交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (1): 351-359.DOI: 10.16097/j.cnki.1009-6744.2026.01.032

• 工程应用与案例分析 • 上一篇    下一篇

共享单车内循环区视角下的调度评估与分类管控

惠英*1,王坪烨1,刘宇良1,余庆2   

  1. 1. 同济大学,道路与交通工程教育部重点实验室,上海201804;2.北京大学,深圳研究生院,城市规划与设计学院,广东深圳518055
  • 收稿日期:2025-11-08 修回日期:2025-12-29 接受日期:2026-01-06 出版日期:2026-02-25 发布日期:2026-02-17
  • 作者简介:惠英(1975—),女,山东日照人,副教授,博士。
  • 基金资助:
    国家自然科学基金(51978475)。

Dispatch Evaluation and Classified Management Considering Bicycle-Sharing Inner Circulation Area

HUI Ying*1, WANG Pingye1, LIU Yuliang1, YU Qing2   

  1. 1. The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China; 2. School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong, China
  • Received:2025-11-08 Revised:2025-12-29 Accepted:2026-01-06 Online:2026-02-25 Published:2026-02-17
  • Supported by:
    National Natural Science Foundation of China (51978475)。

摘要: 为系统评估共享单车实际调度从而开展精细化运营,本文引入共享单车内循环区作为基本空间单元,提出调度评估与分类管控框架,并对上海市进行实证研究。首先,利用共享单车开关锁数据识别骑行和调度行为,并结合社区发现算法和空间邻近性识别出共享单车内循环区。其次,构建包含跨区调度占比、批量调度占比、长距离调度占比、平均调度距离和调度强度的多维评估指标体系,量化调度行为的运营效率和空间结构。在此基础上,运用k-means聚类算法对共享单车内循环区进行分类。结果表明,研究区域被划分为200余个共享单车内循环区,其调度模式呈现显著的空间异质性,例如,中心城区与外环路周边的跨区调度占比较高,而西南市郊区域则是批量调度占比与调度强度较高。此外,通过聚类得到“市区成熟型”“零散长调度型”“市郊拓展型”“郊区低效型”这4类区域,并针对各自调度特征提出稳定维护增效、优化投放策略、集约模式调整和精准缩减运营等差异化管控策略。

关键词: 城市交通, 调度评估, 社区发现算法, 共享单车内循环区, 分类管控

Abstract: To evaluate the actual dispatch of bicycle-sharing and attain refined operations, this paper introduces the Bicycle-sharing Inner Circulation Area (BICA) as the basic spatial unit, and proposes a dispatch evaluation and classified management framework with an empirical study in Shanghai. First, the riding and dispatch behaviors are identified using bicycle-sharing lock data, and the BICAs are delineated by combining community detection algorithms and spatial proximity. Then, a multidimensional evaluation index system is constructed, including the Inter-zone Dispatch Ratio (IDR), Batch Dispatch Ratio (BDR), Long-distance Dispatch Ratio (LDR), Average Dispatch Distance (ADD), and Dispatch Intensity (DI), to quantify the operational efficiency and spatial structure of dispatch behaviors. On this basis, the k-means clustering algorithm is used to classify the BICAs. The results show that the study area can be divided into over 200 BICAs, whose dispatch patterns exhibit significant spatial heterogeneity. For instance, the IDR is higher in the city center and areas surrounding the outer ring road, while the BDR and DI are higher in the southwestern suburbs. Furthermore, the clustering identifies four types of areas: Mature Urban, Scattered Long-distance Dispatch, Suburban Expansion, and Suburban Low-efficiency. Differentiated management strategies based on their respective dispatch characteristics are proposed, such as stable maintenance and efficiency improvement, optimized delivery strategies, intensive mode adjustment, and precise reduction of operations.

Key words: urban transportation, dispatch evaluation, community detection algorithms, bicycle- sharing inner circulation area, classified management

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