Collision Avoidance And Automated Traffic Management Sensors

Collision Avoidance and Automated Traffic Management Sensors

ITS Sensors and Architectures for Traffic Management and Connected Vehicles

An intelligent transportation system (ITS) offers considerable opportunities for increasing the safety, efficiency, and predictability of traffic flow and reducing vehicle emissions. Sensors (or detectors) enable the effective gathering of arterial and controlled-access highway information in support of automatic incident detection, active transportation and demand management, traffic-adaptive signal control, and ramp and freeway metering and dispatching of emergency response providers. As traffic flow sensors are integrated with big data sources such as connected and cooperative vehicles, and cell phones and other Bluetooth-enabled devices, more accurate and timely traffic flow information can be obtained. The book examines the roles of traffic management centers that serve cities, counties, and other regions, and the collocation issues that ensue when multiple agencies share the same space. It describes sensor applications and data requirements for several ITS strategies; sensor technologies; sensor installation, initialization, and field-testing procedures; and alternate sources of traffic flow data. The book addresses concerns related to the introduction of automated and connected vehicles, and the benefits that systems engineering and national ITS architectures in the US, Europe, Japan, and elsewhere bring to ITS. Sensor and data fusion benefits to traffic management are described, while the Bayesian and Dempster–Shafer approaches to data fusion are discussed in more detail. ITS Sensors and Architectures for Traffic Management and Connected Vehicles suits the needs of personnel in transportation institutes and highway agencies, and students in undergraduate or graduate transportation engineering courses.

Driving Green Transportation System Through Artificial Intelligence and Automation

This book is designed to help transportation professionals and construction experts to develop and implement successful smart systems, leveraging the current trends, equipment, and advanced technologies to drive the green transportation system development. Artificial intelligence (AI) is a new direction that has opened a revolution in technology and smart applications, and it is also the basis for creating a green environment in the net-zero era. Therefore, machines, devices, self-driving car, and robots controlled by artificial intelligence-based systems are now the model of a smart transportation ecosystem for which all these technologies are referred to as "green" industries. In past years, the idea of making a green environment has been existing and moving on the society 5.0 being as a country strategy, and today, AI technology continues its development on this prototype. Nowadays, AI has begun actions to resemble a person in a real sense, and the idea of human-liked robotics put forward by scientists has started to be realized and will probably complete its development as living machines in the near future. AI has many subsystems and application in various industries, some of which have automation more accurately and are more integrated in modern industries. This book also targets a mixed audience of specialists, analysts, engineers, scholars, researchers, academics, professionals, and students from different communities to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices to resolve the challenging issues associated with the leveraging of AI and Industrial Internet of Things (IIoT) in green transportation ecosystem.