algorithmic solutions, bike re-balancing, Bike Sharing System (BSS), data analytics
In recent years, the booming of the Bike Sharing System (BSS) has played an important role in offering a convenient means of public transport. The BSS is also viewed as a solution to the first/last mile connection issue in urban cities. The BSS can be classified into dock and dock-less. However, due to imbalance in bike usage over spatial and temporal domains, stations in the BSS may exhibit overflow (full stations) or underflow (empty stations). In this paper, we will take a holistic view of the BSS design by examining the following four components: system design, system prediction, system balancing, and trip advisor. We will focus on system balancing, addressing the issue of overflow/underflow. We will look at two main methods of bike re-balancing: with trucks and with workers. Discussion on the other three components that are related to system balancing will also be given. Specifically, we will study various algorithmic solutions with the availability of data in spacial and temporal domains. Finally, we will discuss several key challenges and opportunities of the BSS design and applications as well as the future of dock and dock-less BSS in a bigger setting of the transportation system.
Tsinghua University Press
Jie Wu. Challenges and Opportunities in Algorithmic Solutions for Re-Balancing in Bike Sharing Systems. Tsinghua Science and Technology 2020, 25(6): 721-733.