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 andrnincreased greenhouse emissions. Yet recent advancements in traffic management technologyrnprove to solve the problem of traffic congestion and substantially improve quality of life inrncommunities. This paper illustrates how InSync, an adaptive traffic control system first releasedrnby Rhythm Engineering in 2008, uses artificial intelligence to optimize traffic signals atrnindividual intersections and coordinate signals along arterial corridors to reduce trafficrncongestion. By reviewing the system’s main hardware components, software components andrnoptimization methodologies, this paper explains how InSync overlays existing traffic cabinetsrnand controllers to enable traffic signals to intelligently and immediately adapt to real-time trafficrndemand. To illustrate the versatility and performance of InSync’s adaptive technology, four casernstudies of InSync deployments in different cities, each with a unique traffic control problem, arernreviewed. These case studies and other independent studies demonstrate that InSync reducesrntraffic stops by 60 to 90 percent, travel times by as much as 50 percent, emissions by at least 30rnpercent and fuel consumption by at least 20 percent, resulting in significant and quantifiablerneconomic savings for cities using the InSync system.