This book offers a detailed investigation of breakdowns in traffic and transportation networks. It shows empirically that transitions from free flow to so-called synchronized flow, initiated by local disturbances at network bottlenecks, display a nucleation-type behavior: while small disturbances in free flow decay, larger ones grow further and lead to breakdowns at the bottlenecks. Further, it discusses in detail the significance of this nucleation effect for traffic and transportation theories, and the consequences this has for future automatic driving, traffic control, dynamic traffic assignment, and optimization in traffic and transportation networks. Starting from a large volume of field traffic data collected from various sources obtained solely through measurements in real world traffic, the author develops his insights, with an emphasis less on reviewing existing methodologies, models and theories, and more on providing a detailed analysis of empirical traffic data and drawing consequences regarding the minimum requirements for any traffic and transportation theories to be valid. The book - proves the empirical nucleation nature of traffic breakdown in networks - discusses the origin of the failure of classical traffic and transportation theories - shows that the three-phase theory is incommensurable with the classical traffic theories, and - explains why current state-of-the art dynamic traffic assignments tend to provoke heavy traffic congestion, making it a valuable reference resource for a wide audience of scientists and postgraduate students interested in the fundamental understanding of empirical traffic phenomena and related data-driven phenomenology, as well as for practitioners working in the fields of traffic and transportation engineering.

The problems of urban traffic in the industrially developed countries have been at the top of the priority list for a long time. While making a critical contribution to the economic well being of those countries, transportation systems in general and highway traffic in particular, also have detrimental effects which are evident in excessive congestion, high rates of accidents and severe pollution problems. Scientists from different disciplines have played an important role in the development and refinement of the tools needed for the planning, analysis, and control of urban traffic networks. In the past several years, there were particularly rapid advances in two areas that affect urban traffic: 1. Modeling of traffic flows in urban networks and the prediction of the resulting equilibrium conditions; 2. Technology for communication with the driver and the ability to guide him, by providing him with useful, relevant and updated information, to his desired destination.

The understanding of empirical traf?c congestion occurring on unsignalized mul- lane highways and freeways is a key for effective traf?c management, control, or- nization, and other applications of transportation engineering. However, the traf?c ?ow theories and models that dominate up to now in transportation research journals and teaching programs of most universities cannot explain either traf?c breakdown or most features of the resulting congested patterns. These theories are also the - sis of most dynamic traf?c assignment models and freeway traf?c control methods, which therefore are not consistent with features of real traf?c. For this reason, the author introduced an alternative traf?c ?ow theory called three-phase traf?c theory, which can predict and explain the empirical spatiot- poral features of traf?c breakdown and the resulting traf?c congestion. A previous book “The Physics of Traf?c” (Springer, Berlin, 2004) presented a discussion of the empirical spatiotemporal features of congested traf?c patterns and of three-phase traf?c theory as well as their engineering applications. Rather than a comprehensive analysis of empirical and theoretical results in the ?eld, the present book includes no more empirical and theoretical results than are necessary for the understanding of vehicular traf?c on unsignalized multi-lane roads. The main objectives of the book are to present an “elementary” traf?c ?ow theory and control methods as well as to show links between three-phase traf?c t- ory and earlier traf?c ?ow theories. The need for such a book follows from many commentsofcolleaguesmadeafterpublicationofthebook“ThePhysicsofTraf?c”.

This book constitutes the refereed proceedings of the 7th International Conference on Computational Data and Social Networks, CSoNet 2018, held in Shanghai, China, in December 2018. The 44 revised full papers presented in this book toghether with 2 extended abstracts, were carefully reviewed and selected from 106 submissions. The topics cover the fundamental background, theoretical technology development, and real-world applications associated with complex and data network analysis, minimizing in uence of rumors on social networks, blockchain Markov modelling, fraud detection, data mining, internet of things (IoT), internet of vehicles (IoV), and others.

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

This book addresses the reader interested in vehicular traffic phenomena, who have not learned about them before. It presents traffic phenomena like traffic breakdown and the emergence of moving traffic jams by showcasing empirical traffic data measured in real-world traffic. The author explains how these empirical traffic studies have led to the three-phase traffic theory and why this new theory is in conflict with standard traffic theories developed before. Moreover, he presents the reason for the failure of applications of standard traffic theories in real-world traffic and discusses why understanding real traffic has caused a paradigm shift in traffic and transportation science. The book examines why understanding real traffic breakdown is the basis for an explanation for the autonomous driving effects on traffic flow. It shows that understanding real traffic is possible from real-world traffic data without the need of mathematical traffic models. This makes the book intuitive for non-specialists, who can qualitatively understand all the basic features of traffic dynamics. In turn, experienced traffic researchers can grasp concepts and ideas made here easily accessible by the author, one of the leading pioneers in the field of vehicular traffic.