Dynamic Obstructed Group Trip Planning Queries in Spatial Databases

Abstract

In this research work, we introduce dynamic obstructed group trip planning (DOGTP) query which allows a group of members to plan a trip dynamically with a minimum total travel distance in the obstructed space. Here, the group of members in a trip can join or leave or rejoin in the middle of a trip at any point of interests (POIs) i.e. restaurant, shopping mall, library or theater. Researchers developed solution for dynamic group trip planning queries in the Euclidean space. They did not consider obstacles in their problem space. In the obstructed space, members can face different types of obstacles i.e. building, private property, main road, lake etc. Therefore, the key challenges of our research work is to minimize the obstructed trip distance in order to find an optimal solution of the dynamic group trip planning queries in the obstructed space. Thus in this study, we extend the research work of dynamic group trip planing query in the Euclidean space into the Obstructed space. We develop solution for processing DOGTP query that returns the optimal trip for all group members with reduced I/O and query processing overhead.