Demand Responsive Signal Control Strategy (DRSC) Incorporating Queue Length Information in Real-Time Signal Control
Date of Award
Master of Science (MS)
Civil & Environmental Engineering
Asad J. Khattak
Call Number for Print
Special Collections LD4331.E542 R35 2012
Most of the existing vehicle detection systems, namely inductive loops, video cameras etc. are incapable of measuring the queue lengths at signalized intersections. However, with the advent of modern technology, newer detection methods such as probe vehicles equipped with wireless communications (Connected Vehicles), particularly under the Vehicle Infrastructure Integration [52), and radar detection currently provide this capability [53). This thesis presents a Demand Responsive Signal Control Strategy (termed as DRSC) for an isolated signalized intersection. The control strategy incorporates real-time queue length information (obtained from probe vehicles) into the signal control logic. Demand based maximum green time for each upcoming/new phase is computed using the equation calibrated in this thesis. Use of variable maximum green times from cycle to cycle enables efficient allocation of the intersection capacity when traffic demand fluctuates. The proposed methodology is implemented for a single isolated typical 4 legged intersection in a microscopic traffic simulation environment (VISSIM). To assess the robustness of the proposed method, three demand scenarios are tested. In each scenario, a demand surge is induced at one or more approaches of the intersection.
The performance of the proposed control method (DRSC) is evaluated against an eight phase typical actuated signal control using three strategic measures of effectiveness (MOEs); the average delay, average queue size and the number of stops. The simulation results indicate the potential of the proposed method (DRSC) m improving the intersection performance under varying traffic demand conditions.
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"Demand Responsive Signal Control Strategy (DRSC) Incorporating Queue Length Information in Real-Time Signal Control"
(2012). Master of Science (MS), Thesis, Civil & Environmental Engineering, Old Dominion University, DOI: 10.25777/mgxt-2z06