基于紧密社会关系的地铁规律结伴乘客出行模式研究  

Metro Regular Companion Passenger Travel Patterns Based on Close Social Relation

作　　者：杨静 饶海洋 张红亮[2,3] 喻言 周浪雅 YANG Jing;RAO Haiyang;ZHANG Hongliang;YU Yan;ZHOU Langya(School of Civil and Transportation Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Academy of Intelligent Railway,Beijing Jiaotong University,Beijing 100044,China;Transportation&Economics Research Institute,China Academy of Railway Sciences Co.,Ltd.,Beijing 100081,China)

机构地区：[1]北京建筑大学土木与交通工程学院,北京100044 [2]北京交通大学交通运输学院,北京100044 [3]北京交通大学智能铁路研究院,北京100044 [4]中国铁道科学研究院集团有限公司运输及经济研究所,北京100081

出　　处：《重庆交通大学学报（自然科学版）》2024年第12期47-54,共8页Journal of Chongqing Jiaotong University(Natural Science)

基　　金：中央高校基本科研业务费专项资金项目(2023JBZX003);中国铁道科学研究院集团有限公司科研项目(2022YJ008);北京市属高等学校高水平科研创新团队建设支持计划项目(BPHR20220109)。

摘　　要：结伴乘客的行为模式是组内各成员交通需求的综合体现,特别是基于紧密社会关系的规律结伴行为,对于交通组织和规划部门了解结伴乘客需求并提供针对性服务、管理至关重要。基于北京市公共交通智能卡数据(smart carddata,SCD)的地铁刷卡数据,通过分析出行过程中的人际距离及结伴行为发生频率,提出了规律结伴乘客的识别规则;为了探究不同类型结伴乘客的出行规律,从时间和空间维度出发,选取首次出发时间均值、末次出发时间均值、首次出发时间变异系数、末次出发时间变异系数、结伴OD重复率作为聚类指标,通过这些指标将结伴乘客出行模式分为3种主要类型,并根据出行特征将其命名为:娱乐早出行结伴模式、娱乐晚归结伴模式和通勤结伴模式;针对不同类型的结伴乘客,提出了个性化的票务政策,这些个性化的票务政策旨在满足不同类型结伴乘客的需求,提高公共交通的吸引力和竞争力。The behavior pattern of companion passengers is a comprehensive embodiment of the transportation needs of each member of the group,especially the regular companion behavior based on close social relations,which is very important for the transportation organization and planning department to understand the needs of companion passengers and provide targeted services and management.Based on the subway card data of smart card data(SCD)of public transportation in Beijing,the identification rules of regular companion passengers were proposed by analyzing the interpersonal distance and the frequency of companion behavior during travel.In order to explore the travel patterns of different types of companion passengers,starting from the dimensions of time and space,the mean value of first departure time,the mean value of last departure time,the coefficient of variation of the first departure time,the coefficient of variation of the last departure time,and the OD repetition rate of the companion passengers were selected as the clustering indicators.Based on these indicators,companion passenger travel patterns were classified into three main types and named according to their travel characteristics:entertainment early travel companion mode,entertainment late return companion mode and commuting companion mode.For different types of companion passengers,the personalized ticketing policies were proposed.These personalized ticketing policies aim to meet the needs of different types of companion passengers and improve the attractiveness and competitiveness of public transport.

关 键 词：交通工程 城市轨道交通 紧密社会关系 规律结伴乘客 乘客出行模式 K-MEANS 

分 类 号：U231[交通运输工程—道路与铁道工程]