Forecasting of Real Time Traffic Situation

실시간 교통상황 예보

  • Published : 2000.08.01

Abstract

This paper proposes a new concept of coordinating green this which controls 10 traffic intersection systems. For instance, if we have a baseballs game at 8 pm today, traffic volume toward the baseball game at 8 pm today, traffic volume toward the baseball game will be incr eased 1 hour or 1 hour 30 minutes before the baseball game. at that time we can not pred ict optimal green time Even though there have smart elctrosensitive traffic light system. Therefore, in this paper to improve average vehicle speed and reduce average vehicle waiting time, we created optimal green time using fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time proposed coordinating green time better than electro-sensitive traffic light system. Therefore, in this paper to improvevehicle speed and reduce average vehicle waiting time, we created optiual green time fuzzy rules and neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dosen't consider coordinating green time.

본 논문은 10개 교차로를 연동제어를 할 수 있는 새로운 교통체제 개념을 제안한다. 예를 들어서 오늘 야구경기가 8시경에 열린다고 하면 야구경기가 시작하기 전 1 시간 혹은 1시간 혹은 1시간 30분전에 교통량이 증가할 것이다. 이럴 때에는 아무리 우수한 전자 신호등 시스템도 최적녹색시간을 예측할 수 없다. 그러므로, 본 논문에서는 평균 승용차 대기시간을 최소화하고 평균 주행속도를 향상하기 위해서 퍼지규칙 및 신경망을 이용한다. 모의실험결과 제안된 연동 녹색시간이 연동 녹색 시간을 고려하지 않은 전자신호등보다 평균 승용차 대기시간을 줄일 수 있음을 입증했다.

Keywords

References

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