Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike Sharing Systems

Bike Sharing Systems (BSSs) have been adopted in many major cities of the world due to traffic congestion and carbon emissions. Although there have been approaches to exploiting either bike trailers via crowdsourcing or carrier vehicles to reposition bikes in the "right" stations in the "right" time, they do not jointly consider the usage of both bike trailers and carrier vehicles. In this paper, we aim to take advantage of both bike trailers and carrier vehicles to reduce the loss of demand with regard to the crowdsourcing of bike trailers and the fuel cost of carrier vehicles. In the experiment, we exhibit that our approach outperforms baselines in several datasets from bike sharing companies. Introduction Bike sharing systems (BSSs) typically have a set of base stations that are strategically placed throughout a city and each station has a fixed number of docks, e.g., Capital Bike-share 1, Bluebikes 2, Mobike 3, BIXI 4, etc. At the beginning of the day, each station is stocked with a predetermined number of bikes. Customers can pick and drop bikes from any station and are charged depending on the hiring duration (Tsai, Chen, and Hong 2019; Hulot, Aloise, and Jena 2018; Lowalekar et al. 2017; Vulcano, van Ryzin, and Ratliff 2012; Schuijbroek, Hampshire, and van Hoeve 2017). Due to the individualistic and uncoordinated movements of customers, there is often starvation (empty base stations precluding bike pickup) or congestion (full base stations precluding bike return) of bikes at certain stations, which results in a significant loss of customer demand (Shu et al. 2013; Chen, Liu, and Liu 2018). To address this problem, a variety of systems (Ghosh et al. 2017; Lowalekar et al. 2017) employ the idea of repositioning idle bikes with the help of carrier vehicles during the day, by taking into account the movement of bikes by customers (Tsai, Chen, and Hong 2019; Pfrommer et al. 2014; Ghosh and V arakantham 2017).