交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (3): 182-189.

• 系统工程理论与方法 • 上一篇    下一篇

考虑移步需求的无桩型共享单车动态调度研究

李兴华,张昕源,成诚,杨超,王洧*   

  1. 同济大学道路与交通工程教育部重点实验室,上海 201804
  • 收稿日期:2019-11-13 修回日期:2020-02-25 出版日期:2020-06-25 发布日期:2020-06-28
  • 作者简介:李兴华(1967-),男,黑龙江克山人,教授,博士.

Dynamic Repositioning Model for Free-floating Bikesharing System Considering Shifting Demand

LI Xing-hua, ZHANG Xin-yuan, CHENG Cheng, YANG Chao,WANGWei   

  1. LI Xing-hua, ZHANG Xin-yuan, CHENG Cheng, YANG Chao,WANGWei
  • Received:2019-11-13 Revised:2020-02-25 Online:2020-06-25 Published:2020-06-28

摘要:

共享单车系统自发的不均衡性导致单车数量分布与用户需求分布之间产生偏移,降低了系统服务能力,需要调度实现再平衡. 现有动态调度算法缺乏考虑起点车辆供给不足,用户在出行过程中“再次”取车的移步需求,难以准确识别用户真实的出行需求分布,降低了调度效果. 本文提出以用户出行选择行为为下层,以调度车辆路径规划为上层的双层规划模型框架,设计结合仿真系统的启发式求解算法. 算例场景基于上海市虹口、杨浦区共享单车历史出行数据搭建,并进行网格化处理. 算例结果表明,模型能有效识别移步需求,提高共享单车的供需匹配能力. 针对各类调度资源配置情况,共享单车的供需匹配率提升18.07%~ 19.89%,提高了共享单车系统的管理效率.

关键词: 城市交通, 共享单车动态调度, 双层规划模型, 无桩型共享单车, 多主体仿真

Abstract:

The spontaneous imbalance of the bike- sharing system creates an offset between the distribution of bikes and demands, and reduces the service capacity of the system. Bike reposition is needed to achieve rebalancing of the system. Existing dynamic reposition algorithms haven't considered the "re-take" demand during the trip due to insufficient supply at the origin. It is difficult to accurately identify the real distribution of requests and reposition effect was thus reduced. This paper proposed a bi-level programming model with user choice behavior as the lower layer and truck path planning as the upper layer. The heuristic algorithm with a simulator was used to solve the model. The case study was based on the historical data of Hongkou, Yangpu districts of Shanghai, China, and was grid- processed. The results show that the proposed model can effectively identify the shifting demand and improve the demand- supply matching level. The matching ratio has been improved by 18.07% to 19.89% under different reposition resource configurations, and the efficiency of bike- sharing system management has been enhanced to some extent.

Key words: urban traffic, dynamic sharing-bike repositioning problem, bilevel programming model, free-floating bike-sharing system, multi-agent simulation

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