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地理学报    2018, Vol. 73 Issue (12): 2423-2439     DOI: 10.11821/dlxb201812011
  旅游地理 本期目录 | 过刊浏览 | 高级检索 |
轨道站点合理步行可达范围建成环境与轨道通勤的关系研究——以北京市44个轨道站点为例
申犁帆1(),王烨2,张纯3(),姜冬睿4,李赫5
1. 武汉大学城市设计学院,武汉 430072
2. 广州市城市规划勘测设计研究院,广州 510030
3. 北京交通大学建筑与艺术学院,北京 100044
4. 北京城市象限科技有限公司,北京 100055
5. 中国银行国际金融研究所,北京 100818
Relationship between built environment of rational pedestrian catchment areas and URT commuting ridership: Evidence from 44 URT stations in Beijing
SHEN Lifan1(),WANG Ye2,ZHANG Chun3(),JIANG Dongrui4,LI He5
1.School of Urban Design, Wuhan University, Wuhan 430072, China
2. Guangzhou Planning & Design Survey Research Institute, Guangzhou 510030, China;
3. School of Architecture and Design, Beijing Jiaotong University, Beijing 100044, China
4. Beijing Urban Quadrant Technology Co., Ltd, Beijing 100055, China
5. International Finance Institute, Bank of China, Beijing 100818, China
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摘要 

轨道站点步行可达范围内建成环境因素与轨道交通通勤行为之间的关系越来越受到人们的重视。从潜在通勤者的角度出发,划定轨道站点的合理步行可达范围,以北京市44个轨道站点为例,利用大数据方法从“宜出行”程序中提取站点合理步行范围内的相对人口数据,结合2017年9月10个工作日早高峰时段的轨道站点刷卡数据得到该站点的相对乘车率。基于数据的非正态分布特征构建GARCH模型,分析早高峰站点合理步行范围内建成环境因素与站点相对乘车率的关系。结果表明:① 始发轨道站点与站点乘车率存在显著正向关系,而站点所在线路的换乘概率与站点乘车率具有非常明显的负相关性;② 轨道站点的出入口数量与乘车率显著正相关;③ 小区—站点的路径转折数和步行范围内的交叉路口数等可步行性特征对轨道交通通勤行为无显著影响,步行范围的公交车站密度与站点乘车率正相关;④ 合理步行范围内的用地混合度与乘车率存在显著的负相关性;⑤ 合理步行范围内的路网密度以及早高峰拥堵道路比与乘车率之间在不同程度上呈现正向关系;⑥ 共享单车订单数与轨道交通通勤行为之间的关系并不明确;⑦ 相比手机信令数据,“宜出行”定位数据的精度更高,适用于分析微观尺度下的实时人口分布及变化。

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申犁帆
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姜冬睿
李赫
关键词 轨道站点合理步行范围建成环境通勤行为广义自回归条件异方差模型北京市 
Abstract

In recent years, there has been a growing interest in the relationship between built environment factors within station pedestrian catchment areas and urban rail transit (URT) commuting ridership. In this paper, the rational pedestrian catchment areas was studied from the perspective of potential commuters. Based on a case-study of 44 URT stations in Beijing, big data method was adopted to collect point data of population from 'Yichuxing', an internet application. In addition, relative values of relative riding rate were obtained by combining point data and rail transit one-card pass data during peak time within 10 working days in September 2017. In view of the abnormal distribution of data, a GARCH model was established to analyze the interactions between station relative riding rate and built environment factors within rational pedestrian catchment areas. The study results showed that (1) there is a notable positive correlation between URT relative riding rate and initial station, and negative interaction between station relative riding rate and transfer probability of station; (2) there is a strong positive relationship between relative riding rate and exit numbers of station; (3) there are no explicit relationships between conditions of station relative riding rate and walkable factors such as residential-station footpath turn times and cross numbers within rational catchment areas, whereas positive relationship was observed between station relative riding rate and bus stop density within rational pedestrian catchment areas; (4) significant negative correlation can be found between relative riding rate and land use mixture; (5) there are positive correlations among station relative riding rate and density of road network, congested road proportion in morning peak hours in varying degree; (6) there is an ambiguous and intricate relationship between bike-sharing order quantities and URT relative riding rate; (7) compared to cellular signaling data, "Yichuxing" point data showed higher accuracy and applicability in terms of the analysis of demographic distribution and micro-scale changes.

