This report documents the activities and results of a test of non- intrusive traffic detection technologies. Seventeen devices representing eight different technologies were evaluated in varying environmental and traffic conditions. The following technologies were tested: passive infrared, active infrared, magnetic, radar, doppler microwave, pulse ultrasonic, passive acoustic, and video. Testing was done at both freeway and intersection locations. Emphasis was placed on urban traffic conditions and locations that typify temporary counting locations. The evaluation also focused on the ease of system setup and use, general system reliability, and system flexibility.
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.
Introduction -- Types of equipment -- Technology descriptions -- A process for selecting equipment -- Best practices for equipment use -- Abbreviations used without definitions in TRB publications.
