GPS-Data Analysis of Munich's Free-Floating Bike Sharing System and Application of an Operator-based Relocation Strategy

Abstract

Public Bike Sharing Systems provide a progressive option for urban mobility, not only for commuters but also for spontaneous users and tourists. Such systems are only reasonable, if the bikes are available where the users need them at a certain time though. In so-called free-floating systems as it's implemented in Munich, the user is allowed to rent and return a bike within a clearly defined operating area. However, on one hand there are zones, where a shortage of returned bikes occurs. No bikes are available but needed there. On the other hand there are zones, where too many bikes were returned but the demand for renting a bike there is too low. Based on a detailed GPS-Data Analysis for the bike sharing system, mobility patterns of the usage were identified. Depending on different factors like weather conditions, time of the day and holidays/weekends, a demand model was created in order to obtain an optimal distribution of bikes within the operating area. At the end of this paper an application of an operater-based relocation strategy is given. By relocating at least some part of the fleet, it's ensured that the demand for bikes is optimally satisfied in time and space.