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TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 307: Systems Engineering Processes for Developing Traffic Signal Systems discusses the systems engineering techniques available to traffic signal systems and identifies the key processes in a number of traffic signal systems engineering areas.
This report serves as a comprehensive guide to traffic signal timing and documents the tasks completed in association with its development. The focus of this document is on traffic signal control principles, practices, and procedures. It describes the relationship between traffic signal timing and transportation policy and addresses maintenance and operations of traffic signals. It represents a synthesis of traffic signal timing concepts and their application and focuses on the use of detection, related timing parameters, and resulting effects to users at the intersection. It discusses advanced topics briefly to raise awareness related to their use and application. The purpose of the Signal Timing Manual is to provide direction and guidance to managers, supervisors, and practitioners based on sound practice to proactively and comprehensively improve signal timing. The outcome of properly training staff and proactively operating and maintaining traffic signals is signal timing that reduces congestion and fuel consumption ultimately improving our quality of life and the air we breathe. This manual provides an easy-to-use concise, practical and modular guide on signal timing. The elements of signal timing from policy and funding considerations to timing plan development, assessment, and maintenance are covered in the manual. The manual is the culmination of research into practices across North America and serves as a reference for a range of practitioners, from those involved in the day to day management, operation and maintenance of traffic signals to those that plan, design, operate and maintain these systems.
Transformations in wireless connectivity and location-aware technologies hold the promise of bringing a sea-change in the way transportation information is generated and used in the future. Sensors in the transportation system, when integrated with those in other sectors (for example, energy, utility and health) have the potential to foster novel new ways of improving livability and sustainability. The end-result of these developments has been somewhat contradictory. Although automation in the transportation environment has become increasingly widespread, the level of involvement and active participation by people, in terms of co-creation and contribution of information, has also increased. As a result, the following two major trends have been observed: (1) increases in Machine-to- Machine (M2M) communications; and (2) increases in the variety and volume of User-Generated Content. In this transportation paradigm, the pervasive use of Information and Communication Technologies will serve as the foundation for mobility intelligence towards an “ubiquitous information-centered mobility environment”. However, many technical and operational questions, as well as social, management and legal challenges present themselves in the transformation to this vision. The book presents a non-technical review of research and initiatives and a discussion of such opportunities and challenges.
This book features papers focusing on the implementation of new and future technologies, which were presented at the International Conference on New Technologies, Development and Application, held at the Academy of Science and Arts of Bosnia and Herzegovina in Sarajevo on 27th–29th June 2019. It covers a wide range of future technologies and technical disciplines, including complex systems such as Industry 4.0; robotics; mechatronics systems; automation; manufacturing; cyber-physical and autonomous systems; sensors; networks; control, energy, automotive and biological systems; vehicular networking and connected vehicles; effectiveness and logistics systems, smart grids, as well as nonlinear, power, social and economic systems. We are currently experiencing the Fourth Industrial Revolution “Industry 4.0”, and its implementation will improve many aspects of human life in all segments, and lead to changes in business paradigms and production models. Further, new business methods are emerging, transforming production systems, transport, delivery, and consumption, which need to be monitored and implemented by every company involved in the global market.
Distributed Artificial Intelligence (DAI) came to existence as an approach for solving complex learning, planning, and decision-making problems. When we talk about decision making, there may be some meta-heuristic methods where the problem solving may resemble like operation research. But exactly, it is not related completely to management research. The text examines representing and using organizational knowledge in DAI systems, dynamics of computational ecosystems, and communication-free interactions among rational agents. This publication takes a look at conflict-resolution strategies for nonhierarchical distributed agents, constraint-directed negotiation of resource allocations, and plans for multiple agents. Topics included plan verification, generation, and execution, negotiation operators, representation, network management problem, and conflict-resolution paradigms. The manuscript elaborates on negotiating task decomposition and allocation using partial global planning and mechanisms for assessing nonlocal impact of local decisions in distributed planning. The book will attract researchers and practitioners who are working in management and computer science, and industry persons in need of a beginner to advanced understanding of the basic and advanced concepts.
This book constitutes the proceedings of the First International Conference on Intelligent Transport Systems, INTSYS 2107, which was held in Helsinki, Finland, in November 2017. The 30 revised full papers were selected from 47 submissions and are organized in 6 thematic sessions on planning and sustainable transport and smart cities, intelligent rail transport systems, transport modelling and simulation & big data application, ITS safety and security, cooperative ITS and autonomous driving, and intelligent traffic management.