Real-Time System Prediction & Optimal Rebalancing Strategies for Public Bike Sharing Systems
| 项目名称： | Real-Time System Prediction & Optimal Rebalancing Strategies for Public Bike Sharing Systems |
| 摘要： | The primary goal of the proposed study is to develop tools that can be used to enhance the performance of public Bicycle Sharing Systems (BSS), in particular the Capital Bikeshare. Capital Bikeshare is one of the oldest and largest BSS operating in Washington D.C., Virginia, and Maryland. In this context, the objectives of the study are three-fold: Objective (1): Develop real-time system state prediction models of BSS. These models will be able to predict the number of departures of customers for retrieving bikes and number of arrivals of customers for returning bikes at each station by time-of-day. Objective (2): Develop heuristic algorithms for managing the expected demand patterns. This includes development of quick heuristic algorithms that can identify optimal rebalancing schedules as demand evolves in real-time Objective (3): Integrate the predictive models into a geographic information systems (GIS) toolkit with an easy-to-use Graphical User Interface (GUI) that visually depicts the future demand patterns (for BSS customers) and associated optimal rebalancing routes and schedules (for BSS operators). |
| 状态： | Completed |
| 资金： | 0 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 执行机构： | Virginia Tech Transportation Institute |
| 主要研究人员： | Paleti, Rajesh |
| 开始时间： | 20160501 |
| 预计完成日期： | 20171031 |
| 实际结束时间： | 0 |
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