United States Department of Transportation
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Edition:Interim Report
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Abstract:The core elements of an adaptive signal control method include a traffic volume prediction model and a signal optimization model. This study proposes an adaptive signal control algorithm to optimize the signal timing for the incoming cycle at an isolated intersection. A cell transmission model (CTM)-based model predicts the traffic volumes for the target intersection by counting the current vehicle numbers in the upstream cells. This model does not make assumptions about the arrival process and the correlation of the flows between consecutive cycles. Through this method, the accuracy of the volume prediction is ensured even under rapidly varying traffic conditions. In addition, the signal optimization problem is modeled as a mixed integer linear program (MILP) based on the Barron-Jensen/Frankowska (B-J/F) solution to the Lighthill-Whitham-Richards (LWR) model. The sequence and the splits of phases can be optimized at the same time according to the current traffic condition. Finally, this study compares the new method to the critical lane flow ratio method, which is a commonly used strategy. It shows that the proposed method can reduce the traffic delay under various traffic congestion degrees for both balanced and unbalanced traffic volumes. The delay reduction percentage increases with decreases of the overall critical volume-to-capacity ratio. The reduction is statistically significant when the overall critical volume-to-capacity ratio is below 0.9, and it can reach 32% when the overall critical volume-to-capacity ratio is equal to 0.347 under unbalanced traffic conditions.
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