Volume 39 Issue 1
Feb.  2021
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YU Erze, ZHOU Jibiao. Travel Characteristics and Influencing Factors of Bike Sharing Based on Spatial Lag Model[J]. Journal of Transport Information and Safety, 2021, 39(1): 103-110. doi: 10.3963/j.jssn.1674-4861.2021.01.0012
Citation: YU Erze, ZHOU Jibiao. Travel Characteristics and Influencing Factors of Bike Sharing Based on Spatial Lag Model[J]. Journal of Transport Information and Safety, 2021, 39(1): 103-110. doi: 10.3963/j.jssn.1674-4861.2021.01.0012
shu

Travel Characteristics and Influencing Factors of Bike Sharing Based on Spatial Lag Model

doi: 10.3963/j.jssn.1674-4861.2021.01.0012
  • 1.

    School of Highway, Chang'an University, Xi'an 710064, China

  • 2.

    Beijing PKU ChinaFront High Technology Co., Ltd, Beijing 100085, China

  • 3.

    School of Civil and Transportation Engineering, Ningbo University of Technology, Ningbo 315211, ZheJiang, China

  • Received Date: 2020-12-09
  • Publish Date: 2021-02-28
    Abstract
  • The paper aims to investigate the spatial-temporal characteristics of the bike sharing system(BSS)and quantify factors affecting BSS usage from the urban spatial environment. The spatio-temporal analysis is conducted to investigate the mobility pattern of BSS using the massive IC-card data in central urban area of Ningbo, China. By considering the spatial autocorrelation of pick-up and drop-off, a spatial lag model is established to identify the internal relationship between BSS usage and spatial variables from population density, road distribution, public transportation, station infrastructure, and built environment. The results show that: ①The global Moran's I for pick-up and drop-off on weekdays and weekends is 0.294, 0.281, 0.272, and 0.271, indicating the spatial correlation is significantly positive. ②The goodness of fit is 0.431, 0.424, 0.412, and 0.401, showing that these models have good fitness and explanatory. ③There are also significant temporal differences between road distribution and built environment variables influencing BSS usage. The length of bus lanes is negatively correlated with the usage demand during weekends, and the POI mixing degree positively affects the demand for pick-up and drop-off on weekdays.

     

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    • References(20)
  • [1]
    SOHRABI S, PALETI R, BALAN L, et al. Real-time prediction of public bike sharing system demand using generalized extreme value count model[J]. Transportation Research Part A: Policy and Practice, 2020(133): 325-336. http://ideas.repec.org/a/eee/transa/v133y2020icp325-336.html
    [2]
    EL-ASSI W, MAHMOUD M, HABIB, K. Effects of built environment and weather on bike sharing demand: A station level analysis of commercial bike sharing in Toronto[J]. Transportation, 2017, 44(3): 589-613. doi: 10.1007/s11116-015-9669-z
    [3]
    LIN Pengfei, WENG Jiancheng, LIANG Quan, et al. Impact of weather conditions and built environment on public bikesharing trips in Beijing[J]. Networks and Spatial Economics, 2020, 20(1): 1-17. doi: 10.1007/s11067-019-09465-6
    [4]
    SUN Y, MOBASHERI A, HU X, et al. Investigating impacts of environmental factors on the cycling behavior of bicycle-sharing users[J]. Sustainability, 2017, 9(6): 1060-1072. doi: 10.3390/su9061060
    [5]
    尹秋怡, 甄峰, 罗桑扎西, 等. 新城公共自行车出行空间影响因素及布局建议[J]. 现代城市研究, 2018(12): 9-15+46. doi: 10.3969/j.issn.1009-6000.2018.12.002

