Road accidents caused by impaired and distracted driving as well as traffic congestion are on the rise, with the numbers increasing dramatically every day. Intelligent transportation systems (ITS) aim to improve the efficiency and safety of traveling by consolidating vehicle operations, managing vehicle traffic, and notifying drivers with alerts and safety messages in real time. Vehicular Cloud Computing for Traffic Management and Systems provides innovative research on the rapidly advancing applications of vehicle-to-vehicle and vehicle-to-infrastructure communication. It also covers the need to fully utilize vehicular ad-hoc network (VANET) resources to provide updated and dynamic information about the conditions of road traffic so that the number of road accidents can be minimized. Featuring research on topics such as identity management, computational architecture, and resource management, this book is ideally designed for urban planners, researchers, policy makers, graduate-level students, transportation engineers, and technology developers seeking current research on vehicle computational design, architecture, security, and privacy.

"This book attempts to close the gap between science and technology in the field of roadside backbones for VCNs"--Provided by publisher.

"This book tackles the prevalent research challenges that hinder a fully deployable vehicular network, presenting a unified treatment of the various aspects of VANETs and is essential for not only university professors, but also for researchers working in the automobile industry"--Provided by publisher.

"This book examines critical issues involved with telematics such as vehicular network infrastructure, vehicular network communication protocols, and vehicular services and applications"--Provided by publisher.

This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.

This brief presents a stochastic microscopic mobility model that describes the temporal changes of intervehicle distances. The model is consistent with simulated and empirical vehicle traffic patterns. Using stochastic lumpability methods, the proposed mobility model is mapped into an aggregated mobility model that describes the mobility of a group of vehicles. In addition, the proposed mobility model is used to analyze the spatiotemporal VANET topology. Two metrics are proposed to characterize the impact of vehicle mobility on VANET topology: the time period between successive changes in communication link state (connection and disconnection) and the time period between successive changes in node’s one-hop neighborhood. Using the proposed lumped group mobility model, the two VANET topology metrics are probabilistically characterized for different vehicular traffic flow conditions. Furthermore, the limiting behavior of a system of two-hop vehicles and the overlap-state of their coverage ranges is modeled, and the steady-state number of common vehicle neighbors between the two vehicles is approximately derived. The proposed mobility model will facilitate mathematical analysis in VANETs. The spatiotemporal VANET topology analysis provides a useful tool for the development of mobility-aware vehicular network protocols. Mobility Modeling for Vehicular Communication Networks is designed for researchers, developers, and professionals involved with vehicular communications. It is also suitable for advanced-level students interested in communications, transport infrastructure, and infotainment applications.

In spite of their importance and potential societal impact, there is currently no comprehensive source of information about vehicular ad hoc networks (VANETs). Cohesively integrating the state of the art in this emerging field, Vehicular Networks: From Theory to Practice elucidates many issues involved in vehicular networking, including traffic eng

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. - Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring - Uses methods based on video and time series data for traffic modeling and forecasting - Includes case studies, key processes guidance and comparisons of different methodologies

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.