INSYNC ADAPTIVE TRAFFIC SIGNAL TECHNOLOGY: REAL-TIME ARTIFICIAL INTELLIGENCE DELIVERING REAL-WORLD RESULTS

摘要

Every year, traffic congestion costs American motorists $115 billion in lost time, wasted fuel and increased greenhouse emissions. Yet 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 InSync, 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 components, software components and optimization methodologies, this paper explains how InSync 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 InSync's adaptive technology, four case studies of InSync deployments in different cities, each with a unique traffic control problem, are reviewed. These case studies and other independent studies demonstrate that InSync reduces traffic stops by 60 to 90 percent, travel times by as much as 50 percent, emissions by at least 30 percent and fuel consumption by at least 20 percent, resulting in significant and quantifiable economic savings for cities using the InSync system.