Key wordsurban rail transit station    rational pedestrian catchment areas    built environment    commuting behaviour    GARCH    Beijing
收稿日期: 2017-11-03      出版日期: 2018-12-14
基金资助:国家自然科学基金项目(51678029, 51778039);中国城市轨道交通协会专项研究项目(A17M00080)
引用本文:   
申犁帆, 王烨, 张纯等 . 轨道站点合理步行可达范围建成环境与轨道通勤的关系研究——以北京市44个轨道站点为例[J]. 地理学报, 2018, 73(12): 2423-2439.
SHEN Lifan, WANG Ye, ZHANG Chun et al . Relationship between built environment of rational pedestrian catchment areas and URT commuting ridership: Evidence from 44 URT stations in Beijing[J]. Acta Geographica Sinica, 2018, 73(12): 2423-2439.
链接本文:  
http://www.geog.com.cn/CN/10.11821/dlxb201812011      或      http://www.geog.com.cn/CN/Y2018/V73/I12/2423
Fig. 1  研究范围内轨道站点的分布
所属区 站点名称
海淀区 健德门 巴沟 公主坟 海淀五路居 上地
牡丹园 火器营 莲花桥 花园桥 西二旗
西土城 长春桥 军事博物馆 白石桥南 清华东路西口
知春路 车道沟 白堆子 万寿路 六道口
知春里 慈寿寺 五棵松 大钟寺 北沙滩
苏州街 西钓鱼台 玉泉路 五道口
西城区 车公庄西 积水潭 木樨地 长椿街 达官营
车公庄 鼓楼大街 南礼士路 和平门 广安门内
北海北 阜成门 复兴门 湾子 虎坊桥
Tab. 1  研究范围内的轨道站点
Fig. 2  轨道站点的合理步行范围
Fig. 3  站点合理步行范围内“宜出行”点数据分布图
Fig. 4  地铁万寿路站出入口示意
站点 乘车率 站点 乘车率 站点 乘车率 站点 乘车率 站点 乘车率
健德门 3.420 莲花桥 2.518 海淀五路居 11.378 上地 6.175 鼓楼大街 3.512
巴沟 6.902 知春路 2.138 万寿路 2.910 西二旗 7.675 南礼士路 2.455
牡丹园 3.487 知春里 1.858 五棵松 5.032 六道口 0.972 复兴门 2.564
西土城 2.062 苏州街 1.786 玉泉路 7.725 北沙滩 1.654 和平门 2.796
长春桥 4.151 西钓鱼台 3.607 军事博物馆 2.932 北海北 2.006 达官营 3.173
火器营 4.775 白堆子 1.729 白石桥南 2.234 积水潭 7.494 广安门内 1.744
车道沟 4.773 车公庄西 1.498 清华东路西口 0.991 阜成门 1.947 虎坊桥 0.946
慈寿寺 6.729 车公庄 2.797 大钟寺 2.234 木樨地 2.155 湾子 3.269
公主坟 3.747 花园桥 1.733 五道口 1.282 长椿街 6.280
Tab. 2  样本站点的相对乘车率
变量 定义
ride 轨道站点的相对乘车率。用工作日早高峰时段轨道站点一卡通进站刷卡次数(人次)与前一天夜间时段合理步行范围内标准化处理后的“宜出行”定位点数(个)的比值表示
transfe 轨道站点是否属于换乘站。用虚拟变量表示,其中,1表示该站是换乘站,0表示该站不是换乘站
initial 轨道站点是否属于始发站。用虚拟变量表示,其中,1表示该站是始发站,0表示该站不是始发站
tranpos 轨道线路的换乘率。用相邻3个轨道站点范围内的换乘站数表示(个)
exit 轨道站点的出入口数(个)。经修正后统计得到
turn 合理步行范围内主要居住小区到轨道站点的平均转折次数
