Cityride: A predictive bike sharing journey advisor
Ji Won Yoon, Fabio Pinelli, et al.
MDM 2012
Together with the availability of new mobility data, the development of new intelligent transport systems (ITS) have increased, in order to provide new key performance indicators toward the improvement of the management of traffic awareness in cities. ITS rely on accurate transit infrastructure data that often contain erroneous information (e.g., inconsistencies or is out of date). In this paper, we propose a new methodology that makes use of GPS traces to automatically detect or correct bus stop locations, reconstruct bus route shapes, and estimate time schedules. The methodology performs different steps: 1) data cleaning and detection of trips; 2) bus stop extraction through data mining techniques; 3) route shape reconstruction; and 4) time schedule estimation. A case study using real GPS data from the City of Dublin, Ireland, is performed.
Ji Won Yoon, Fabio Pinelli, et al.
MDM 2012
Jean-François Labourdette, Eric Bouillet, et al.
IEEE/ACM Transactions on Networking
Hoang Thanh Lam, Eric Bouillet
SIGSPATIAL GIS 2014
Michele Berlingerio, Fabio Pinelli, et al.
Data Mining and Knowledge Discovery