公交线路资源配置与客流状况协调性综合评价方法

马嘉欣; 陈旭梅; 柯靖宇; 彭飞

doi:10.3963/j.jssn.1674-4861.2021.03.015

公交线路资源配置与客流状况协调性综合评价方法

doi: 10.3963/j.jssn.1674-4861.2021.03.015

1.
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
2.
南京市城市与交通规划设计研究院股份有限公司南京210008

基金项目:

国家自然科学基金项目 71871013

北京市科技计划项目 Z191100002519006

详细信息

作者简介:
马嘉欣（1997—），博士研究生.研究方向：常规公交运营优化及评价.E-mail：mjx4363@163.com

通讯作者:
陈旭梅（1974—），博士，教授.研究方向：城市公共交通.E-mail：xmchen@bjtu.edu.cn

中图分类号: U491
计量
- 文章访问数: 326
- HTML全文浏览量: 183
- PDF下载量: 16
- 被引次数: 0
出版历程
- 收稿日期: 2020-05-25

A Comprehensive Evaluation Method for Coordinating Resource Allocations and Passenger Flow of Bus Lines

MA Jiaxin^1
,,
CHEN Xumei^{1
, ,},
KE Jingyu²,
PENG Fei¹

1.
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport of Ministry of Transport, Beijing Jiaotong University, Beijing 100044, China
2.
Nanjing Institute of City & Transport Planning Co., Ltd, Nanjing 210008, China

摘要

摘要: 由于常规公交线路资源配置存在不平衡、不充分等问题，量化评价公交线路资源配置与客流状况协调发展程度成为科学优化城市公交线网布局的重要前提。考虑公交线路资源配置与客流状况协调性特征构建指标体系，针对传统DEA方法中指标及其影响效应的确定存在较为主观、难以区分有效决策单元等劣势，以结构方程模型为依托筛选有效指标并确定其影响效应。在此基础上，应用基于理想点的改进DEA模型获得二者间协调性差异化排序，研究了公交线路资源配置与客流状况协调性综合评价方法，并以北京市海淀区65条公交线路数据进行案例分析。结果表明，平均站点间距指标对二者协调性影响最大，影响效应达0.901。所提出的方法能有效区分应用传统DEA方法难以排序的5条线路，且其评价结果与线路等级及实际运营情况相符，具有良好的应用可行性。
- 城市交通 /
- 公交线路 /
- 资源配置与客流状况协调性 /
- 结构方程模型 /
- 数据包络分析法
Abstract: Due to the imbalanced and inadequate resource allocations of bus lines, the quantitative coordination evaluation of the resource allocations and passenger flow of bus lines are essential for the optimized layout of the urban public transport network.The indicator system is developed by considering the characteristics of the coordination between the resource allocations and passenger flow.Because of the disadvantages of the traditional DEA method, such as the groundless selection of indicators, the subjective determination of their influence effects, and the difficulty in distinguishing effective decision-making units, the structural equation model is introduced as a basis for selecting effective indicators and identifying the rank of the influencing effects.Further, the differentiated coordination ranking is obtained based on the improved DEA model where the ideal point is introduced.Therefore, the work proposes a comprehensive evaluation method of the coordination between the resource allocations and passenger flow conditions.Finally, a case study is conducted with data from 65 bus lines in Haidian District, Beijing.The results show that the indicator of the average stop spacing has the most significant impact on the coordination of resource allocations and passenger flow, with an effect of 0.901.The five bus lines that are difficult to rank with the traditional DEA method are distinguished based on the proposed method.Also, the evaluation results consistent with the design and operation of bus lines show the good application of the proposed model.
- urban traffic /
- bus lines /
- coordination of resource allocation and passenger flow /
- structural equation model /
- data-envelopment analysis

HTML全文

图 1 评价方法思路

Figure 1. Approach of the evaluation method

下载: 全尺寸图片幻灯片

图 2 PLS路径模型计算结果

Figure 2. Estimation of the PLS-path model

下载: 全尺寸图片幻灯片

图 3 评价结果

Figure 3. Evaluation results

下载: 全尺寸图片幻灯片

表 1 指标体系

Table 1. Indicator system

一级指标	二级指标
η₁基本布设	x₁₁线路长度/km
	x₁₂平均站点间距/km
	x₁₃非直线系数
	x₁₄换乘站点比例%
η₂运营状况	x₂₁发车间隔/min
	x₂₂车辆定员/人
	x₂₃平均运送速度/（km/h）
η₃客流状况	x₃₁日客运总量/（人·次）
	x₃₂日客运周转量/（人·km）
	x₃₃平均满载率/%

