멀티 에이전트를 이용한 도로정체에 따른 교통흐름 예측 및 통합제어 I : 시뮬레이션 시스템 개발 및 최적화를 위한 모델링

The Integrated Control Model for the Freeway Corridors based on Multi-Agent Approach I : Simulation System & Modeling for Optimization

  • 조기용 (성균관대학교 기계공학부) ;
  • 배철호 (성균관대학교 기계공학부 대학원) ;
  • 김현준 (성균관대학교 기계공학부 대학원) ;
  • 주열 (미시시피주립대학교 전기 & 컴퓨터공학부) ;
  • 서명원 (성균관대학교 기계공학부)
  • Cho, Ki-Yong (School of Mechanical Engineering, Sungkyunkwan University) ;
  • Bae, Chul-Ho (Graduated School of Mechanical Engineering, Sungkyunkwan University) ;
  • Kim, Hyun-Jun (Graduated School of Mechanical Engineering, Sungkyunkwan University) ;
  • Chu, Yul (School of Electric & Computer Engineering, Mississippi State university) ;
  • Suh, Myung-Won (School of Mechanical Engineering, Sungkyunkwan University)
  • 발행 : 2007.01.01

초록

Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.

키워드

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