Trip Planning and Scheduling Queries in Spatial Databases: A Survey

Abstract

Planning and scheduling trips in an optimized manner allow users to perform their daily activities with convenience. A trip planning query finds a trip for a single user or a group jointly visiting different types of points of interests (POIs) such as a restaurant, a pharmacy and a movie theater with the minimum travel cost, whereas a trip scheduling query distributes the tasks of visiting different POI types among the group members by computing individual trips for the group members. In recent years, researchers have proposed variants of location based trip queries that include single trip planning queries, group trip planning queries, group trip scheduling queries, obstructed trip planning queries, dynamic group trip planning queries, and privacy preserving trip planning queries. Processing trip planning and scheduling queries in real time is a computational challenge as trips may involve more than one user and POIs of multiple types, and more importantly, the query answer is evaluated from a huge POI database. In this survey, we give an overview of the state of the art approaches for processing trip planning and scheduling queries. We compare these approaches from different angles like the number of users involved in a query (i.e., single or group), the type of the data space (i.e., Euclidean space/road networks/obstructed space), the sequence of POI types (i.e., fixed/flexible), static or dynamic, optimization parameters (i.e., distance/popularity) and privacy.