下载: 导出CSV

表 2 效度检验

Table 2. Validity test of the proposed model

模型类别	检验指标	显变量/变量	取值
构成型测量模型	VIF	线路长度	1.092
		平均站点间距	1.291
		非直线系数	1.205
		换乘站点比例	1.182
		发车间隔	1.427
		车辆定员	1.108
		平均运送速度	1.418
反映型测量模型	CR	客流状况	0.764
	AVE	客流状况	0.525
	Cronbach's α	客流状况	0.756
结构模型	R²	运营状况	0.548
结构模型	R²	客流状况	0.493

下载: 导出CSV

表 3 参数显著性检验

Table 3. Significance test of parameters

模型类别	模型类别显变量	参数	T统计量
构成型	线路长度	0.570	1.964
	平均站点间距	0.850	6.388
	非直线系数	-0.527	3.368
	换乘站点比例	-0.298	2.869
	发车间隔	0.556	1.996
	车辆定员	0.379	2.913
	平均运送速度	0.955	10.166
反映型	日客运总量	0.800	3.000
	日客运周转量	0.557	2.807
	平均满载率	0.790	1.997

下载: 导出CSV

表 4 路径系数显著性检验

Table 4. Significance test of path coefficient

影响路径	路径系数	T统计量
基本布设→运营状况	0.740	11.328
运营状况→客流状况	0.398	2.632
基本布设→客流状况	0.765	2.796

下载: 导出CSV

表 5 各指标影响效应值

Table 5. Effectiveness of the factors

潜变量	显变量	直接效应	间接效应	总效应
	线路长度	0.436	0.168	0.604
基本	平均站点间距	0.650	0.250	0.901
布设	非直线系数	0.403	0.155	0.558
	换乘站点比例	0.228	0.088	0.316
运营	发车间隔	0.221		0.221
	车辆定员	0.151		0.151
状况	平均运送速度	0.380		0.380
客流	日客运总量			0.800
	日客运周转量			0.557
状况	平均满载率			0.790

下载: 导出CSV

表 6 理想DMU指标值

Table 6. Indicator values of the ideal DMU

投人指标	理想DMU指标值	产出指标	理想DMU指标值
线路长度/km	9	日客运总量/人次	20 079
平均站点间距/km	0	日客运周转量（人，km)	44 135
非直线系数	1.36	平均满载率%	100
换乘站点比例%	26.11
发车间隔/mm	0
车辆定员/人	90
平均运送速度（km/h)	12.2

下载: 导出CSV

参考文献(20)

