StaCover: Mobile Energy-Sharing Cabinets Deployment with Public Bike System

To enhance environmental sustainability and fulfill metropolitan public traffic demands, some metropolises are developing a kind of new Bike-Energy System (BES) including the existing Public Bike System (PBS) and Mobile Energy-sharing System (MES), which consists of some batteries-loaded cabinets. Cabinet location selection is expected to facilitate users to access battery in nearby cabinet. Meanwhile, the limited budget cannot afford establish a cabinet for each station. It thus brings up a problem: which bike stations should be selected to deploy the cabinets so as to minimize the deployment cost and satisfy that all users can rent and return battery conveniently from at least one nearby bike station on the way riding. This paper formulates the bike station selection problem as the Set Cover Problem and proposes a novel data-driven method-StaCover accordingly. StaCover presents the Density-Based Stations Clustering algorithm (DBSC) to select the candidate stations and then designs a Greedy Heuristic Selection algorithm (GHS) to determine the final stations to deploy the energy-sharing cabinets. Our experiments adopt diversified parameters to demonstrate the effectiveness of StaCover over the other methods.