| This work addresses the problem of managing moving objects databases which capture the inherent uncertainty associated with the location of moving point objects. We address the issues of: (1) modeling and constructing the trajectories based on the information available in electronic maps. The proposed model of the trajectory captures all of the temporal, spatial and uncertainty aspects; (2) simplification/reduction of the trajectories' representation in order to save storage space, as well as improve the querying performance; (3) updating the database based on the real-time information about traffic abnormalities; (4) the uncertainty aspect in the trajectory model; (5) querying a trajectories database with uncertainty; and (6) triggers utilization in maintaining the consistency of the answer-set for users' queries to the moving objects database.; The trajectory is modeled as a 3D cylindrical body. The model incorporates uncertainty in a manner that enables efficient querying. Thus, our model strikes a balance between modeling power and computational efficiency. To demonstrate efficiency, we report on experimental results that relate the length of a trajectory to its size in bytes. We have generated a real data-set of over 1000 trajectories, based on the maps of 18 counties around Chicago metropolitan area, which was used in our experiments.; We introduce a set of novel but natural spatio-temporal operators which capture uncertainty, and are used to express spatio-temporal range queries. We also devise and analyze algorithms to process these operators which, as it turned out, have strong “computational geometry flavor”. The operators have been implemented as a part of the DOMINO project conducted at the Database and Mobile Computing Laboratory (DBMC) at the University of Illinois at Chicago. |