[1]	中国产业调研网. 2020—2026年中国城市公交行业现状分析与发展前景预测报告[R/OL]. (2019-10-29)[2020-02-11]. http://www.cir.cn/R_JiaoTongYunShu/56/ChengShiGongJiaoShiChangYuCeBaoGao.html. China Industry Research. 2020-2026 China urban public transport industry status analysis and development prospect forecast report[R/OL]. (2019-10-29)[2020-02-11]. http://www.cir.cn/R_JiaoTongYunShu/56/ChengShiGongJiaoShiChangYuCeBaoGao.html(. inChinese).
[2]	吴瑶, 陆建, 邱红桐, 等. 基于TOPSIS模型城市常规公共交通适应性评价[J]. 交通信息与安全, 2014, 32(6): 153-158+165. doi: 10.3963/j.issn.1674-4861.2014.06.025 WU Yao, LU Jian, QIU Xintong, et al. Evaluation of adaptability of urban public transit based on TOPSIS model[J]. Journal of Transport Information and Safety, 2014, 32(6): 153-158+165. (in Chinese). doi: 10.3963/j.issn.1674-4861.2014.06.025
[3]	玛依拉·艾则孜, 林强, 姚志刚. 基于DEA方法的城市公交与经济社会发展协调性研究[J]. 公路交通科技, 2017, 34(9): 130-137. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201709019.htm MAYILA Aizezi, LIN Qiang, YAO Zhigang. Study on coordination between urban public transport and economic and social development based on DEA method[J]. Journal of Highway and Transportation Research and Development, 2017, 34(9): 130-137. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201709019.htm
[4]	ERICK G, CAMILO C, PAAVO M, et al. Urban form, transit supply, and travel behavior in Latin America: Evidence from Mexico's 100 largest urban areas[J]. Transport Policy, 2018(69): 98-105.
[5]	朱丽, 陈峻, 何鹏. 基于主成分分析的城市空间形态与公交发展协调性研究[J]. 南京理工大学学报, 2019, 43(3): 353-362. https://www.cnki.com.cn/Article/CJFDTOTAL-NJLG201903016.htm ZHU Li, CHEN Jun, HE Peng. Coordination between urban spatial form and public transport development based on principal component analysis[J]. Journal of Nanjing University of Science and Technology, 2019, 43(3): 353-362. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-NJLG201903016.htm
[6]	ZHANG Yingqun, SONG Rui, ROB N, et al. Identifying urban structure based on transit-oriented development[J]. Sustainability, 2019, 11(24): 1-21.
[7]	谢天. 城市轨道交通与公交换乘协调评价[J]. 铁道运输与经济, 2017, 39(增刊2): 119-126. https://www.cnki.com.cn/Article/CJFDTOTAL-TDYS2017S2021.htm XIE Tian. An evaluation on the coordination of the transfer between urban rail transit and bus[J]. Railway Transport and Economy, 2017, 39(S2): 119-126. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TDYS2017S2021.htm
[8]	DOU X, GONG X, GUO X, et al. Coordination of feeder bus schedule with train service at integrated transport hubs[J]. Journal of the Transportation Research Board, 2017(2648): 103-110. http://www.researchgate.net/publication/321739771_Coordination_of_Feeder_Bus_Schedule_with_Train_Service_at_Integrated_Transport_Hubs
[9]	冯树民, 申翔浩. 公交线路资源配置与高峰客流协调评价研究[J]. 交通运输系统工程与信息, 2015, 15(4): 129-133. doi: 10.3969/j.issn.1009-6744.2015.04.020 FENG Shumin, SHEN Xianghao. Evaluation of coordination between bus lines resource allocation and peak passenger flow[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(4): 129-133. (in Chinese). doi: 10.3969/j.issn.1009-6744.2015.04.020
[10]	刘新民, 鲁晓燕, 孙秋霞. 公交线路资源配置与服务质量协调性评价[J]. 城市问题, 2017(9): 80-84. https://www.cnki.com.cn/Article/CJFDTOTAL-CSWT201709011.htm LIU Xinmin, LU Xiaoyan, SUN Qiuxia. Evaluation of the coordination of bus lines resource allocation and service quality[J]. Urban Problems, 2017(9): 80-84. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CSWT201709011.htm
[11]	PITAM S, KUMAR S A, PRIYAMVADA S, et al. Multimodal data modeling for efficiency assessment of social priority based urban bus route transportation system using GIS and data envelopment analysis[J]. Multimedia Tools and Applications, 2019(78): 23897-23915.
[12]	HAHN J, KIM H, KHO S. A DEA approach for evaluating the efficiency of exclusive bus routes[J]. Proceedings of the Eastern Asia Society for Transportation Studies, 2009, 27(6): 45-53. http://ci.nii.ac.jp/naid/130005036950
[13]	CHARNES A, COOPER W, LEWIN A, et al. Data envelopment analysis theory, methodology and applications[J]. Journal of the Operational Research Society, 1997(48): 332-333. doi: 10.1057/palgrave.jors.2600342
[14]	AMIN G R. Comments on finding the most efficient DMUs in DEA: an improved integrated model[J]. Computers & Industrial Engineering, 2009, 56(4): 1701-1702.
[15]	祝凌曦, 肖雪梅, 李伟, 等. 基于改进DEA法的铁路应急预案编制绩效评价方法研究[J]. 铁道学报, 2011, 33(4): 1-6. doi: 10.3969/j.issn.1001-8360.2011.04.001 ZHU Lingxiao, XIAO Xuemei, LI Wei, et al. Research on performance evaluation of compilation of railway emergency plan based on improved DEA method[J]. Journal of the China Railway Society, 2011, 33(4): 1-6. (in Chinese). doi: 10.3969/j.issn.1001-8360.2011.04.001
[16]	柯靖宇. 基于PLS偏好的DEA模型在公交线路服务能力评价中的应用研究[D]. 北京: 北京交通大学, 2017. KE Jingyu. Application of PLS-DEA model on the service ability evaluation of transit lines[D]. Beijing: Beijing Jiaotong University, 2017. (in Chinese).
[17]	王卓, 王金详. 基于理想点法的DEA有效单元的效率评价及应用研究[J]. 科学管理研究, 2008, 26(1): 67-69. https://www.cnki.com.cn/Article/CJFDTOTAL-KXGY200801017.htm WANG Zhuo, WANG Jinxiang. Research on efficiency evaluation DEA units based on ideal point method and its application[J]. Scientific Management Reasearch, 2008, 26(1): 67-69. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-KXGY200801017.htm
[18]	侯杰泰, 温忠麟, 成子娟, 等. 结构方程模型及其应用[M]. 北京: 教育科学出版社, 2004. HOU Jietai, WEN Zhonglin, CHENG Zijuan, et al. Structural equation model and its application[M]. Beijing: Educational Science Publishing House, 2004. (in Chinese).
[19]	郭淑霞. 基于时变二源数据的城市公交调度协调模型与算法[D]. 北京: 北京交通大学, 2010. GUO Shuxia. Models and algorithms for urban transit dispatching coordination based on time-varying dual sourcing of data[D]. Beijing: Beijing Jiaotong University, 2010. (in Chinese).
[20]	孟亚男. 基于PLS路径模型的上市公司高管薪酬影响因素研究[D]. 济南: 山东财经大学, 2013. MENG Yanan. The influence factors of executive compensation in listed companies based on PLS path modeling[D]. Jinan: Shandong University of Finance and Economics, 2013. (in Chinese).