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This handbook, which was developed in recognition of the need for the compilation and dissemination of information on advanced traffic control systems, presents the basic principles for the planning, design, and implementation of such systems for urban streets and freeways. The presentation concept and organization of this handbook is developed from the viewpoint of systems engineering. Traffic control studies are described, and traffic control and surveillance concepts are reviewed. Hardware components are outlined, and computer concepts, and communication concepts are stated. Local and central controllers are described, as well as display, television and driver information systems. Available systems technology and candidate system definition, evaluation and implementation are also covered. The management of traffic control systems is discussed.
TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 403: Adaptive Traffic Control Systems: Domestic and Foreign State of Practice explores the state of practice of adaptive traffic control systems (ATCSs), also known as real-time traffic control systems, which adjust, in real time, signal timings based on traffic conditions, demand, and system capacity --
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.
The purpose of this project is to deploy and evaluate the effectiveness of the future Utah Department of Transportation (UDOT) Adaptive Traffic Control System (ATCS) on an arterial street network in Park City, Utah that experiences both everyday and unpredictable changes in traffic flow.
This book constitutes selected revised and extended papers from the 10th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production, HPCST 2020, Barnaul, Russia, in May 2020. Due to the COVID-19 pancemic the conference was partly held in virtual mode. The 14 full papers presented in this volume were thoroughly reviewed and selected form 51 submissions. The papers are organized in topical sections on hardware for high-performance computing and its applications; information technologies and computer simulation of physical phenomena.
With over 300,000 traffic signals in the United States, it is important to everyone that those traffic signals operate optimally. Unfortunately, according to the Institute of Transportation Engineers over 75% of traffic signal control systems are in need of retiming or upgrade. Agencies and practitioners responsible for these signals face significant budgeting and procedural challenges to maintain and upgrade their systems. Transportation professionals have traditionally lacked accessible and effective tools to identify when and where the greatest benefits may be generated through retiming and system feature selection. They have also lacked methods and tools to identify, select and defend choices of new traffic signal control systems. This is especially true for adaptive traffic signal control systems which are generally more expensive and whose adaptive algorithms are proprietary, invalidating many traditional analysis methods. To address these challenges, a new theoretical framework including queuing and traffic signal control models has been developed in this study to predict the impacts of signal control technology on a given corridor. This framework has been implemented in the STAR Lab Toolkit for Analysis of Traffic and Intersection Control Systems (STATICS) that uses an underlying queuing model interacting with simulated traffic signal control logic to develop traffic measures of effectiveness under different traffic signal control strategies and settings. The STATICS toolkit has been employed by the Oregon Department of Transportation and several other transportation agencies to analyze their corridors and select advanced traffic signal control systems. Furthermore, a new cost-effective adaptive traffic signal control system called the Swarm-Intelligence Based Adaptive Signal System (SIBASS) is proposed to address situations where optimum optimization strategies change with traffic conditions. Compared to the existing adaptive signal control systems, SIBASS carries an important advantage that makes it robust under communication difficulties. It operates at the individual intersection level in a flat hierarchy that does not use a central controller. Instead, each intersection self-assigns a role based on current traffic conditions and the current roles of neighboring intersections. Each role uses different optimization goals, allowing SIBASS to change intersection optimization criteria based on the current role chosen by that intersection. By designing cooperative features into SIBASS it is possible to create corridor coordination and optimization. This is accomplished using the characteristics of the swarm rather than external imposition to create order. SIBASS is evaluated via simulation under varied traffic conditions. SIBASS consistently outperformed the existing systems tested in this study. On average, SIBASS reduced system average per vehicle delay by approximately 3.5 seconds and system average queue lengths by 20 feet in the tested scenarios. New approaches to tailoring traffic signal control optimization strategies to current traffic conditions and desired operational goals are enabled by SIBASS. Combined, STATICS and SIBASS offer a solid basis upon which to build future tools and methods to analyze traffic signal control systems. Future STATICS analytical modules may include estimating environmental performance and costs as well as improvements to pedestrian modeling and mobility analysis. Environmental and pedestrian considerations also present opportunities for improvement of SIBASS. New optimization roles can be created for SIBASS to address environmental and pedestrian optimization issues.
In a world dependent on digital technologies, business corporations continually try to stay ahead of their competitors by adopting the most updated technology into their business processes. Many companies are adopting digital transformation models, data analytics, big data, data empowerment, and data sharing as key strategies and as service disruptors for information delivery and record management. Higher education institutions have adopted digital service innovation as a core to driving their business processes. Such services are key to ensuring efficiency and improving organizational performance. Digital Transformation and Innovative Services for Business and Learning is a collection of innovative research on the latest digital services and their role in supporting the digital transformation of businesses and education. While highlighting topics including brand equality, digital banking, and generational workforce, this book is ideally designed for managers, executives, IT consultants, industry professionals, academicians, researchers, and students.