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Author: Dominique Lord
Publisher: Elsevier
ISBN: 9780443300264
Category : Law
Languages : en
Pages : 0
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Book Description
Highway Safety Analytics and Modeling, Second Edition comprehensively covers the key elements for effective transportation engineering and policy decisions based on highway safety data analysis in a single reference. It includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating results. It discusses the challenges of working with crash and naturalistic data, identifies problems, and proposes well-researched methods to solve them. It examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes. This thoroughly updated second edition updates the material contained in the book based on the latest advancements in highway safety research as well as feedback from readers. It includes entirely new sections on topics such as digital twins as a source of data, model validation, extreme value models, temporal instability, joint crash frequency and severity modeling, sample size, quasi-induced exposure method, autonomous vehicle safety estimate, and more. This book serves as a valuable reference for students, researchers, and practitioners alike. It provides more examples and exercises to help in using the book for courses, and it continues to complement the Highway Safety Manual (HSM) published by the American Association of State Highway and Transportation Officials (AAHSTO), thus helping in the training of engineers and practitioners to better understand the concepts and methods outlined in the forthcoming HSM.
Author: Dominique Lord
Publisher: Elsevier
ISBN: 9780443300264
Category : Law
Languages : en
Pages : 0
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Book Description
Highway Safety Analytics and Modeling, Second Edition comprehensively covers the key elements for effective transportation engineering and policy decisions based on highway safety data analysis in a single reference. It includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating results. It discusses the challenges of working with crash and naturalistic data, identifies problems, and proposes well-researched methods to solve them. It examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes. This thoroughly updated second edition updates the material contained in the book based on the latest advancements in highway safety research as well as feedback from readers. It includes entirely new sections on topics such as digital twins as a source of data, model validation, extreme value models, temporal instability, joint crash frequency and severity modeling, sample size, quasi-induced exposure method, autonomous vehicle safety estimate, and more. This book serves as a valuable reference for students, researchers, and practitioners alike. It provides more examples and exercises to help in using the book for courses, and it continues to complement the Highway Safety Manual (HSM) published by the American Association of State Highway and Transportation Officials (AAHSTO), thus helping in the training of engineers and practitioners to better understand the concepts and methods outlined in the forthcoming HSM.
Author: Dominique Lord
Publisher: Elsevier
ISBN: 0128168196
Category : Law
Languages : en
Pages : 504
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Book Description
Highway Safety Analytics and Modeling comprehensively covers the key elements needed to make effective transportation engineering and policy decisions based on highway safety data analysis in a single. reference. The book includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating analysis results. It discusses the challenges of working with crash and naturalistic data, identifies problems and proposes well-researched methods to solve them. Finally, the book examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes. - Complements the Highway Safety Manual by the American Association of State Highway and Transportation Officials - Provides examples and case studies for most models and methods - Includes learning aids such as online data, examples and solutions to problems
Author: Mashrur Chowdhury
Publisher: Elsevier
ISBN: 0443138796
Category : Computers
Languages : en
Pages : 473
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Book Description
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including 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. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover 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. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
Author: Subasish Das
Publisher: CRC Press
ISBN: 1000726266
Category : Computers
Languages : en
Pages : 354
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Book Description
Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway safety within its contexts, while drawing attention to the predictive powers of AI techniques in solving complex problems for safety improvement. This book provides both theoretical and practical aspects of highway safety. Each chapter contains theory and its contexts in plain language with several real-life examples. It is suitable for anyone interested in highway safety and AI and it provides an illuminating and accessible introduction to this fast-growing research trend. Material supplementing the book can be found at https://github.com/subasish/AI_in_HighwaySafety. It offers a variety of supplemental materials, including data sets and R codes.
