Highway Safety Analytics and Modeling


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




Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation


Book Description

Covers empirical approaches to outlier detection in intelligent transportation systems data, modeling of traffic crash-flow relationships for intersections, profiling of high-frequency accident locations by use of association rules, analysis of rollovers and injuries with sport utility vehicles, and automated accident detection at intersections via digital audio signal processing.




Transportation Accident Analysis and Prevention


Book Description

This book is dedicated to research on transportation accidental injury and damage, including the pre-injury and immediate post-injury phases. It also includes studies of human, environmental and vehicular factors influencing the occurrence, type and severity of transportation accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety and prevention of traffic accidents.




Statistical Methods


Book Description

This Transportation Research Record contains 28 papers dealing with statistical methods in highway safety research; highway safety data, analysis, and evaluation; occupant protection; and systematic reviews and meta-analysis. The papers address such topics as risk and crash prediction models, crashes on freeways and at signalized intersections, multivehicle crash prediction, speed and safety, red light running crashes, freeway lane closures, ramp design, accident exposure, rumble strip benefits, collisions with median trees, intersection safety, accident reconstruction, safety effects of speed limit changes, geometric design and head-on crashes, deer-vehicle crashes, sport utility vehicle rollover, vehicle occupancy and crash risk, a logit model for studying injury severity, abdominal injuries in rail passengers, healthy transport policies, and meta-analysis.




Transportation Cyber-Physical Systems


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




Mathematical and Statistical Methods for Actuarial Sciences and Finance


Book Description

The cooperation and contamination between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas, in the form of four- to six-page papers, presented at the International Conference eMAF2020 – Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the now sadly famous COVID-19 pandemic, the conference was held remotely through the Zoom platform offered by the Department of Economics of the Ca’ Foscari University of Venice on September 18, 22 and 25, 2020. eMAF2020 is the ninth edition of an international biennial series of scientific meetings, started in 2004 at the initiative of the Department of Economics and Statistics of the University of Salerno. The effectiveness of this idea has been proven by wide participation in all editions, which have been held in Salerno (2004, 2006, 2010 and 2014), Venice (2008, 2012 and 2020), Paris (2016) and Madrid (2018). This book covers a wide variety of subjects: artificial intelligence and machine learning in finance and insurance, behavioral finance, credit risk methods and models, dynamic optimization in finance, financial data analytics, forecasting dynamics of actuarial and financial phenomena, foreign exchange markets, insurance models, interest rate models, longevity risk, models and methods for financial time series analysis, multivariate techniques for financial markets analysis, pension systems, portfolio selection and management, real-world finance, risk analysis and management, trading systems, and others. This volume is a valuable resource for academics, PhD students, practitioners, professionals and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.




Applied Predictive Modeling


Book Description

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.







Statistical Methods


Book Description

This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters




Proceedings of International Conference on Recent Trends in Computing


Book Description

This book is a collection of high-quality peer-reviewed research papers presented at International Conference on Recent Trends in Computing (ICRTC 2022) held at SRM Institute of Science and Technology, Ghaziabad, Delhi, India, during 3 – 4 June 2022. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. The book presents original works from researchers from academic and industry in the field of networking, security, big data and the Internet of things.