Research On Spatio-temporal Indexing Methods For Intergillgent Transportation Systems

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging which enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. Previous works focus their research on update approaches, with better approaches could reduce update and improve system performance. But although these researches, they didn't give proper index structure to sustain their update approaches. On the other hand, the researches on the spatio-temporal access methods formally base their precondition on the free movement (such as R-tree and TPR-tree), not consider road networks.This paper first introduces LBS, then describes three existing tracking approaches, offers empirical evaluations and comparisons among them, and presents proper access method for each one. Specially, it presents a new access structure for the segment-based tracking approaches and its optimization which indexes moving objects not only by their absolute position but also by the roads they drive.The paper gives the structure description, insertion and search algorithms, then compares this structure with existing spatio-temporal access method TPR-tree in structure size, insertion and query efficiency, which proves it high-power for indexing moving objects in road networks.