Large-Scale Trip Planning for Bike-Sharing Systems

In Bike-Sharing System (BSS), great efforts have been devoted to performing resources prediction, redistribution and trip planning to alleviate the unbalance of resources and inconvenience of bike utilization caused by the explosion of users. However, there is few work in trip planning noticing that the complete trip composes of three segments: from user's start point to a start station, from the start station to a target station and from the target station to user's terminal point. To study the case, this paper addresses a static trip planning problem in BSS by considering system-wide conflicts so as to achieve higher service quality of the system. The problem is formulated as the well-known weighted k-set packing problem. We design two algorithms, a Greedy Trip Planning algorithm (GTP) and a Humble Trip Planning algorithm (HTP), for the problem. For comparison, we design a Random Trip Planning algorithm (RTP) as a benchmark. Extensive simulation results show that GTP and HTP outperform RTP and reveal the impact of different factors on our algorithms.