    YIN Qiuyi, ZHEN Feng, LUO Sangzhaxi, et al. Influencing factors and layout suggestions of public bicycle travel space in the new city[J]. Modern Urban Research, 2018(12): 9-15+46. (in Chinese) doi: 10.3969/j.issn.1009-6000.2018.12.002
    [6]
    LIN J, ZHAO P, TAKADA K, et al. Built environment and public bike usage for metro access: a comparison of neighborhoods in Beijing, Taipei, and Tokyo[J]. Transportation Research Part D: Transport and Environment, 2018(63): 209-221. http://www.sciencedirect.com/science/article/pii/S1361920917307198
    [7]
    BAO Jie, SHI Xiaomeng, ZHANG Hao. Spatial analysis of bikeshare ridership with smart card and POI data using geographically weighted regression method[J]. IEEE Access, 2018(6): 76049-76059.
    [8]
    FAGHIH-IMANI A, ELURU N. Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York Citibike system[J]. Journal of Transport Geography, 2016(54): 218-227.
    [9]
    MA Xinwei, JI Yanjie, JIN Yuchuan, et al. Modeling the factors influencing the activity spaces of bikeshare around metro stations: A spatial regression model[J]. Sustainability, 2018, 10 (11): 3949. doi: 10.3390/su10113949
    [10]
    杜明洋, 程琳, 李雪峰. 基于自适应粒子群小波网络的公共自行车出行需求预测[J]. 公路交通科技, 2019, 36(6): 94-102. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201906013.htm

    DU Mingyang, CHENG Lin, LI Xuefeng. Prediction of public bike trip demand based on APSO-WNN[J]. Journal of Highway and Transportation Research and Development, 2019, 36 (6): 94-102. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201906013.htm
    [11]
    LIU H, LIN J. Associations of built environments with spatiotemporal patterns of public bicycle use[J]. Journal of Transport Geography, 2019, 74(3): 299-312. http://www.sciencedirect.com/science/article/pii/S0966692318305660
    [12]
    ORNL."2017 LandScan data for population distribution from the Oak Ridge National Laboratory in USA."[R/OL]. (2018-06)[2020-12-09]. https://landscan.ornl.gov/.
    [13]
    池娇, 焦利民, 董婷, 等. 基于POI数据的城市功能区定量识别及其可视化[J]. 测绘地理信息, 2016, 41(2): 68-73. https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG201602018.htm

    CHI Jiao, JIAO Limin, DONG Ting, et al. Quantitative identification and visualization of urban functional area based on POI data[J]. Journal of Geomatics, 2016, 41(2): 68-73. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CHXG201602018.htm
    [14]
    庄楚天, 吴戈. 基于站点爬虫数据的公共自行车系统时空特征分析[J]. 交通信息与安全, 2017, 35(3): 51-58. doi: 10.3963/j.issn.1674-4861.2017.03.007

    ZHUANG Chutian, WU Ge. Spatial-temporal characteristics of a shared bicycle system based on web crawler data[J]. Journal of Transport Information and Safety, 2017, 35(3): 51-58. (in Chinese) doi: 10.3963/j.issn.1674-4861.2017.03.007
    [15]
    ANSELIN L. Spatial econometrics: Methods and models[M]. Dordrecht: Kluwer Academic Publishers, 1988.
    [16]
    NKURUNZIZA A, ZUIDGEEST M, BRUSSEL M. Examining the potential for modal change: Motivators and barriers for bicycle commuting in Dares-Salaam[J]. Transport Policy, 2012 (24): 249-259.
    [17]
    ZHANG Ying, THOMAS T, BRUSSEL M, et al. Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China[J]. Journal of Transport Geography, 2017(58): 59-70. http://www.sciencedirect.com/science/article/pii/S0966692316300412
    [18]
    GUO Yanyong, ZHOU Jibiao, WU Yao, et al. Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China[J]. Plos One, 2017, 12(9): 1-19. http://www.ncbi.nlm.nih.gov/pubmed/28934321
    [19]
    张敏捷, 周继彪, 董升, 等. 城市公共自行车准动态调度方法[J]. 交通运输系统工程与信息, 2019, 19(5): 185-192. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201905026.htm

    ZHANG Minjie, ZHOU Jibiao, DONG Sheng, et al. Quasi-dynamic balancing method for urban public bike-sharing system[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(5): 185-192. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201905026.htm
    [20]
    于乐, 谢秉磊, 张鹍鹏, 等. 职住地建成环境对网约车通勤出行影响研究[J]. 交通信息与安全, 2019, 37(6): 149-155. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201906019.htm

    YU Le, XIE Binglei, ZHANG Kunpeng, et al. Impacts of built environments on car-hailing commuting in job-housing locations[J]. Journal of Transport Information and Safety, 2019, 37 (6): 149-155. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS201906019.htm
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