Passenger Flow Characteristic Analysis of Public Transportation in Urban Agglomerations by Big Data

被引:0
|
作者
Li, Zizi [1 ]
Zhang, Mengyao [2 ]
Han, Yunzhe [3 ]
Zhao, Ying [3 ]
Chen, Yanyan [4 ]
Zhou, Yuyang [4 ]
机构
[1] Beijing Inst Technol, Beijing Engn Res Ctr Urban Transport Operat Guara, Beijing, Peoples R China
[2] Beijing Univ Technol, Beijing Key Lab Traff Engn, Minist Transport, Beijing, Peoples R China
[3] Beijing Public Transport Corp, Beijing, Peoples R China
[4] Beijing Univ Technol, Beijing Key Lab Traff Engn, Key Lab Adv Publ Transportat Sci, Minist Transport, Beijing, Peoples R China
关键词
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The development of the Beijing-Hebei urban agglomeration has driven the increase of intercity travel demand of residents in the region, which increases passenger flow pressure on intercity bus lines. The analysis on the travel characteristics is the basis of operation optimization for supply-demand balance. This paper analyzes the characteristics of passenger flow from the perspectives of travel frequency, passenger mileage utilization, travel time, and spatial distribution, and major origin-destination (OD) flow using the case study of Line 930, with 300,000 smart card data and quick response (QR) data in the fare collection system. The results show that the morning peak of the public transportation in the Beijing-Hebei urban agglomeration is from 5:00 to 7:00. The number of frequent passengers accounted for 64.62%.
引用
收藏
页码:622 / 631
页数:10
相关论文
共 50 条
  • [31] TRANSPORTATION COSTS AND SUBSIDY DISTRIBUTION MODEL FOR URBAN AND SUBURBAN PUBLIC PASSENGER TRANSPORT
    Sevrovic, Marko
    Brcic, Davor
    Kos, Goran
    PROMET-TRAFFIC & TRANSPORTATION, 2015, 27 (01): : 23 - 33
  • [32] Region ridership characteristic clustering using passenger flow data
    Leng, Biao
    Zhao, Wenyuan
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2014, 51 (12): : 2653 - 2662
  • [33] Complex Characteristic Analysis of Passenger Train Flow Network
    Meng, Xuelei
    Jia, Limin
    Xie, Jinxin
    Qin, Yong
    Xu, Jie
    2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 2533 - 2536
  • [34] Public transportation competitiveness analysis based on current passenger loyalty
    Li, Linbo
    Bai, Yufang
    Song, Ziqi
    Chen, Anthony
    Wu, Bing
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2018, 113 : 213 - 226
  • [35] Modeling urban mobility with machine learning analysis of public taxi transportation data
    Song, Ha Yoon
    You, Dabin
    INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS, 2018, 14 (01) : 73 - 87
  • [36] Measuring Transfer Efficiency of Urban Public Transportation Terminals by Data Envelopment Analysis
    Sun, Lishan
    Rong, Jian
    Yao, Liya
    JOURNAL OF URBAN PLANNING AND DEVELOPMENT-ASCE, 2010, 136 (04): : 314 - 319
  • [37] Optimal design of urban transportation planning based on big data
    Sai, Wei
    Wang, Hongzhi
    ENVIRONMENTAL TECHNOLOGY & INNOVATION, 2021, 23
  • [38] Urban Analytics of Big Transportation Data for Supporting Smart Cities
    Leung, Carson K.
    Braun, Peter
    Hoi, Calvin S. H.
    Souza, Joglas
    Cuzzocrea, Alfredo
    BIG DATA ANALYTICS AND KNOWLEDGE DISCOVERY, DAWAK 2019, 2019, 11708 : 24 - 33
  • [39] Passenger flow estimation based on convolutional neural network in public transportation system
    Liu, Guojin
    Yin, Zhenzhi
    Jia, Yunjian
    Xie, Yulai
    KNOWLEDGE-BASED SYSTEMS, 2017, 123 : 102 - 115
  • [40] BIGSEA: A Big Data analytics platform for public transportation information
    Alic, Andy S.
    Almeida, Jussara
    Aloisio, Giovanni
    Andrade, Nazareno
    Antunes, Nuno
    Ardagna, Danilo
    Badia, Rosa M.
    Basso, Tania
    Blanquer, Ignacio
    Braz, Tarciso
    Brito, Andrey
    Elia, Donatello
    Fiore, Sandro
    Guedes, Dorgival
    Lattuada, Marco
    Lezzi, Daniele
    Maciel, Matheus
    Meira Jr, Wagner
    Mestre, Demetrio
    Moraes, Regina
    Morais, Fabio
    Pires, Carlos Eduardo
    Kozievitch, Nadia P.
    dos Santos, Walter
    Silva, Paulo
    Vieira, Marco
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 96 : 243 - 269