TripCube: A Trip-oriented vehicle trajectory data indexing structure |
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| Affiliation: | 1. Key Laboratory of Geographical Information Science, Ministry of Education, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China;2. Key Laboratory of Analysis and Processing on Big Data of Henan Province, Henan University, 85 Minglun Road, Kaifeng, Henan 475001, China;3. Department of Computer Science & Information Systems, College of Business University of North Alabama, Florence, Alabama, United States;4. Naval Academy Research Institute, Brest, France;1. Dept. of Information and Communication Engineering, Chungbuk National University, 410 Seongbong-ro (street), Heungduk-gu, Cheongju, Chungbuk, South Korea;2. School of Software, Xidian University, Xian, Shaanxi 710071, China;1. Institute of Transportation Systems, Deutsches Zentrum für Luft- und Raumfahrt, Germany;2. Engineering Faculty Construction, Geo, Environment, Department of Traffic Techniques, Technical University of Munich, Germany |
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| Abstract: | 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 them being data access issues. Most of existing tree-shape indexing schemes cannot facilitate maintenance and management of very large vehicle trajectory data. How to retrieve vehicle trajectory information efficiently requires more 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 > 100 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. |
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