01698315

Component

Adaptive signal control is a favorable way to reduce the congestion and improve the mobility of urban traffic networks. This paper proposes an adaptive signal control algorithm to optimize the signal timing for the incoming cycle at an isolated intersection. Traffic volume prediction and signal optimization are two crucial components of adaptive control methods. A 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 a 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 paper compares the new method to the critical lane flow ratio method which is a commonly used strategy. The total delay per vehicle resulting from the new method is reduced under degrees of traffic congestion ranging from low to high.

This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.

19-05850

English

0000-0001-5585-6576

10p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Adaptive control; Linear programming; Mixed integer programming; Optimization; Signalization; Traffic signal timing

Cell transmission model

Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2019 Paper #19-05850

TRIS, TRB, ATRI

Dec 7 2018 9:52AM