cross 合理步行范围内的路口密度。用合理步行范围内路口数(个)与合理步行范围面积(km2)的比值表示
landuse 合理步行范围内的土地利用混合度。利用公式(1)计算得出
busstop 合理步行范围内的公交车站密度。用合理步行范围内公交车站数(个)与合理步行范围面积(km2)的比值表示
strgrid 合理步行范围内的路网密度。用合理步行范围内车行道总长度(m)与合理步行范围面积(km2)的比值表示
trafjam 工作日早高峰时段合理步行范围的道路拥堵程度,用早高峰时段合理步行范围内拥堵路段长度(m)与合理步行范围内车行道路总长度(m)的比值表示。
bike 合理步行范围内的ofo小黄车订单数。用早高峰时段在样本站点200 m半径范围内结束行程的ofo小黄车平均订单数表示
Tab. 3  变量定义
平均值 中位值 最大值 最小值 标准偏差 偏度 峭度 JB检测 或然率 总和 总平方和 样本量
ride 9.85 6.91 28.57 1.79 6.96 1.21 3.53 11.23 0.00 433.34 2085.37 44
transfe 0.20 0.00 1.00 0.00 0.41 1.46 3.15 15.78 0.00 9.00 7.16 44
initial 0.05 0.00 1.00 0.00 0.21 4.36 20.05 672.49 0.00 2.00 1.91 44
tranpos 4.61 5.00 10.00 1.00 2.28 0.00 2.26 1.01 0.60 203.00 224.43 44
exit 3.82 4.00 8.00 1.00 1.32 0.52 4.10 4.25 0.12 168.00 74.55 44
turn 0.65 0.66 2.00 0.00 0.50 0.44 2.56 1.75 0.42 28.74 10.85 44
cross 9.85 6.91 28.57 1.79 6.96 1.21 3.53 11.23 0.00 433.34 2085.37 44
landuse 0.60 0.61 0.83 0.35 0.12 -0.02 2.26 1.00 0.61 26.40 0.61 44
busstop 4.75 4.66 10.94 1.58 2.01 0.91 4.02 8.01 0.02 209.12 173.89 44
strgrid 5.11 4.96 9.06 2.41 1.64 0.58 2.72 2.64 0.27 224.64 115.22 44
trafjam 0.21 0.22 0.41 0.02 0.10 0.06 2.10 1.52 0.47 9.46 0.47 44
bike 68.39 48.65 216.3 1.86 58.64 0.94 3.02 6.48 0.04 3009.31 147878.4 44
Tab. 4  误差正态性检验结果
F检验统计量 4.495 概率(3, 37) 0.009
样本数可绝系数 10.952 卡方概率(3) 0.012
Tab. 5  自回归条件异方差LM检测结果
变量 系数 标准误差 Z检验统计量 概率
ride 2.5123 0.4603 5.4579 0.0000
transfe 0.5220 0.4165 1.2533 0.2101
initial 3.6168 1.3050 2.7716 0.0056
tranpos -0.3532 0.0734 -4.8096 0.0000
exit 0.6308 0.1844 3.4214 0.0006
turn 0.3978 0.4432 0.8975 0.3694
cross 0.0022 0.0414 0.0532 0.9576
landuse -12.6295 1.3388 -9.4335 0.0000
busstop 0.1950 0.0880 2.2156 0.0267
strgrid 0.2797 0.1625 1.7213 0.0852
trafjam 5.7032 1.5667 3.6404 0.0003
bike 0.0021 0.0019 1.0821 0.2792
Tab. 6  建成环境变量对轨道站点乘车率的回归结果
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