站点分类下的城市公共自行车交通需求预测

doi:10.13229/j.cnki.jdxbgxb20191153

摘要/Abstract

摘要：

准确掌握土地利用与公共自行车交通需求关系是调整管控措施和站点运营管理的关键依据，以西安市的公共自行车站点为例，先以多因子指标作为变量运用K-means聚类将站点分为白天目的地站点、夜间目的地站点、白天起源地站点和组合起源/目的地站点；然后针对各类站点属性，分别建立用地、公交线路、地铁出入口、站点中心性为解释变量的非线性回归模型，结果表明：站点区位、外部环境变量和土地利用对不同属性站点具有不同的客流生成率。结果可在城市公共自行车系统运营管理方面提供理论基础建议。

关键词: 交通运输规划与管理, 公共自行车系统, 土地利用, 聚类分析, 非线性回归模型

Abstract:

Accurately understanding the relationship between land use and public bicycle traffic demand is essential for adjusting control measures and station operation management. Taking public bicycle stations in Xi'an as an example， first， the public bicycle stations are divided into daytime destination stations， nighttime destination stations， daytime origin stations and combined origin/destination stations through K-means clustering while treating multi-factor indicators as variables. Then the non-linear regression models of land use， bus lines， subway entrances and exits， and station centrality as explanatory variables for each station attribute separately are established. The results show that station locations， external environment variables， and land use will lead to discrepancy in passenger flow generation rates for stations with different attributes. This study can provide theoretical reference for the operation and management of urban public bicycle systems.

Key words: transportation planning and management, public bicycle system, land use, cluster analysis, nonlinear regression model

中图分类号:

U491.1

朱才华,孙晓黎,李岩. 站点分类下的城市公共自行车交通需求预测[J]. 吉林大学学报(工学版), 2021, 51(2): 531-540.

Cai-hua ZHU,Xiao-li SUN,Yan LI. Forecast of urban public bicycle traffic demand by station classification[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 531-540.

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时间段	相关系数	时间段	相关系数
6∶00~7∶00	0.382	14∶00~15∶00	0.517
7∶00~8∶00	0.697	15∶00~16∶00	0.495
8∶00~9∶00	0.503	16∶00~17∶00	0.356
9∶00~10∶00	0.516	17∶00~18∶00	0.427
10∶00~11∶00	0.410	18∶00~19∶00	0.728
11∶00~12∶00	0.554	19∶00~20∶00	0.630
12∶00~13∶00	0.429	20∶00~21∶00	0.494
13∶00~14∶00	0.394	21∶00~22∶00	0.231

变量编号	变量名称	变量描述
1	早高峰客流量	站点早高峰借出还入总量
2	晚高峰客流量	站点晚高峰借出还入总量
3	站点总桩数	站点设计布局桩数
4	接驳轨道交通	300 m内地铁出入口个数
5	站点用地混合度	车站300 m以内的土地混合熵
6	站点建筑强度	站点300 m建筑容积率
7	接驳公交线路数	100 m之内的公交线路连接数

参数	估计值
参数	聚类1	聚类2	聚类3	聚类4	聚类5	聚类6
拟合优度(r²)	0.786	0.803	0.788	0.794	0.775	0.817
F值	68.698	56.832	61.764	76.397	91.205	49.781
Sig. F	0.011	0.009	0.014	0.016	0.021	0.012
公交线路	10.368	11.114	11.352	12.957	10.133	9.941
地铁出入口	21.092	20.871	24.132	29.618	22.077	20.925
中心性	8.121	8.364	7.683	8.344	7.906	8.307
居住	0.000 196	0.000 419	0.000 287	0.000 924	0.000 246	0.000 271
行政办公	0.001 750	0.001 688	0.000 314	0.000 267	0.002 148	0.001 169
商业金融	0.000 629	0.000 024	0.000 318	0.000 217	0.000 022	0.000 627
文化娱乐	0.000 819	0.000 847	0.001 016	0.000 312	0.000 964	0.000 901
体育	0.000 011	0.000 027	0.000 134	0.000 081	0.000 059	0.000 067
医疗	0.001 170	0.001 021	0.000 127	0.000 049	0.002 619	0.000 874
教育科研	0.000 132	0.001 009	0.000 104	0.000 503	0.000 912	0.000 677
文物古迹	0.000 239	0.000 398	0.000 191	0.000 099	0.000 742	0.001 316
工业	0.000 081	0.000 161	0.000 072	0.000 049	0.000 083	0.000 204
其他	0.000 175	0.000 102	0.000 034	0.000 077	0.000 093	0.000 121