 3
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Author : Haoran Zhang
language : en
Publisher: Elsevier
Release Date : 2023-01-29

Handbook Of Mobility Data Mining Volume 3 written by Haoran Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-29 with Business & Economics categories.


Handbook of Mobility Data Mining: Volume Three: Mobility Data-Driven Applications introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations. The book introduces how to design MDM platforms that adapt to the evolving mobility environment—and new types of transportation and users—based on an integrated solution that utilizes sensing and communication capabilities to tackle significant challenges faced by the MDM field. This third volume looks at various cases studies to illustrate and explore the methods introduced in the first two volumes, covering topics such as Intelligent Transportation Management, Smart Emergency Management—detailing cases such as the Fukushima earthquake, Hurricane Katrina, and COVID-19—and Urban Sustainability Development, covering bicycle and railway travel behavior, mobility inequality, and road and light pollution inequality. Introduces MDM applications from six major areas: intelligent transportation management, shared transportation systems, disaster management, pandemic response, low-carbon transportation, and social equality Uses case studies to examine possible solutions that facilitate ethical, secure, and controlled emergency management based on mobile big data Helps develop policy innovations beneficial to citizens, businesses, and society Stems from the editor’s strong network of global transport authorities and transport companies, providing a solid knowledge structure and data foundation as well as geographical and stakeholder coverage



Logic Driven Traffic Big Data Analytics


Logic Driven Traffic Big Data Analytics
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Author : Shaopeng Zhong
language : en
Publisher: Springer Nature
Release Date : 2022-02-01

Logic Driven Traffic Big Data Analytics written by Shaopeng Zhong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Business & Economics categories.


This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book. This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data’s impact on mobility patterns and urban planning.



Data Driven Intelligence In Wireless Networks


Data Driven Intelligence In Wireless Networks
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Author : Muhammad Khalil Afzal
language : en
Publisher: CRC Press
Release Date : 2023-03-27

Data Driven Intelligence In Wireless Networks written by Muhammad Khalil Afzal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-27 with Computers categories.


Covers details on wireless communication problems, conducive for data-driven solutions Provides a comprehensive account of programming languages, tools, techniques, and good practices Provides an introduction to data-driven techniques applied to wireless communication systems Examines data-driven techniques, performance, and design issues in wireless networks Includes several case studies that examine data-driven solution for QoS in heterogeneous wireless networks



Data Driven Detection And Diagnosis Of Faults In Traction Systems Of High Speed Trains


Data Driven Detection And Diagnosis Of Faults In Traction Systems Of High Speed Trains
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Author : Hongtian Chen
language : en
Publisher: Springer Nature
Release Date : 2020-04-25

Data Driven Detection And Diagnosis Of Faults In Traction Systems Of High Speed Trains written by Hongtian Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-25 with Technology & Engineering categories.


This book addresses the needs of researchers and practitioners in the field of high-speed trains, especially those whose work involves safety and reliability issues in traction systems. It will appeal to researchers and graduate students at institutions of higher learning, research labs, and in the industrial R&D sector, catering to a readership from a broad range of disciplines including intelligent transportation, electrical engineering, mechanical engineering, chemical engineering, the biological sciences and engineering, economics, ecology, and the mathematical sciences.



Implementing Data Driven Strategies In Smart Cities


Implementing Data Driven Strategies In Smart Cities
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Author : Didier Grimaldi
language : en
Publisher: Elsevier
Release Date : 2021-09-18

Implementing Data Driven Strategies In Smart Cities written by Didier Grimaldi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-18 with Social Science categories.


Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management. Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader’s own business agenda Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility



Data Analytics For Intelligent Transportation Systems


Data Analytics For Intelligent Transportation Systems
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Author : Mashrur Chowdhury
language : en
Publisher: Elsevier
Release Date : 2017-04-05

Data Analytics For Intelligent Transportation Systems written by Mashrur Chowdhury and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-05 with Business & Economics categories.


Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Includes case studies in each chapter that illustrate the application of concepts covered Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies Contains contributors from both leading academic and commercial researchers Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications