Volume 41 Issue 3
Jun.  2023
Turn off MathJax
Article Contents
YU Xiaofei, LIU Bing, CHEN Xi, JIA Tingting, MA Xiaolei. A Method for Planning of Parking-facility Locations Using Internet Mobility Data[J]. Journal of Transport Information and Safety, 2023, 41(3): 119-127. doi: 10.3963/j.jssn.1674-4861.2023.03.013
Citation: YU Xiaofei, LIU Bing, CHEN Xi, JIA Tingting, MA Xiaolei. A Method for Planning of Parking-facility Locations Using Internet Mobility Data[J]. Journal of Transport Information and Safety, 2023, 41(3): 119-127. doi: 10.3963/j.jssn.1674-4861.2023.03.013

A Method for Planning of Parking-facility Locations Using Internet Mobility Data

doi: 10.3963/j.jssn.1674-4861.2023.03.013
  • Received Date: 2022-07-20
    Available Online: 2023-09-16
  • To address the issue of parking facility location under uncertain demand, a method for planning parking facility locations based on Internet mobility data is proposed. This method estimates parking demand and identifies alternative parking facility locations based on residents' commuting data. An optimization model for parking facility location under uncertain demand is developed, which has an objective function considering the construction and maintenance costs of parking facilities and the walking distance from parking facilities. To verify the feasibility of the model, a case study is conducted based on the residents' commuting data in Beijing from September to November in 2021. specifically, an optimization model is established for the area of Zhongguanchun and its surrounding areas in Haidian District and the relationship between variation of the total costs of building and maintaining the parking facilities and uncertainty of parking demand is analyzed. Study results show that the optimal number and size of parking facilities will increase as the confidence interval of satisfying the parking demand (i.e., the probability of parking demand being smaller than or equal to the capacity of parking facilities) increases. When the confidence level reaches 0.9, the variation rate of total cost is significantly increased, where the number of parking facility required is 30 with a total of 28 862 parking spots. In addition, the total system cost is sensitive to the level of uncertainty of parking demand and will increase as the level of uncertainty increases. when the level of uncertainty reaches 0.4, 0.5, and 0.6, the variation rate of relative total cost for parking facility is 1.25, 1.75, and 2.25, respectively. Under the same confidence interval, the higher the level of uncertainty of parking demand, the higher the change rate of total cost is to the level of the uncertainty of the demand. This study enables parking planners to effectively control the total system cost and to ensure the robustness of the location plan by controlling the capacity and demand fluctuations of the parking facilities.

     

  • loading
  • [1]
    李超. 城市商圈停车特性与停车选择研究[D]. 重庆: 重庆交通大学, 2014.

    LI C. Research on parking characteristics and parking choices in urban commercial circles[D]. Chongqing : Chongqing Jiaotong University, 2014. (in Chinese)
    [2]
    黄睿. 我国城市中心商业区停车问题现状及发展对策研究[D]. 西安: 西安建筑科技大学, 2003.

    HUNG R. Research on the current situation and development countermeasures of parking problems in my country's urban central business districts[D]. Xi'an: Xi'an University of Architecture and Technology, 2003. (in Chinese)
    [3]
    GARCÍA-PALOMARES J C, GUTIÉRREZ J, LATORRE M. Optimizing the location of stations in bike-sharing programs: A GIS approach[J]. Applied Geography, 2012, 35(1): 235-246.
    [4]
    汪光焘. 大数据时代城市交通学发展的机遇[J]. 城市交通, 2016, 14(1): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-CSJT201601001.htm

    WANG G T. Opportunities for the development of urban transportation in the era of big data[J]. Urban Transportation, 2016, 14(1): 1-7. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CSJT201601001.htm
    [5]
    郑敏慧. 基于滴滴网约车OD数据的停车规划方法研究[D]. 北京: 北京交通大学, 2018.

    ZHENG M H. Research on parking planning method based on Didi. com car-hailing OD data[D]. Beijing: Beijing Jiaotong University, 2018. (in Chinese)
    [6]
    GUAN Y, WANG Y, YAN X, et al. A big-data-driven framework for parking demand estimation in urban central districts[J]. Journal of Advanced Transportation, 2020, (3): 1-13.
    [7]
    郭彦茹, 罗志雄, 王家川, 等. 数据驱动的共享单车停放区规划方法研究[J]. 交通运输系统工程与信息, 2021, 21(6): 9-16. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202106002.htm

    GUO Y R, LUO Z X, WANG J C, et al. Research on data-driven shared bicycle parking area planning method[J]. Transportation Systems Engineering and Information, 2021, 21(6): 9-16. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202106002.htm
    [8]
    KIM K, KOSHIZUKA N. Data-driven parking decisions: proposal of parking availability prediction model[C]. 16th International IEEE Conference, Charlotte, USA: IEEE, 2019.
    [9]
    LI M, GAO S, LIANG Y, et al. A data-driven approach to understanding and predicting the spatiotemporal availability of street parking[C]. 27th ACM SIGSPATIAL International Conference, Chicago, USA: Association for Computing Machinery, 2019.
    [10]
    FIEZ T, RATLIFF L J, DOWLING C, et al. Data driven spatio-temporal modeling of parking demand[C]. 2018 Annual American Control Conference(ACC), Milwaukee, USA: IEEE, 2018.
    [11]
    SANDOVAL R, VAN GEFFEN C, WILBUR M, et al. Data driven methods for effective micromobility parking[J]. Transportation Research Interdisciplinary Perspectives, 2021 (10): 100368.
    [12]
    陈峻, 王炜, 胡克定. 城市社会停车场选址规划模型研究[J]. 公路交通科技, 2000(1): 61-64. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200001015.htm

    CHEN J, WANG W, HU K. Research on the planning model of urban social parking lot site selection[J]. Highway Traffic Science and Technology, 2000(1): 61-64. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200001015.htm
    [13]
    HSU Y T, YAN S, HUANG P. The depot and charging facility location problem for electrifying urban bus services[J]. Transportation Research Part D: Transport and Environment, 2021(100): 103053.
    [14]
    杨宇. 城市共享新能源汽车选址-分配研究[D]. 北京: 中国矿业大学, 2019.

    YANG YU. Urban shared new energy vehicle site selection-allocation research[D]. Beijing: China University of Mining and Technology, 2019. (in Chinese)
    [15]
    邹志云. 社会公共停车场选址方法研究[J]. 武汉城市建设学院学报, 1996(4): 70-72. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ604.015.htm

    ZOU Z Y. Research on the method of site selection of social public parking lot[J]. Journal of Wuhan Urban Construction Institute, 1996(4): 70-72. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WHCJ604.015.htm
    [16]
    SAIF A, DELAGE E. Data-driven distributionally robust capacitated facility location problem[J]. European Journal of Operational Research, 2021, 291(3): 995-1007.
    [17]
    HAMERLY G, ELKAN C. Learning the k in k-means[C]. 17th Annual Conference on Neural Information Processing Systems(NIPS 2003), Vancouver, Canada: Biologische Kybernetik, 2004.
    [18]
    GABREL V, LACROIX M, MURAT C, et al. Robust location transportation problems under uncertain demands[J]. Discrete Applied Mathematics, 2014(164): 100-111.
    [19]
    NG M, WALLER S T. Reliable evacuation planning via demand inflation and supply deflation[J]. Transportation Research Part E: Logistics and Transportation Review, 2010, 46 (6): 1086-1094.
    [20]
    LI Z. Optimal robust optimization approximation for chance constrained optimization problem[J]. Computers & Chemical Engineering, 2015(74): 89-99.
    [21]
    中华人民共和国建设部. 城市道路交通规划设计规范: GB 50220—95[S]. 北京: 人民交通出版社, 1995.

    Ministry of Construction of the People's Republic of China. Urban road traffic planning and design code: GB 50220-95[S]. Beijing: China Communications Press, 1995.
  • 加载中

Catalog

    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

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(7)

    Article Metrics

    Article views (525) PDF downloads(29) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return