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城市轨道交通大小交路开行方案与多站联合限流协同优化研究
引用本文:陈维亚,章雍,陈鑫,王婕妤. 城市轨道交通大小交路开行方案与多站联合限流协同优化研究[J]. 交通运输系统工程与信息, 2019, 19(5): 177-184
作者姓名:陈维亚  章雍  陈鑫  王婕妤
作者单位:中南大学交通运输工程学院,长沙,410075;中南大学交通运输工程学院,长沙,410075;中南大学交通运输工程学院,长沙,410075;中南大学交通运输工程学院,长沙,410075
基金项目:国家自然科学基金/ National Natural Science Foundation of China(61203162);湖南省自然科学基金/ Natural Science Foundation of Hunan Province, China(2018JJ2537);中南大学中央高校基本科研业务经费专项资金/ Fundamental Research Funds for the Central Universities of Central South University (2018zzts505).
摘    要:针对城市轨道交通高峰时段客流量大、客流空间分布不均衡导致的供需能力不匹配和车站大客流组织安全压力大等问题,本文提出了一种大小交路开行方案与多站联合限流相结合的运输组织协同优化方法. 该方法考虑客流安全容量、列车运行时间和大小交路开行等约束,建立了以乘客出行成本、企业运营成本和各站上车比例方差和最小为目标的优化模型,设计嵌套人工蜂群算法求解. 以某市城市轨道交通线路为例验证模型的有效性与适用性,并对小交路列车开行频率和多目标的权重系数进行了敏感性分析. 结果表明,该方法在输送乘客人数相当的情况下,能有效节省企业运营成本,并提高乘客出行公平性,有效缓解大客流车站的客流组织压力.

关 键 词:城市交通  大小交路  联合限流  协同优化  人工蜂群算法
收稿时间:2019-04-23

Collaborative Full-length and Short-turning Plan and Joint Multi-station Control of Passenger Flow in Urban Rail Transit
CHEN Wei-ya,ZHANG Yong,CHEN Xin,WANG Jie-yu. Collaborative Full-length and Short-turning Plan and Joint Multi-station Control of Passenger Flow in Urban Rail Transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(5): 177-184
Authors:CHEN Wei-ya  ZHANG Yong  CHEN Xin  WANG Jie-yu
Affiliation:Traffic and Transportation Engineering School, Central South University, Changsha 410075, China
Abstract:During peak hours, urban rail transit has large passenger flow and uneven distribution of passenger flow in space, which causes the imbalance of supply and demand and the safety pressure of the station passenger flow organization. To alleviate this problem, this paper proposes collaborative full- length and short- turning plan and joint multi- station control of passenger flow transport organization method. We considers the constraints of passenger flow safety capacity, train running time and full-length and short-turning, and the model which goals are minimizing passenger travel cost, operating cost, and the sums of passengers on board ratio variance of each station is established. A nested artificial bee colony algorithm is designed to solve the model. Taking the urban rail transit line of a city as an example to verify the validity and applicability of the model, and the sensitivity analysis of the short- turning frequency and multi- objective weight coefficient is carried out. The results show that the method can save the operating cost of the enterprise and improve the fairness of passenger travel, and relieve the pressure on the passenger flow of the large passenger flow station effectively.
Keywords:urban traffic  full- length and short- turning plan  joint multi- station control of passenger flow  collaborative optimization  artificial bee colony algorithm  
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