1st International ICST Workshop on Computational Transportation Science

Research Article

TransDB: GPS data management with applications in collective transport

  • @INPROCEEDINGS{10.4108/ICST.MOBIQUITOUS2008.3890,
        author={Christian S. Jensen and Dalia Tiesyte},
        title={TransDB: GPS data management with applications in collective transport},
        proceedings={1st International ICST Workshop on Computational Transportation Science},
        publisher={ACM},
        proceedings_a={IWCTS},
        year={2010},
        month={5},
        keywords={Collective transport vehicle trajectories tracking prediction GPS  position data},
        doi={10.4108/ICST.MOBIQUITOUS2008.3890}
    }
    
  • Christian S. Jensen
    Dalia Tiesyte
    Year: 2010
    TransDB: GPS data management with applications in collective transport
    IWCTS
    ICST
    DOI: 10.4108/ICST.MOBIQUITOUS2008.3890
Christian S. Jensen1,*, Dalia Tiesyte1,*
  • 1: Department of Computer Science, Aalborg University, Denmark, Selma Lagerlöfs vej 9220-DK
*Contact email: csj@cs.aau.dk, dalia@cs.aau.dk

Abstract

Recent and continuing advances in geo-positioning, mobile communications, and computing electronics combine to offer opportunities for advanced and affordable collective transport services. As the roads in many parts of the world are facing increasing congestion, it becomes increasingly important to establish collective transport solutions, such as bus services, that are competitive in comparison to the use of private cars. One important ingredient in the provisioning of such solutions is an information system that is always aware of the current location and expected future locations of each bus and that is capable of utilizing this information in real time as well as off-line, e.g., for offering the users accurate arrival information and for creating safe, realistic, and environmentally friendly bus schedules. This paper introduces to an on-going project that explores the advanced data management techniques needed to create an efficient, accurate, and yet inexpensive information system for collective transport monitoring. Focus is on bus travel time prediction and the communication between the vehicles and their surrounding infrastructure.