交通运输系统工程与信息 ›› 2018, Vol. 18 ›› Issue (2): 177-182.

• 系统工程理论与方法 • 上一篇    下一篇

共享自行车系统动态调度时间域的获取方法

刘冬旭 1, 2,董红召*1   

  1. 1. 浙江工业大学 智能交通系统联合研究所,杭州 310014;2. 浙江广播电视大学 信息学院 杭州 310012
  • 收稿日期:2017-12-21 修回日期:2018-02-02 出版日期:2018-04-25 发布日期:2018-04-25
  • 作者简介:刘冬旭(1976-),女,江西九江人,副教授,博士生.
  • 基金资助:

    国家自然科学基金/National Natural Science Foundation of China(61773347).

Algorithm of Dynamic Rebalance Time Ranges for Bicycle Sharing System

LIU Dong-xu1, 2, DONG Hong-zhao1   

  1. 1. ITS Joint Research Institute, Zhejiang University of Technology, Hangzhou 310014, China; 2. College of Information Engineering, Zhejiang Radio & Television University, Hangzhou 310012, China
  • Received:2017-12-21 Revised:2018-02-02 Online:2018-04-25 Published:2018-04-25

摘要:

共享自行车系统(Bicycle Sharing System,BSS)调度时机的确定是影响BSS服务质量和调度成本的重要因素.综合考虑调度基准阈值、服务点的自行车周转率及租还量差异时变特性,建立了BSS服务点运行状态的自流动模型.基于自流动模型,提出了BSS服务点调度时机的动态调度时间域获取方法,包括判断服务点空/满位的车容比动态阈值的计算,以及根据BSS服务点调入/调出自行车的需求而获取的正/负调度时间域算法.最后,根据杭州锁桩式BSS运行的2016年历史数据,以编号3758服务点为例,对车容比动态阈值和固定阈值获取的调度时间域及调度效果进行分析比较.结果表明,本文研究的动态调度时间域获取方法能够更精准地获取BSS的调度时机,在满足BSS调度服务质量情况下,可以减少调度频次、降低服务成本

关键词: 城市交通, 调度时间域, 自流动模型, 共享自行车系统, 车容比

Abstract:

The reasonable rebalance time of the Bicycle Sharing System (BSS) are important factors that influence service quality and rebalance costs of BSS. However, few relevant studies have focused on it. A bicycle self-moving model considering the reference threshold, bicycle turnover rate, quantitative difference between rentals and returns, etc. is established to characterize the state change of BSS stations. Based on the self-moving model, the method to acquire the rebalance time range of BSS service station is proposed. The method includes how to calculate occupancy-capacity ratio threshold for assessing the empty/full status of stations and the algorithm for time ranges of positive/negative redistribution for BSS rebalance. Based on the Hangzhou dockbased BSS historical data in 2016, an experiment is conducted on the No. 3758 station to analyze and compare the effects of rebalance time ranges by dynamic threshold and fixed reference threshold of the station’s occupancycapacity ratio. The results show that the proposed method can obtain the exact rebalance time range and help decrease the rebalance frequency of the station. It can not only reduce the rebalance cost but also improve the service quality.

Key words: urban traffic, rebalance time range, self-moving model, BSS, occupancy-capacity ratio

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