Multiregime Adaptive Signal Control for Congested Urban Roadway Networks

Abstract

A hierarchical adaptive signal control was developed and implemented in New York City to manage congestion in a complex urban roadway environment. Control strategies, including strategically regulating traffic demand and balancing the queue–storage ratio at critical intersections, work in concert to systematically alleviate congestion and improve mobility. The high usage of electronic toll collection tags in this area allows large amounts of per trip travel time data to be collected (nearly 1 million per trip travel time records daily) and used in real time for effective control. Congestion levels are mapped to different control regimes. Various demand-regulating strategies are applied at the peripheral roadways of the target control zone. These strategies proactively employ signal offsets and splits to exert a tapering and rebalancing effect on the traffic. Demand regulation results in a better use of available network storage spaces while preserving the capacity of the target control zone. Inside the target control area, a dynamic queue-balancing strategy is implemented at selected critical intersections to prevent propagation of spillovers with stabilized or diminished queues. The initial implementation covered 110 intersections in the highly congested central business district of midtown Manhattan New York City. Results to date are summarized.