Data-driven Planning and Design for Bike Sharing Parking Spots

被引：0
|
作者：
Guo Y.-R. [1 ]
Luo Z.-X. [2 ]
Wang J.-C. [1 ]
He F. [2 ]
机构：
[1] Beijing Transportation Information Center, Beijing
[2] Department of Industrial Engineering, Tsinghua University, Beijing
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2021年 / 21卷 / 06期
基金：
国家重点研发计划;
关键词：
Bike sharing; Mixed-integer programming; Modeling and simulation; Parking spots planning; Simulation-based optimization; Traffic engineering;
D O I：
10.16097/j.cnki.1009-6744.2021.06.002
中图分类号：
学科分类号：
摘要：
This paper investigates the bike-sharing parking spots planning from both macro and micro perspectives. The proposed method optimizes the location, capacity, and layout of the parking areas. At the macro level, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) generates the feasible parking locations through the bike parking/renting data cluster analysis. Then a mixed-integer linear programming model is developed to optimize the site and capacity of parking areas, considering users' path choice and parking spots choice and capacity. The micro-level analysis taking account of the interaction between pedestrians, bicycles, and vehicles. The improved social force model is used to simulate the movement of pedestrians and shared bike users. The parking area layout is evaluated through the traffic efficiency analysis. The risk level of mixed traffic simulation and is optimized by surrogate-based optimization. The proposed method has been applied to plan the bike-sharing parking areas around Chongwenmen metro station in Beijing, China. The implementation verifies the effectiveness of the method, improves the mixed traffic efficiency, and reduces the traffic risk. Copyright © 2021 by Science Press.
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页码：9 / 16
页数：7
相关论文
共 16 条
  • [1] LI K H., Research on the development countermeasures of urban bike-sharing based on the perspective of sharing economy, City, 3, pp. 66-69, (2017)
  • [2] LI Y F., Fixed point settlement" is the "intelligent key" to crack the randomly parking, China Consumer Journal
  • [3] GARCiA-PALOMARES J C, GUTIeRREZ J, LATORRE M., Optimizing the location of stations in bike-sharing programs: A GIS approach, Applied Geography, 35, 1-2, pp. 235-246, (2012)
  • [4] ELEBI D, YORUSUN A, ISIK H., Bicycle sharing system design with capacity allocations, Transportation Research Part B: Methodological, 114, pp. 86-98, (2018)
  • [5] LU M, AN K, HSU S C, Et al., Considering user behavior in free-floating bike sharing system design: A data-informed spatial agent-based model, Sustainable Cities and Society, 49, (2019)
  • [6] WANG Y Q, JIA S P, ZHANG S J, Et al., Reward and punishment strategy for bicycle-sharing parking based on the game theory under the influence of position recognition rate, Journal of Transportation Systems Engineering and Information Technology, 19, 1, pp. 97-103, (2019)
  • [7] HELBING D, MOLNAR P., Social force model for pedestrian dynamics, Physical Review E, 51, 5, (1995)
  • [8] MOUSSA? D M, HELBING D, THERAULAZ G., How simple rules determine pedestrian behavior and crowd disasters, Proceedings of the National Academy of Sciences, 108, 17, pp. 6884-6888, (2011)
  • [9] GUO N, JIANG R, WONG S C, Et al., Modeling the interactions of pedestrians and cyclists in mixed flow conditions in uni-and bidirectional flows on a shared pedestrian-cycle road, Transportation Research Part B: Methodological, 139, pp. 259-284, (2020)
  • [10] TREIBER M, HELBING D., Realistische Mikrosimulation von Strassenverkehr mit einem einfachen Modell, 16th Symposium Simulationstechnik ASIM, 2002, (2002)
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