Every year, traffic congestion costs American motorists $166 billion in lost time, wasted fuel and increased greenhouse emissions. Expenses related to traffic accidents add another $242 billion to the negative impact of traffic. Traffic congestion is so pervasive that most motorists and transportation engineers consider it a necessary evil. In reality, recent advancements in traffic management technology prove to solve the problem of traffic congestion and substantially improve quality of life in communities.
This paper illustrates how In|Sync, an adaptive traffic control system first released by Rhythm Engineering in 2008, uses artificial intelligence to optimize traffic signals at individual intersections and coordinate signals along arterial corridors to reduce traffic congestion. By reviewing the system’s main hardware and software components, its optimization methodologies and available add-on modules, this paper explains how In|Sync overlays existing traffic cabinets and controllers to enable traffic signals to intelligently and immediately adapt to real-time traffic demand. To illustrate the versatility and performance of In|Sync’s adaptive technology, three case studies of In|Sync deployments in different cities, each with a unique traffic control problem, are reviewed. These case studies reveal how In|Sync’s adaptive technology works in real-world scenarios to intelligently improve traffic flow, thus improving safety and travel time for motorists while also decreasing wasted fuel and harmful emissions.
These case studies and other independent studies demonstrate that on average In|Sync reduces traffic stops by 60 percent, travel times by 24 percent, emissions by 23 percent and fuel consumption by at least 17 percent, resulting in significant and quantifiable economic savings for cities using the In|Sync system.