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 model-based 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.
Highlights
With the rapid development of society and economy, the number of vehicles has grown larger and larger
We proposed an improved model-based predictive control method which can simultaneously optimize green time splits according to the predicted traffic demand over a finite horizon and manage queue based on different traffic flow conditions
The detailed descriptions of different traffic signal control methods are introduced as below: (1) Model-based predictive control, whose green time splits for all intersections are optimized according to the measured traffic flow state is showed
Summary
With the rapid development of society and economy, the number of vehicles has grown larger and larger. Michalopoulos et al [15] employed a “bang-bang” control model with restrained queue length to Mathematical Problems in Engineering deal with the problem of optimal timing during the oversaturated period These strategies obtain optimal timing according to historical data rather than real-time data, which is difficult to adapt to the real-time traffic conditions [16]. The simulation results demonstrated that the proposed method can improve significantly the traffic signal control performance For these methods, it is important to predict the traffic demand over the finite horizon accurately. (1) We propose an improved model-based predictive control approach integrating model-based signal control and queue spillover control to obtain an optimal green time allocation scheme and to avoid spillover simultaneously under oversaturated traffic conditions.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
