Trip Planning Queries for Subgroups in Spatial Databases

Abstract

In this paper, we introduce a novel type of trip planning queries, a subgroup trip planning (SGTP) query that allows a group to identify the subgroup and the points of interests (POIs) from each required type (e.g., restaurant, shopping center, movie theater) that have the minimum aggregate trip distance for any subgroup size. The trip distance of a user starts at the user’s source location and ends at the user’s destination via the POIs. The computation of POI set for all possible subgroups with the straightforward application of group trip planning (GTP) algorithms would be prohibitively expensive. We propose an algorithm to compute answers for different subgroup size concurrently with less query processing overhead. We focus on both minimizing the total and maximum trip distance of the subgroup. We show the efficiency of our algorithms in experiments using both real and synthetic datasets.