A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data

YIN Shisong; LU Bincheng; YE Mao; YANG Zhiqiang

doi:10.3963/j.jssn.1674-4861.2023.02.009

Volume 41 Issue 2

Apr. 2023

Turn off MathJax

Article Contents

Article Navigation > Journal of Transport Information and Safety > 2023 > 41(2): 86-94

YIN Shisong, LU Bincheng, YE Mao, YANG Zhiqiang. A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data[J]. Journal of Transport Information and Safety, 2023, 41(2): 86-94. doi: 10.3963/j.jssn.1674-4861.2023.02.009

Citation:

YIN Shisong, LU Bincheng, YE Mao, YANG Zhiqiang. A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data[J]. Journal of Transport Information and Safety, 2023, 41(2): 86-94. doi: 10.3963/j.jssn.1674-4861.2023.02.009

Citation:

PDF( 1542 KB)

A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data

doi: 10.3963/j.jssn.1674-4861.2023.02.009

YIN Shisong^{1, 2
,},
LU Bincheng^{1, 2},
YE Mao^{1, 2
,
,},
YANG Zhiqiang³

1.
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
2.
MIIT Key Lab of Traffic Information Fusion & System Control, Nanjing University of Science and Technology, Nanjing 210094, China
3.
Guangzhou Metro Group Co., Ltd, Guangzhou 510000, China

Received Date: 2022-06-23
Available Online: 2023-06-19

Abstract

Abstract

It is a fundamental task to generate effective paths for predicting cross-section passenger flows, calculat-ing network capacity, and analyzing passenger demand of urban rail transit system. To solve the problems of tradi-tional effective path generation in which the validity of each path cannot be evaluated, and the linear constraint can-not be assigned, as well as aiming at reducing the influences of randomness of questionnaire on the final path set generation, a method of generating effective path sets is developed based on traditional survey data. The proposed method analyzes route choice behavior of passengers and makes corresponding hypothesis. Then, models for evalu-ating effective routes under different clusters are established by introducing passenger trip duration. Additionally, the stations and the lines between them are abstracted as nodes and edges of the network of rail transit. And then, considering route types, subjective factors, and the density of passenger flows, the passenger's travel time data are processed using the adaptive DBSCAN algorithm and are divided into clusters according to the density of passenger flows at different time intervals. Furthermore, taking the clustering results as the input, a Logit model is developed to replace the linear constraints in path generation. Weights of effective paths represented by clusters are calculated separately, and the effective path set is obtained based on its continuity characteristics at travel time intervals. Exper-iments are conducted based on multiple origin-destination trip data from the metro network in the City of Guang-zhou. Study results show that the effective paths have an average adjusted Rand index of 0.652. Compared with the traditional algorithms, the adjusted Rand index has improved by 0.379. It indicates that the proposed method produc-es a smoother set boundary in the plane of route length and transfer time, which is more adaptable to complex and changeable networks.
- Urban rail transit,
- Effective path,
- Travel data,
- Density-based clustering,
- K-short circuit algorithm

FullText(HTML)

References(21)

