个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:计算机科学与技术学院
办公地点:大连理工大学创新园大厦8-A0824
联系方式:18641168567
电子邮箱:gztan@dlut.edu.cn
Real time turning flow estimation based on model predictive control
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论文类型:会议论文
发表时间:2011-08-20
收录刊物:EI、Scopus
卷号:1
页面范围:356-360
摘要:In order to predict the real time turning flow at intersections, which is used for the real-time adaptive traffic signal control, a real time turning flow estimation model based on model predictive control is proposed. The model adopts multiple independent parallel BP neural networks to structure the prediction model in the model predictive control mechanism, which adequately exerts the advantages of rolling optimization, feedback correction, and multi-step prediction. The benefit of this is to improve the prediction accuracy. We utilize the microscopic traffic simulator with mathematical software and proper computational applications for the simulation. The simulation results prove that real time turning flow estimation model based on model predictive control ha s been more effective, compared with the traditional neural network prediction model. ? 2011 IEEE.