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This paper aims to address the issue of imbalanced supply and demand in shared bikes by proposing the concept of ‘red packet bike’, utilizing the open-source Beijing Shared Bike Dataset. The Temporal Graph Convolutional Network (T-GCN) is selected to predict the demand for shared bikes based on the analysis of spatio-temporal correlations in the order data. Additionally, a user incentive scheduling algorithm is designed using the breadth-first algorithm (BFS) and presented in the form of distributing the red packet bikes, thereby delegating the scheduling problem to the users to solve.

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Dynamic Scheduling Strategy Based on Demand Prediction of Shared Bike

  • 会议论文

  • 发表日期：

    2025年

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  • Xiangkai Qiu,
  • Wenbing Yang,
  • Haoyang Zhou,
  • He Wang,
  • Shangjing Lin

摘要

This paper aims to address the issue of imbalanced supply and demand in shared bikes by proposing the concept of ‘red packet bike’, utilizing the open-source Beijing Shared Bike Dataset. The Temporal Graph Convolutional Network (T-GCN) is selected to predict the demand for shared bikes based on the analysis of spatio-temporal correlations in the order data. Additionally, a user incentive scheduling algorithm is designed using the breadth-first algorithm (BFS) and presented in the form of distributing the red packet bikes, thereby delegating the scheduling problem to the users to solve.