Journal of Computer Science and Technology ›› 2019, Vol. 34 ›› Issue (4): 709-726.doi: 10.1007/s11390-019-1938-4

Special Issue: Surveys; Data Management and Data Mining

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Moving Objects with Transportation Modes: A Survey

Jian-Qiu Xu1, Member, CCF, Ralf Hartmut Güting2, Yu Zheng3, Senior Member, CCF, Ouri Wolfson4, Fellow, ACM, IEEE   

  1. 1 College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics Nanjing 211106, China;
    2 Faculty of Mathematics and Computer Science, University of Hagen, Hagen 58097, Germany;
    3 JD Intelligent City Research, Beijing 100176, China;
    4 Department of Computer Science, University of Illinois at Chicago, Chicago 60607, U.S.A
  • Received:2019-01-31 Revised:2019-04-17 Online:2019-07-11 Published:2019-07-11
  • Supported by:
    Jian-Qiu Xu is supported by the National Key Research and Development Program of China under Grant No. 2018YFB1003900 and the Fundamental Research Funds for the Central Universities of China under Grant No. NS2017073.

In this article, we survey the main achievements of moving objects with transportation modes that span the past decade. As an important kind of human behavior, transportation modes reflect characteristic movement features and enrich the mobility with informative knowledge. We make explicit comparisons with closely related work that investigates moving objects by incorporating into location-dependent semantics and descriptive attributes. An exhaustive survey is offered by considering the following aspects:1) modeling and representing mobility data with motion modes; 2) answering spatio-temporal queries with transportation modes; 3) query optimization techniques; 4) predicting transportation modes from sensor data, e.g., GPS-enabled devices. Several new and emergent issues concerning transportation modes are proposed for future research.

Key words: moving object; transportation mode; data model; performance; data generator;

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         1860-4749(Online)
CN 11-2296/TP

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