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作 者:姚恩建[1,2] 白珂炎 张永生[1,2] 高巍 李俊铖[3] 何建涛 YAO Enjian;BAI Keyan;ZHANG Yongsheng;GAO Wei;LI Junchen;HE Jiantao(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Key Laboratory of Transport Industry of Big Data Application Technolo-gies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China;Guangzhou Metro Group Co.,Ltd.,Guangzhou 510380,China)
机构地区:[1]北京交通大学交通运输学院,北京100044 [2]北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室,北京100044 [3]广州地铁集团有限公司,广州510380
出 处:《北京交通大学学报》2023年第4期12-18,109,共8页JOURNAL OF BEIJING JIAOTONG UNIVERSITY
基 金:国家自然科学基金(52102387,52172312)。
摘 要:针对城轨新线接入站间(Origin-Destination,OD)客流分布预测的问题,提出新线接入条件下面向运营的基于进、出站双重选择的城轨客流OD分布预测方法,实现对进、出站选择的双重考虑.首先,考虑站点土地利用、起终点进出站量、出行时间、换乘次数等因素对城轨乘客出行选择的影响,分别构建基于离散选择理论的进、出站选择模型.其次,融合基于进、出站选择的OD分布预测,建立基于进、出站双重选择的OD分布预测模型.最后,以广州地铁18号线接入既有线网为例进行模型验证.研究结果表明:与既有方法相比,本文所提方法预测精度有较大提升,全网站间客流分布的平均绝对误差降低10%以上、新站间OD量平均绝对误差降低20%以上.Regarding the problem of predicting passenger flow distribution between Origin-Destination(OD)stations of new urban rail lines,this paper proposes a prediction method for the distribution of OD passenger flows in the urban rail transit network with the operation of new lines.The method takes into account both entry and exit station choices.Firstly,the influence of factors such as station land use,entrance and exit station volume,travel time,and transfer times on the travel choices of ur⁃ban rail passengers are considered.Two separate choice models,based on discrete choice theory,are developed for entry and exit station choices,respectively.Secondly,a new OD distribution prediction model is established by integrating entry and exit station choices.Finally,the model is validated using the example of the new line 18 integration into the existing Guangzhou Metro network.The results demonstrate show that compared with the traditional models,the proposed method significantly im⁃proves the prediction accuracy,the average absolute errors of the passenger flow distribution on the network are reduced by more than 10%and average absolute errors in the OD volumes between new stations reduced by 20%.
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