Freeway Ramp Controllers Optimized by Ant Colony Algorithm

Yang Fang Lan; Xin Rong Liang; Chao Jun Dong

doi:10.4028/www.scientific.net/AMM.361-363.2214

Paper Titles

Improved Floyd Route Mending Algorithm Based on Dynamic Travel Time Applied to the Estimation of Floating Car Origin-Destination Data
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The Analysis of Transfer Information Demands of Public Transports
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Research on Evaluation Method for the Service Quality of Public Transport Based on Time Reliability Degree
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Research on Public Bicycle Traffic Mode Choice Based on Disaggregate Model
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Freeway Ramp Controllers Optimized by Ant Colony Algorithm
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Application of PLC in the Expressway Intelligent Traffic Control System
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An Experimental Analysis of Drivers Attitudes towards In-Vehicle Warning System at Stop Sign Controlled Intersection
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Vehicle Detection and Counting in Traffic Video Based on OpenCV
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Creation and Application of Highway Network Spatial Database
p.2236

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 361-363Freeway Ramp Controllers Optimized by Ant Colony...

Freeway Ramp Controllers Optimized by Ant Colony Algorithm

Abstract:

A proportional plus integral (PI) control method based on ant colony optimization (ACO) is proposed to regulate the number of vehicles entering freeway entrance points. First, a macroscopic traffic flow model is established. Then the basic principles of an ant colony algorithm are formulated and the steps of ACO algorithm in optimizing the PI parameters are given. In conjunction with nonlinear feedback theory, on-ramp PI controllers optimized by the ant colony algorithm are designed. Finally, the control method is simulated in MATLAB software. Simulation results show that the ACO based ramp metering controllers are of good performance. This control method can eliminate traffic jams, maintain traffic flow stability, and make vehicles travel more efficiently and safely.