运动延误下城市交通轨道多站协同客流控制模型研究
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  • 英文篇名:Multi Station Cooperative Passenger Flow Control Model for Urban Traffic Track Under Motion Delay
  • 作者:崔素萍
  • 英文作者:Cui Suping;College of Engineering,Tibet University;
  • 关键词:运动延误 ; 交通轨道 ; 客流量 ; 协同 ; 控制模型
  • 英文关键词:motion delay;;traffic track;;passenger flow;;coordination;;control model
  • 中文刊名:KJTB
  • 英文刊名:Bulletin of Science and Technology
  • 机构:西藏大学工学院;
  • 出版日期:2019-02-28
  • 出版单位:科技通报
  • 年:2019
  • 期:v.35;No.246
  • 语种:中文;
  • 页:KJTB201902039
  • 页数:4
  • CN:02
  • ISSN:33-1079/N
  • 分类号:209-212
摘要
城市化水平提高人们出行需求随之增长,公共交通具有安全、准时等特点,使城市交通客流量显著增长出现拥塞现象。在运动延误条件下,提出基于离散系统线性最优控制理论的城市交通轨道多站协同客流控制模型。以交通路网换乘站内行人交通性质分析为基础,将站台进出客流实行分类,运用离散系统线性最优控制理论,使进站客流量成为控制输入变量,站台现存客流量成为状态变量,建立站内客流量密度最少目标函数,先对高峰时段换乘站内客流进行初步控制。根据阻抗大小运用Dial搜索方法获取符合条件的有效路径,结合Floyd最短路径法将出行OD交通量合理分配至有效路径上,完成多站协同客流控制建模。实验证明,应用所提控制方法可有效减小高峰时期客流量,缓解交通运营压力。
        The urbanization level increases the people's travel demand, and the public transport has the characteristics of safety and punctuality, which makes the traffic congestion of urban traffic increase significantly. Based on discrete linear optimal control theory, a multi station cooperative passenger flow control model for urban rail transit is proposed under the condition of motion delay. Based on the analysis of the pedestrian traffic in the traffic network transfer station, the passenger flow is classified and the discrete system linear optimal control theory is used to make the passenger flow into the control input variable, the existing passenger flow of the platform becomes the state variable, the minimum target function of the passenger flow density in the station is set up, and the peak period is first of the peak time period. The passenger flow in the transfer station is preliminarily controlled. According to the impedance size, the Dial search method is used to obtain the effective path, and the traffic volume of travel OD is allocated to the effective path by the shortest path method of Floyd, and the multi station cooperative passenger flow control modeling is completed. Experiments show that the proposed control method can effectively reduce peak traffic volume and ease traffic operation pressure.
引文
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