Earticle

초록

영어

Past research has produced various ramp metering approaches. Even so, the results of existing ramp control techniques are unsatisfactory due to the highly nonlinear property of the ramp control system. For improving the ramp metering performance and raising the ramp control accuracy, we propose a mixed approach of fuzzy logic control and proportional plus integral (PI) control for freeway ramp metering. We also employ a genetic algorithm (GA) to optimize the PI parameters in this paper. Furthermore, we apply a nonlinear control technique with a feedback loop to enhance system performance. Firstly, a first-order traffic flow model called hydrodynamic model is established, and the model characteristics are analyzed. Secondly, the control objective of the ramp metering system is defined by the mainline traffic density. Thirdly, a mixed controller of fuzzy logic and genetic PI is designed based upon this hydrodynamic model and in combination with a nonlinear control technique. The membership functions of the fuzzy logic control are triangular or Gaussian curves, and the numbers of fuzzy control rules are nine. Fourthly, optimization procedures of a GA for finding the best PI control parameters are given with details. Finally, the authenticity and effectiveness of the mixed controller are verified with Matlab software R2010a and also by VISSIM microscopic traffic simulation. Simulation results prove that this mixed control approach has better tracking performance and smaller density errors compared with the method of artificial neural networks. This mixed control approach, as well as the nonlinear control technique, provides a new idea for freeway ramp metering.

목차

Abstract
 1. Introduction
 2. Freeway Hydrodynamic Model
 3. Control Objective of the Ramp Metering System
 4. Traffic Density Controller Based on Fuzzy Logic Control and Genetic PI Control
  4.1. Combination Structure and Block Diagram of the Feedback Loop plus the Intelligent Control
  4.2. Basic Principle and Design Process of Fuzzy Logic Control
  4.3. Design of Proportional plus Integral Control
  4.4. Optimization Procedure of the PI Control Parameters with GA
 5. Simulation Results
 6. Result Comparison and Test
  6.1. Results of the Fuzzy Logic Mixed Controller with Gauss Membership Functions
  6.2. Testing Results via VISSIM Microscopic Traffic Simulation
 7. Conclusions
 References

키워드

저자

• Xinrong Liang [ College of Information Engineering, Wuyi University, Jiangmen, China / College of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China ]
• Qi Lu [ College of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China ]
• Jianmin Xu [ College of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605