References

[1]	XU G M, LIU W, YANG H. A reliability-based assignment method for railway networks withheterogeneous passen-gers[J]. Transportation Research Part C: Emerging Technolo-gies, 2018, 93: 501-524. doi: 10.1016/j.trc.2018.06.017
[2]	XU G M, LIU W, WU R F, et al. A double time-scale passen-ger assignment model for high-speed railway networks with continuum capacity approximation[J]. Transportation Re-search Part E: Logistics and Transportation Review, 2021, 150: 1-25.
[3]	张永生, 姚恩建, 刘莎莎, 等. 城市轨道交通乘客半补偿路径选择建模与应用[J]. 铁道学报, 2018, 40(2): 1-7. doi: 10.3969/j.issn.1001-8360.2018.02.001 ZHANG Y S, YAO E J, LIU S S, et al. Metro passen-gers'semi-compensatory route choice modeling and applica-tion[J]. Journal of the China Railway Society, 2018, 40(2): 1-7. (in Chinese) doi: 10.3969/j.issn.1001-8360.2018.02.001
[4]	曾诚, 吴佳媛, 罗无瑕, 等. 基于双向BFS算法的城市轨道交通有效路径研究[J]. 交通运输工程与信息学报, 2021, 19(1): 100-108. https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC202101012.htm ZENG C, WU J Y, LUO W X, et al. Subway passenger flow assignment based on BFS and weighted semiclustering algo-rithm[J]. Journal of Transportation Engineering and Informa-tion, 2021, 19(1): 100-108. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTGC202101012.htm
[5]	许胜博, 朱志国. 基于换乘次数的城市轨道交通有效径路集生成算法研究[J]. 交通运输工程与信息学报, 2017, 15(2): 83-90. doi: 10.3969/j.issn.1672-4747.2017.02.013 XU S B, ZHU Z G. Study on effective path set generating al-gorithm for urban rail transit based on transfer times[J]. Jour-nal of Transportation Engineering and Information, 2017, 15(2): 83-90. (in Chinese) doi: 10.3969/j.issn.1672-4747.2017.02.013
[6]	黄婷婷, 朱海燕, 杨聚芬. 基于前景理论的轨道交通乘客路径选择模型[J]. 都市快轨交通, 2019, 32(2): 59-63. https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG201902017.htm HUANG T T, ZHU H Y, YANG J F. The route choice model of urban rail traveler based on prospect theory[J]. Urban Rap-id Rail Transit, 2019, 32(2): 59-63. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG201902017.htm
[7]	MINGOZZI A, GIORGI S, BALDACCI R. An exact method for the vehicle routing problem with backhauls[J]. Transporta-tion Science, 1999, 33(3): 315-329. doi: 10.1287/trsc.33.3.315
[8]	CANCA D, DE-LOS-SANTOS A, LAPORTE G, et al. Inte-grated railway rapid transit network design and line planning problem with maximum profit[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 127(7): 1-30.
[9]	杨泳, 严余松, 户佐安, 等. Logit随机网络配流模型的改进Dial算法[J]. 交通运输系统工程与信息, 2013, 13(2): 158-163. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201302025.htm YANG Y, YAN Y S, HU Z A, et al. Improved Dial's algo-rithm for Logit-Based stochastic traffic assignment model[J]. Journal of Transportation Engineering and Information, 2013, 13(2): 158-163. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201302025.htm
[10]	王冠, 钟鸣, 李建忠, 等. 时变网络下轨道交通出行路径动态选择模型: 以武汉市为例[J]. 交通信息与安全, 2020, 38(3): 48-56. doi: 10.3963/j.jssn.1674-4861.2020.03.00701 WANG G, ZHONG M, LI J Z, et al. A route dynamic assign-ment model of rail transit with time-varying network topolo-gy: A case study of Wuhan city[J]. Journal of Transport Infor-mation and Safety, 2020, 38(3): 48-56. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2020.03.00701
[11]	王璐瑶, 蒋熙. 基于集成学习的城市轨道交通乘客路径选择建模[J]. 铁道学报, 2020, 42(6): 18-24. https://www.cnki.com.cn/Article/CJFDTOTAL-TDXB202006003.htm WANG L Y, JIANG X. Ensemble learning based bodeling of passenger route choice on urban rail transit network[J]. Jour-nal of the China Railway Society, 2020, 42(6): 18-24. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TDXB202006003.htm
[12]	周薇. 城市轨道交通有效路径选择的改进Dial算法[J]. 西华大学学报(自然科学版), 2013(6): 38-40, 50. https://www.cnki.com.cn/Article/CJFDTOTAL-SCGX201306009.htm ZHOU W. Improved Dial algorithm for urban rail transit path selection[J]. Journal of Xihua University(Natural Sci-ence Edition), 2013(6): 38-40, 50. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SCGX201306009.htm
[13]	BINDER S, MAKNOON M Y, AZADEH SS, et al. Passen-ger-centric timetable rescheduling: A user equilibrium ap-proach[J]. Transportation Research Part C: Emerging Tech-nologies, 2021(132): 103368.
[14]	朱炜, 韦锦, 洪玲, 等. 基于旅行时间分析的城轨乘客路径集验证方法[J]. 同济大学学报(自然科学版), 2019, 47(1): 56-63. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201901007.htm ZHU W, WEI J, HONG L, et al. Validation method of pas-senger route choice set based on travel time analysis for ur-ban rail transit[J]. Journal of Tongji University(Natural Sci-ence), 2019, 47(1): 56-63. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201901007.htm
[15]	翁小雄, 张洁颖. 基于BFS和加权半监督聚类算法的地铁客流分配研究[J]. 都市快轨交通, 2020, 33(3): 77-84. https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG202003018.htm WEN X X, ZHANG J Y. Subway passenger flow assignment based on BFS and weighted semiclustering algorithm[J]. Ur-ban Rapid Rail Transit, 2020, 33(3): 77-84. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DSKG202003018.htm
[16]	ANUPRIYA, GRAHAM D J, CARBO J M, et al. Under-standing the costs of urban rail transport operations[J]. Trans-portation Research Part B: Methodological, 2020(38): 292-316.
[17]	毛保华, 四兵锋, 刘智丽. 城市轨道交通网络管理及收入分配理论与方法[M]. 北京: 科学出版社, 2007. MAO B H, SI B F, LIU Z L. Theory and method of urban rail transit network management and income distribution[M]. Beijing: Science Press, 2007. (in Chinese)
[18]	杨信丰, 刘兰芬, 李引珍, 等. 基于影响度的有效路径集合的确定[J]. 交通运输系统工程与信息, 2011, 11(6): 104-110. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201106017.htm YANG X F, LIU L F, LI Y Z, et al. Determining the efficient paths based on effect degree[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(6): 104 -110. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201106017.htm
[19]	周慧娟, 邢玉玲. 基于乘客轨道交通出行全过程的服务水平评价体系[J]. 交通工程, 2020, 20(6): 44-50. https://www.cnki.com.cn/Article/CJFDTOTAL-DLJA202006008.htm ZHOU H J, XING Y L. Level of service evaluation system based on the entire journey of passenger travel on rail tran-sit[J]. Journal of Transportation Engineering, 2020, 20(6): 44-50. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLJA202006008.htm
[20]	李文杰, 闫世强, 蒋莹, 等. 自适应确定DBSCAN算法参数的算法研究[J]. 计算机工程与应用, 2019, 55(5): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201905002.htm LI W J, YAN S Q, JIANG Y, et al. Research on method of self-adaptive determination of DBSCAN algorithm parame-ters[J]. Computer Engineering and Applications, 2019, 55(5): 1-7. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201905002.htm
[21]	HUBERT L, ARABIE P. Comparing partitions[J]. Journal of Classification, 1985, 2(1): 193-218.

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(7) / Tables(4)

Get Citation

PDF

XML

Article Metrics

Article views (835) PDF downloads(26)

A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data

doi: 10.3963/j.jssn.1674-4861.2023.02.009

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

A Method of Generating Effective Paths of Urban Rail Transit Based on Passenger Fare Collection Data

doi: 10.3963/j.jssn.1674-4861.2023.02.009

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content