TripCube: A Trip-oriented vehicle trajectory data indexing structure

Tao Xu (1, 2) , Xihui Zhang (2) , Christophe Claramunt (3) , Li Xiang (1)

1 ECNU - East China Normal University [Shangaï]
2 Key Laboratory of Big Data Analysis and Processing
3 IRENAV - Institut de Recherche de l'Ecole Navale

With the dramatic development of location-based services, a large amount of vehicle trajectory data are available and applied to different areas,while there are still many research challenges left, one of thembeing data access issues. Most of existing tree-shape indexing schemes cannot facilitate maintenance and management of very large vehicle trajectory data. Howto retrieve vehicle trajectory information efficiently requiresmore efforts. Accordingly, this paper presents a trip-oriented data indexing scheme, named TripCube, for massive vehicle trajectory data. Its principle is to represent vehicle trajectory data as trip information records and develop a three-dimensional cube-shape indexing structure to achieve trip-oriented trajectory data retrieval. In particular, the approach is implemented and applied to vehicle trajectory data in the city of Shanghai including N100 million locational records per day collected from about 13,000 taxis. TripCube is compared to two existing trajectory data indexing structures in our experiments, and the result exhibits that TripCube outperforms others.

Mots clés: Spatio-temporal data management; Indexing structure; Vehicle trip; Vehicle trajectory data

Domaines: Informatique [cs]

Tao Xu, Xihui Zhang, Christophe Claramunt, Li Xiang. TripCube: A Trip-oriented vehicle trajectory data indexing structure. Computers, Environment and Urban Systems, 2018, 67, pp.21-28. ⟨10.1016/j.compenvurbsys.2017.08.005⟩. ⟨hal-02139371⟩