DocumentCode
622569
Title
An extended model predictive control approach to coordinated ramp metering
Author
Linglong Hu ; Weili Sun ; Hui Wang
Author_Institution
State Key Lab. of Ind. Control, Zhejiang Univ., Hangzhou, China
fYear
2013
fDate
12-14 June 2013
Firstpage
681
Lastpage
686
Abstract
Ramp metering is the most powerful tool to reduce congestion in freeway management. The problem of designing an on-line coordinated ramp metering strategy is considered in this paper. First, the prevalent model predictive control (MPC) structure is used to formulate the problem with a second-order macroscopic traffic flow prediction model. To reduce the computational effort to match the request of on-line application, the original MPC is then extended with a controller positioning procedure. Not all but only the necessary ramps are selected as controllers by investigating the partial derivation of the cost criterion with respect to each ramp metering rate. Finally, a gradient-based numerical solving algorithm is introduced and the overall method is validated in a hypothetic network. Applying the proposed method, the performance of the freeway network improves as much as 13.4% compared with no-control case. In comparison with the original MPC method, the extended MPC method saves 32.3% computation time while barely degrades the control effectiveness.
Keywords
gradient methods; position control; predictive control; road traffic control; MPC structure; controller positioning procedure; extended model predictive control; freeway management; freeway network; gradient-based numerical solving algorithm; online coordinated ramp metering; second-order macroscopic traffic flow prediction model; Optimal control; Optimization; Predictive control; Predictive models; Traffic control; Trajectory; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation (ICCA), 2013 10th IEEE International Conference on
Conference_Location
Hangzhou
ISSN
1948-3449
Print_ISBN
978-1-4673-4707-5
Type
conf
DOI
10.1109/ICCA.2013.6564996
Filename
6564996
Link To Document