An integrated optimization approach for passenger flow control strategy and metro train scheduling considering skip-stop patterns in special situations

被引:13
|
作者
Yuan, Fuya [1 ,2 ]
Sun, Huijun [1 ]
Kang, Liujiang [3 ]
Lv, Ying [3 ]
Yang, Xin [1 ]
Wei, Yun [4 ,5 ]
机构
[1] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing 100044, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Sch Modern Posts, Chongqing 400065, Peoples R China
[3] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol Co, Minist Transport, Beijing 100044, Peoples R China
[4] Beijing Mass Transit Railway Operat Corp LTD, Beijing 100044, Peoples R China
[5] Beijing Key Lab Subway Operat Safety Technol, Beijing 100044, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Integrated optimization; Passenger flow control; Train scheduling; Skip-stop patterns; NETWORK; ROBUST; TIME; OPERATION; DEMAND;
D O I
10.1016/j.apm.2023.01.034
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In many special situations (epidemic, emergencies, large-scale events, etc.) of the metro, it is a considerably real issue on how to control passenger flow density and improve op-erational efficiency synchronously under the control requirements of specific the load fac-tor. This paper aims to propose an integrated optimization approach for jointly researching passenger flow control and train scheduling with skip-stop patterns. Besides, the passenger dynamic demand and train occupancy rate are considered. A mixed integer programming model is formulated to minimize the unused capacity of trains and the total number of waiting passengers at platforms and outside stations. Through the comprehensive analysis of the relationship between passengers and trains, the numerical experiments are imple-mented in Beijing Metro Line 1 to illustrate the validity of the proposed method. Finally, discussion and comparison of the performance of integration optimization strategies with diverse scenarios are given. The results show that, under the optimized combination strat-egy, the average boarding rate of all stations can increase from 88.09% to 94.69% by the proposed approach, the number of waiting behaviors of passengers can be declined by 92.65%, and the average travel time of passengers can be reduced by 7.22%.(c) 2023 Published by Elsevier Inc.
引用
收藏
页码:412 / 436
页数:25
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