Title: Bike sharing systems: a new incentive rebalancing method based on spatial outliers detection

Authors: Yousra Chabchoub; Rayane El Sibai; Christine Fricker

Addresses: LISITE Laboratory, Institut suprieur d'lectronique de Paris (ISEP), 10 Rue de Vanves, Issy-les-Moulineaux 92130, France ' LISITE Laboratory, Institut suprieur d'lectronique de Paris (ISEP), 10 Rue de Vanves, Issy-les-Moulineaux 92130, France ' Departement dinformatique de lENS, École normale supérieure, CNRS, PSL, Research University, 75005 Paris, France

Abstract: Since its launch, Velib' (the Bike Sharing System – BSS – in Paris) has emerged in the Parisian landscape and has been a model for similar systems in many cities. A major problem with BSS is the stations' heterogeneity caused by the attractivity of some stations located in particular areas. In this paper, we focus on spatial outliers defined as stations having a behaviour significantly different from their neighbouring stations. First, we propose an improved version of Moran scatterplot to exploit the similarity between neighbours, and we test it on a real dataset issued from Velib' system to identify outliers. Then, we design a new method that globally improves the resources' availability in bike stations by adapting the users' trips to the resources' availability. Results show that with a partial collaboration of the users or a limitation to the rush hours, the proposed method enhances significantly the resources' availability in Velib' system.

Keywords: outliers detection; spatial data mining; Moran scatterplot; bike sharing systems; BSS.

DOI: 10.1504/IJSSC.2019.104220

International Journal of Space-Based and Situated Computing, 2019 Vol.9 No.2, pp.99 - 108

Received: 17 Dec 2018
Accepted: 31 May 2019
Published online: 22 Dec 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article