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轨道交通换乘常规公交平均候车时间模型
引用本文:郭淑霞,陈旭梅,于雷,胡东方.轨道交通换乘常规公交平均候车时间模型[J].交通运输系统工程与信息,2010,10(2):143.
作者姓名:郭淑霞  陈旭梅  于雷  胡东方
作者单位:1.北京交通大学 交通运输学院,城市交通复杂系统理论与技术教育部重点实验室,北京 100044;2.美国德克萨斯南方大学 交通系,休斯顿 77004
基金项目:国家高技术研究发展计划(863计划)(2008AA11Z202)
摘    要:乘客平均候车时间建模在公交网络协调优化研究、公共交通效益分析等诸多研究领域起着至关重要的作用. 本文首先将轨道换乘常规公交的客流分为固定客流和随机客流,并进行客流到站时间分布曲线拟合,结果表明固定客流到站时间的对数正态分布拟合效果最好,而随机客流到站时间的伽马分布拟合效果最好;在此研究的基础上,建立了基于客流分类的换乘客流晚高峰平均候车时间模型;最后,对北京市13号线龙泽站519路公交线路进行了模型应用,以检验模型的准确性. 检验结果表明:模型能够准确地估计晚高峰换乘乘客的平均候车时间,相对误差在2.05%以内.

关 键 词:城市交通  公共交通  固定客流  随机客流  到站时间分布  平均候车时间  
收稿时间:2009-07-03

Average Waiting Time Model for Transfer from Rail Transit to Buses
GUO Shu-xia,CHEN Xu-mei,YU Lei,HU Dong-fang.Average Waiting Time Model for Transfer from Rail Transit to Buses[J].Transportation Systems Engineering and Information,2010,10(2):143.
Authors:GUO Shu-xia  CHEN Xu-mei  YU Lei  HU Dong-fang
Institution:1.MOE Key Laboratory for Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University,Beijing 100044, China; 2.Department of Transportation Studies, Texas Southern University, Houston, Texas 77004
Abstract:The modeling of average waiting time for passengers has an important role in several fields of studies, such as the public transport network coordination optimization, the benefit analysis of the public transportation system, and so on. This paper first categorizes passengers transferring from rail transit to buses into two groups, namely, scheduled passengers and random passengers, and conducts the curve-fitting for the arrival time distribution accordingly. It is shown that the lognormal distribution has the best fitting performance for scheduled passengers, and the gamma distribution has the best performance for random passengers. Then, it develops a peak-hour average waiting time model for transferring passengers based on the passenger classification. Finally, it applies the proposed model to the bus line 519 at Longze station of Beijing to examine the accuracy of the model. The examination results demonstrate that the developed model can accurately estimate the peak-hour average waiting time of transferring passengers with a relative error less than 2.05%.
Keywords:urban traffic  public transportation  scheduled passenger  random passenger  arrival rate distribution  average waiting time  
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