Integration of Model‐Based Signal Control and Queue Spillover Control for Urban Oversaturated Signalized Intersection

Abstract

An improved model-based predictive control approach integrating model-based signal control and queue spillover control is proposed in this paper, which includes three modules: model-based signal control, queue spillover identification, and spillover control to deal with the problem of traffic congestion for urban oversaturated signalized intersection. The main steps are as follows. First of all, according to the real-time traffic flow data, the green time splits for all intersections will be solved online by the modelbased signal control controller whose optimization model is based on model-predictive control (MPC) strategy. Second, the queue spillover identification module will be used to detect the potential queue spillover. If potential queue spillover is detected, the spillover control module will be activated to prevent vehicles from the upstream link of the link with possible spillover from entering the downstream link to avoid traffic congestion. The experiment is performed on a simulated road network. The results verify that the proposed scheme can significantly decrease the delay which reflects the overall performance of the studied intersection.

Traffic signal coordination control along oversaturated two-way arterials

“…The proposed intersection coordination control method is based on model predictive control, which consists of prediction model, optimization model and optimization algorithm (Xu, Chen & Xu, 2019;Zhou et al, 2017). At the beginning of each cycle, the prediction model will first predict traffic information according to collected real-time number of vehicles and queue length for each link.…”

“…Finally, IGAABC algorithm is applied to solve the optimal green time plans. A detailed description of prediction model, optimization model and IGAABC optimization algorithm has been provided in our previous article (Xu, Chen & Xu, 2019).…”

“…s e+1 i is saturation flow rate which can be given directly. Considering that the traffic demand is not constant, the arrival flow rate of v e ij ,V e+1 jR and V e+1 jG can be predicted by the prediction model (Xu, Chen & Xu, 2019). Suppose that the distance between the intersection E e and the intersection E e+1 is L e+1 .…”

“…The flowchart is shown in Fig. 6, and the details of IGAABC have been given in our previous paper (Xu, Chen & Xu, 2019).…”

“…The upstream direction and downstream direction along oversaturated arterial are set as the same signal group. Deploy the necessary detectors and apply the queue spillover identification method (Xu, Chen & Xu, 2019) to identify potential queue spillover for each section along oversaturated arterial. As shown in Fig.…”