Data-Driven Dynamic Optimization of Electronic Fences in Free-Float Bike Sharing Systems

As an emerging technical means of free-float bike sharing parking management, electronic fencing solves the problem of chaotic parking. Existing research mostly conducts static optimal site selection for electronic fences, without considering the spatial and temporal heterogeneity of free-float bike sharing, which to some extent causes the problem of resource utilization mismatch. This paper proposes a multi-scale siting method based on free-float bike sharing big data to select the site of free-float bike sharing electronic fence in a macro and micro superposition way; starting from users and enterprises, establishing a multi-objective hybrid planning model considering the characteristics of free-float bike sharing, and dynamically optimizing the free-float bike sharing electronic fence to determine the open location and capacity of the electronic fence in different time periods. An example analysis of the free-float bike sharing data set in the local area of Shenzhen is selected to verify the effectiveness of the method.