Human Factors in Traffic Safety for Highway and Traffic Engineers provides human factors principles and findings to allow nonexperts to consider the road user’s capabilities and limitations more effectively into the practice of design, operations, and safety. It provides data and insights on the needs, capabilities, and limitations of road users, including perception and effects of visual demands, cognition, and influence of expectations on driving behavior. It bridges the gap between human factors research and practical application, presenting complex psychological insights in an accessible manner.This book begins with Part 1 explaining the significance of the traffic safety problem and giving an overview of the importance of human factors in highway design and traffic engineering. Part 2 focuses on driver information perception and processing, including perception of depth and speed, driver’s visual search, how road users search for information, and how mental and information load affects drivers’ performance. Part 3 provides results of investigations of traffic crash causation and reviews major driver errors. Part 4 then describes key principles of road users’ considerations during highway design and traffic operation. Finally, Part 5 focuses on safety analysis and assessment and describes in detail the existing methods to evaluate human factors during safety assessments.This is a valuable resource for professionals in highway and traffic engineering, researchers, policymakers, urban planners, and students to understand how human factors contribute to traffic incidents and how to mitigate these through design and operational strategies.
Models and Applications of Tourists’ Travel Behavior provides an overview of all possible approaches to modeling tourists’ travel behavior, helping readers decide which theoretical approach should be chosen depending on the available type of data. It focuses on the connection between traditional travel behavior theories and tourist studies and introduces specific tourist contexts in travel demand modelling. It goes beyond the theoretical background of tourist travel behavior modeling and offers a practical understanding for choosing the right model and sourcing the right data.The book begins with the role of transport in tourist’ travel behavior, then employs a literature review to establish the necessary background on the topic. It then goes on to describe theoretical approaches, descriptive approaches, and statistical approaches for modelling. It discusses choice models based on both Stated Preference Data and Revealed Preference Data. It concludes with chapters on machine learning methods. This book uniquely focuses on modeling transport with regard to tourism, including mode choice, modelling waiting time, modelling delay, and more.A variety of readers will find this book a valuable resource: Educators can use it as a basis for courses on the quantification of tourists’ travel behavior; students will learn how to deal with modeling tourists’ travel choices; and researchers will benefit from a good starting point from where new models can be developed.
Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling, Second Edition provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing, and controlling mobility patterns—a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications, and concepts in mobility analysis and transportation systems. Fields covered are evolving rapidly, and this new edition updates existing material and provides new chapters that reflect recent developments in the field (such as the emergence of active, transfer and reinforcement learning).Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements, limitations for realistic transportation applications, and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques.
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.
The Digital Transformation of Supply Chain Management offers a roadmap to all areas of supply chain management, with the idea of ecosystem as a center of gravity. The book describes the impact of Internet-driven global information and communication systems in enhancing supply chain management processes. It analyzes six building blocks of supply chain management, including consumer focus and demand, resource and capacity management, procurement and purchasing, inventory management, operation management, and distribution management. The book concludes by presenting the principal innovative solutions available now, or in the future, for managing and increasing the efficiency of supply chains. As supply chains are evolving toward an ecosystem that incorporates a wide range of digital technologies such as the cloud, big data, the Industrial Internet of Services, 3D printing, augmented and virtual reality, blockchain, artificial intelligence, machine learning, and many more, this book is an ideal resource.
Port Planning and Management Simulation examines port planning simulation applications, showing how they supports better port decision-making. Using a clear organizational format based on actual port system structure and operation processes, the book provides practical and theoretical insights on port planning and management. The book describes the water, land, collecting and distributing components of the port system, focusing on management, development, and risk mitigation. It examines the key challenges based on discrete system simulation theory that is less affected by local or national regulations. It compares various simulation scenarios for optimal port operational strategy. It quantifies port emissions, analyzes the impact of different reduction strategies, and presents operational strategies for green port planning developmentmand management. Port Planning and Management Simulation provides guidance for carrying out deep analysis in a complex and dynamic system, providing an integrated solution framework based on simulation techniques for improving efficiency and cost savings of the port system.
Road 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.
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.
Freight Transport Modeling in Emerging Countries examines freight transport models developed in emerging countries including Turkey, South Africa, India, Chile, and more. It provides a toolbox of successful freight transport model applications, alternative data collection methods, and evaluation techniques for the development of future policies. The book offers solutions for issues related to the urban, national, and international transportation of goods and examines new advances in freight transport models and data collection techniques and their applications in emerging countries. Emerging countries have unique transport-related policies, regulatory structures, logistics systems, and long-term uncertainties that hinder their economic development. This book tackles these issues by examining decision-making models for locating logistics sites such as ports and distribution centers, modeling urban freight movements in megacities and port cities, using existing datasets to get information when data is not available, implementing policies related to the national and international movements of goods, and more.
Traffic Congestion and Land Use Regulations: Theory and Policy Analysis explores why, when, where and how land use regulations are utilized in cities to address road transportation congestion. The book shows how to design optimal density and zonal regulations for efficient traffic flow in cities, examines land use regulations using optimal control theory, and offers detailed insights into the mechanisms behind optimal regulations and techniques for exploring spatial optimal policies. Discussions from this book will help highlight the practical usefulness of land use regulations for the maximization of urban social welfare.