The alternative to a top-down, federally-driven national architecture would have been a strictly open or market-based solution. However, this would have led to development delays as competing products went in different directions, or duplicated each other with slight variations. Instead, we now have national consistency in terms of subsystems, centers, information flows and external interfaces, so ITS in one region can be compatible with another region.
Under the direction of the U.S. DOT, major research initiatives have included:
Integrated Corridor Management (ICM), to better utilize existing corridor capacity, for which funding continues in FY 10
VII, now IntelliDrive, for which funding continues in FY 10
Cooperative Intersection Collision Avoidance Systems (CICAS), for which funding continues in FY 10
Clarus, a weather information network (funding set aside), and
Integrated Vehicle Based Safety Systems (IVBSS), prototype vehicles designed to prevent rear-end, lane change and run-off-road crashes, funding complete.
Adaptive Signals Move Traffic
While public and private interests both inside and outside the Beltway try to direct the development of America’s ITS technologies, intelligent, practical refinements of existing traffic flow techniques – like the evolution of what used to be called “sequential traffic light timing” into “adaptive traffic signals” – offer tremendous value for both agencies and road users.
In past decades, arterial drivers were lucky if they could experience a consecutive sequence of traffic lights that would change to green as they approached. Today, sequential light timing is being fine-tuned using traffic sensors – combined with computer hardware and software – that will time lights according to traffic needs in real time.
“Classical and centralized traffic control systems are becoming obsolete and are unable to meet growing demands,” says the Federal Highway Administration in its flyer, Adaptive Control Software. “In response, researchers at FHWA’s Turner-Fairbank Highway Research Center began a 10-year research effort in 1992 to develop Adaptive Control Software (ACS).”
The goal of this effort was to refine traffic control systems that operate in real time, adjusting signal timing to accommodate changing traffic patterns as they unfold.
“Unlike their predecessors, these adaptive systems are not based on a fixed cycle length; they can adjust the split, offset, cycle lengths, and phase order of the control signal,” FHWA says. “ACS uses sensors to interpret characteristics of traffic approaching a traffic signal and, using mathematical and predictive algorithms, adapts the signal timings accordingly, optimizing their performance.”
Adaptive signal control is so appealing that on May 22, at the American Association of State Highway and Transportation Officials (AASHTO) spring meeting in Natchez, Miss., Federal Highway Administrator Victor Mendez announced that adaptive signal control technology would be one of several innovative technologies selected for accelerated deployment under his 2010 Every Day Counts initiative.
Other technologies selected were warm mix asphalt, geosynthetic reinforced soil integrated bridge systems, and prefabricated bridge elements and systems.
FHWA will host a series of strategic regional summits this fall to promote the deployment efforts, and to more broadly engage stakeholders who will be involved in mainstreaming the technologies.
New York City is developing a new integrated adaptive signal control decision support system, and is implementing it on two New York City arterials. In their 2010 Transportation Research Board paper Integrated Adaptive Traffic Signal Control with Real-Time Decision Support, authors Xin, Chang, Bertoli and Talas describe a new integrated adaptive signal control decision support system for use in the Big Apple.
Featuring mixed control objectives for both under- and over-saturated traffic, the system integrates a just-in-time “microscopic” traffic simulation framework, enabling the operator to supervise, review, and interact with signal operations in real time by verifying algorithm-optimized strategies against other alternatives.
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