Intelligent traffic volume variation control with supervised multi-model traffic signal adaptive predictive control
监督交通量变化的多模型预测自适应交通信号灯控制

A major issue in traffic control systems is the high level of uncertainty due to traffic volume variation in the dynamics of vehicular queue and signal timings. An approach is proposed to deal with the problem based on the supervised multi-model signal adaptive predictive control (SMM-SAPC). According to the characteristics in traffic flow, such as nominal period, peak period and a super flow period, a supervised multi-model approach for modeling the dynamic traffic flow is proposed. By incorporating the traffic modeling method within MPC with control traffic signal systems, a novel intelligent traffic control is implemented. Corresponding response will be made for different traffic conditions; an adaptive signal control for intersection in a main road can be implemented. The presented simulations are indicative for the reasonable traffic time and reduction in delay time and stop time that can be achieved by the proposed method.