【作者】 马超云；

【导师】 毛保华；

【作者基本信息】 北京交通大学 ， 交通运输规划与管理， 2010， 硕士

【摘要】 城市轨道交通作为城市公共交通的骨干,对于缓解城市道路交通拥堵,构建低碳、节能环保的出行方式,发挥着重要的作用。随着轨道交通的快速发展,轨道交通线路逐渐形成网络,而目前各线路基本独立运营、相互间的协调性不强,给乘客换乘带来不便,网络运营条件下的换乘协调成为研究的一项新课题。本文以网络运营条件下,城市轨道交通模式内不同线路间换乘协调为研究内容,运用概率论和数理统计的方法,分别对同站台换乘和通道换乘条件下的时刻表优化问题进行建模,设计了模型求解的启发式算法。在建模之前,介绍了网络换乘协调的理论方法,研究了通道换乘走行时间的分布规律,以便为建模提供理论方法和数据支持。首先分析了轨道交通网络中的换乘理论,对换乘进行了分类,介绍了国外有关换乘站布局、换乘协调组织等的规划思想和设计理念。然后,对通道换乘走行时间进行了抽样调查,从累积分布函数的角度,运用Weibull函数来描述换乘走行时间的分布,采用极大似然估计法对参数取值进行了估计。在此研究基础上,运用定时换乘的思想和方法,分别对同站台换乘和通道换乘条件下,换乘站的列车时刻表进行了优化设计。同站台换乘协调中,将列车的周期性到达定义为列车到达方波脉冲,运用波的理论来分析列车的运行,建立了方波脉冲同步优化模型,通过调整方波脉冲的相位差,实现列车的同步到达；通道换乘协调中,对换乘等待时间进行了严格界定,以换乘等待时间最小为目标函数,建立了换乘协调优化模型,并设计了模型求解的遗传算法。最后,以北京地铁雍和宫站为例进行了案例研究。研究结果表明,Weibull分布能较好地描述通道换乘走行时间,平峰时段对换乘站列车时刻表的协调优化更有意义,高峰时段不需要进行协调。方波脉冲能形象地描述列车的周期性到达,将列车运行视为波的传播,并用数学语言Fourier级数进行表达,提供了一种新的研究思路和方法。雍和宫站列车时间表经过优化后,单个乘客在研究时段内的平均换乘等待时间较现状减少了70s、减幅达到29.7%,总换乘等待时间减少了54145 s,折合15 h。本文设计的换乘协调模型和遗传算法对换乘站列车时刻表的优化是有效的,具有一定的实际适用性。论文中图24幅,表10个,参考文献51篇。更多还原

【Abstract】 Urban rail transit, as the backbone of urban public transit, plays an important part in relieving traffic jams and shaping low-carbon, energy conservation and environmental protection trip mode. With the rapid development of urban rail transit, transit network is formed from isolated lines; however, the operation of each line is independent and lack of coordination, which makes great inconvenious to passenger transfers. Thus, transfer coordination between different lines under network operation becomes a new research subject.This paper studies the transfer coordination between different lines in urban rail transit under network operation. Using the probility theory and mathematical statistics method, the paper has proposed models for optimizing across-platform transfers and passage transfers respectively. Genetic Algorithm is designed to solve the optimization model. Besides, the network transfer optimization theories and methods have been introduced and transfer walking time in passage analysed to provide tools and data for modeling on transfer coordination.Firstly, the paper analyses transfer theories in rail transit networks, including the planning principles and operation ideas of transfer classification, transfer station layout, transfer coordination from abroad. Meanwhile, sampling survey of transfer walking time in subway passages has been made and Weibull function is used to describe the walking time distribution from the perspective of Cumulative Distribution. Parameter values in Weibull function are derived through maximum likelihood estimation.Secondly, transfer coordination models on across-platform transfers and passage transfers have been proposed to optimize schedules of transfer station. The arrivals of train are considered to be period square pulse, and the train operation is analysed using wave theory. Transfer synchronization is achieved by adjusting phase difference of square pulse to make trains arrive at transfer stations simultaneously under across platform transfers. To the passage transfers, transfer waiting time is strictly defined and used as objective function. The model of minimizing transfer waiting time is formulated and Genetic Algorithm is adopted to solve the problem.Finally, a case study of scheduling optimization in Yonghegong Lama Temple transfer station is carried out using methods proposed by the paper.The results of the paper suggest that Weibull function could well describe transfer walking time distribution in subway passages; timetable coordination in non-peak hours is worthier of optimization than peak hours; square pulse could vividly present the periodical arrivals of trains, the paper provides a new approach for rail scheduling by considering train movement as wave propagation and using mathematics function to express square pulse; case study shows that transfer waiting time per pedestrian has been reduced by 70 seconds (29.7%) and total transfer waiting time 54145 seconds, equivalent to 15 hours during study period after schedule optimization; the models and Genetic Algorithm proposed by the paper is effective to timetable optimization and could be applied to transfer coordination in actual urban rail transit networks.更多还原