This study (1) develops a stochastic traffic delay model based on busy period analysis in queueing theory; (2) proposes a traffic optimization model based on the stochastic traffic delay model; (3) proposes a rolling horizon scheme to update signal timing on a phase-phase base; and (4) demonstrates the efficiency of the proposed model through case studies. To accomplish these objectives, the authors have undertaken several tasks. First, based on busy period analysis, the authors propose stochastic traffic delay models for both the currently served phase (green phase) and the currently idle phase (red phase). The authors derive and then aggregate the traffic delays in all the subperiods within a signal cycle. Second, the authors derive a signal optimization model to minimize the average delay per vehicle in the current cycle. Third, the stochastic traffic delay model uses a rolling horizon scheme to adjust the signal timing in time to make full use of the available information, i.e., queue lengths. Fourth, the authors executed simulations to demonstrate the effectiveness of the proposed framework. The simulations show that compared to the Webster’s formula and another proposed adaptive signal control method, the proposed model can reduce traffic delay significantly.
The core elements of an adaptive signal control method include a traffic volume prediction model and a signal optimization model. This study proposes ...
On April 20, 2005, the first National Traffic Signal Report Card was issued by a coalition of leading transportation organizations. This evaluation of...
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