摘要
时刻表优化技术是城市轨道交通运营管理所涉及的一项关键技术,其实施好坏直接影响到城市轨道交通运营的各个环节。针对当前实际运营过程中,列车时刻表的优化调整显著受制于断面客流预估精度的现状,借助城市轨道交通AFC(自动售检票)系统采集的乘客交易信息,提出了一种基于客流信息的城市轨道交通时刻表优化技术框架,并对其核心模块功能实现的关键技术环节进行了阐述,探讨了基于客流特性参数的发车模型。
Timetable optimization technology is a key tech- nology in urban rail transit operation and management, its implementation has direct impact on all aspects of rail tran- sit operation. In the process of actual operation, optimiza- tion adjustment of train timetable is significantly limited by accurate prediction of the section passenger flow. With the collected passenger transaction information from urban rail transit AFC system, a technique application framework for optimization of rail transit timetable based on flow infor- mation is proposed, in which the core modules and function realization are discussed based on passenger flow in detail. Various departure models parameters are discussed.
出处
《城市轨道交通研究》
北大核心
2016年第9期61-65,共5页
Urban Mass Transit
基金
交通运输部建设科技项目(2015318J33080)
江苏省科技厅产学研联合创新资金项目(BY2012197)
南京地铁专项科技项目(8550140042)
关键词
城市轨道交通
时刻表优化
有序样本聚类
混合遗传算法
urban rail transit
time table optimization
clustering of ordinal samples
hybrid genetic algorithm