Author:
Publisher: Elsevier
ISBN: 0081026722
Category : Law
Languages : en
Pages : 4418
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Book Description
In an increasingly globalised world, despite reductions in costs and time, transportation has become even more important as a facilitator of economic and human interaction; this is reflected in technical advances in transportation systems, increasing interest in how transportation interacts with society and the need to provide novel approaches to understanding its impacts. This has become particularly acute with the impact that Covid-19 has had on transportation across the world, at local, national and international levels. Encyclopedia of Transportation, Seven Volume Set - containing almost 600 articles - brings a cross-cutting and integrated approach to all aspects of transportation from a variety of interdisciplinary fields including engineering, operations research, economics, geography and sociology in order to understand the changes taking place. Emphasising the interaction between these different aspects of research, it offers new solutions to modern-day problems related to transportation. Each of its nine sections is based around familiar themes, but brings together the views of experts from different disciplinary perspectives. Each section is edited by a subject expert who has commissioned articles from a range of authors representing different disciplines, different parts of the world and different social perspectives. The nine sections are structured around the following themes: Transport Modes; Freight Transport and Logistics; Transport Safety and Security; Transport Economics; Traffic Management; Transport Modelling and Data Management; Transport Policy and Planning; Transport Psychology; Sustainability and Health Issues in Transportation. Some articles provide a technical introduction to a topic whilst others provide a bridge between topics or a more future-oriented view of new research areas or challenges. The end result is a reference work that offers researchers and practitioners new approaches, new ways of thinking and novel solutions to problems. All-encompassing and expertly authored, this outstanding reference work will be essential reading for all students and researchers interested in transportation and its global impact in what is a very uncertain world. Provides a forward looking and integrated approach to transportation Updated with future technological impacts, such as self-driving vehicles, cyber-physical systems and big data analytics Includes comprehensive coverage Presents a worldwide approach, including sets of comparative studies and applications
Author: Dominique Lord
Publisher: Emerald Group Publishing
ISBN: 1787148920
Category : Transportation
Languages : en
Pages : 511
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Book Description
This book increases the level of knowledge on road safety contexts, issues and challenges; shares what can currently be done to address the variety of issues; and points to what needs to be done to make further gains in road safety.
Author: Robert Stevens
Publisher: CRC Press
ISBN: 1003806244
Category : Computers
Languages : en
Pages : 99
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Book Description
Nearly all our safety data collection and reporting systems are backwardlooking: incident reports; dashboards; compliance monitoring systems; and so on. This book shows how we can use safety data in a forward-looking, predictive sense. Predictive Safety Analytics: Reducing Risk through Modeling and Machine Learning contains real use cases where organizations have reduced incidents by employing predictive analytics to foresee and mitigate future risks. It discusses how Predictive Safety Analytics is an opportunity to break through the plateau problem where safety rate improvements have stagnated in many organizations. The book presents how the use of data, coupled with advanced analytical techniques, including machine learning, has become a proven and successful innovation. Emphasis is placed on how the book can “meet you where you are” by illuminating a path to get there, starting with simple data the organization likely already has. Highlights of the book are the real examples and case studies that will assist in generating thoughts and ideas for what might work for individual readers and how they can adapt the information to their particular situations. This book is written for professionals and researchers in system reliability, risk and safety assessment, quality control, operational managers in selected industries, data scientists, and ML engineers. Students taking courses in these areas will also find this book of interest to them.
Author: Sanjay Chakraborty
Publisher: Springer Nature
ISBN: 3030930882
Category : Technology & Engineering
Languages : en
Pages : 210
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Book Description
This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.
Author: Lipika Deka
Publisher: Elsevier
ISBN: 0128142960
Category : Transportation
Languages : en
Pages : 350
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Book Description
Transportation Cyber-Physical Systems provides current and future researchers, developers and practitioners with the latest thinking on the emerging interdisciplinary field of Transportation Cyber Physical Systems (TCPS). The book focuses on enhancing efficiency, reducing environmental stress, and meeting societal demands across the continually growing air, water and land transportation needs of both people and goods. Users will find a valuable resource that helps accelerate the research and development of transportation and mobility CPS-driven innovation for the security, reliability and stability of society at-large. The book integrates ideas from Transport and CPS experts and visionaries, consolidating the latest thinking on the topic. As cars, traffic lights and the built environment are becoming connected and augmented with embedded intelligence, it is important to understand how smart ecosystems that encompass hardware, software, and physical components can help sense the changing state of the real world. - Bridges the gap between the transportation, CPS and civil engineering communities - Includes numerous examples of practical applications that show how diverse technologies and topics are integrated in practice - Examines timely, state-of-the-art topics, such as big data analytics, privacy, cybersecurity and smart cities - Shows how TCPS can be developed and deployed, along with its associated challenges - Includes pedagogical aids, such as Illustrations of application scenarios, architecture details, tables describing available methods and tools, chapter objectives, and a glossary - Contains international contributions from academia, government and industry
Author: Martin Treiber
Publisher: Springer Science & Business Media
ISBN: 3642324592
Category : Science
Languages : en
Pages : 505
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Book Description
This 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.
