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Moving objects with multiple transportation modes

The new applications on detecting transportation modes and advanced trip recommendations make it crucial to investigate moving objects with different transportation modes. Practically, the complete trip of a person can cover several real world environments such as road network, bus network and indoor. However, in the database community, existing methods focus on a single environment and can only manage a sub trip of the continuous movement. Consequently, moving objects passing through various environments are not represented in a database system, and novel queries regarding transportation modes cannot be supported. The aim of the thesis is to (1) define a data model that represents moving objects with different transportation modes in a database system; (2) provide efficient query processing mechanisms enabling to support novel queries; (3) evaluate the performance of such a database system called GMOD (Generic Moving Objects Database) that manages complete trips for humans. Towards this goal, at first we propose a generic method that is able to represent the location of a moving object in all environments. Since each environment consists of a set of geographic objects, a group of data types is designed to represent them. A data type for generic moving objects is defined where the location is represented by referencing to geographic objects. Afterwards, a set of operators is proposed to efficiently access the data. Definitions of both syntax and semantics are given. The proposed operators are also used to formulate queries. The data model is implemented in a database system. In order to evaluate the performance of GMOD, a tool is developed to create real world environments based on roads and floor plans. All underlying geographic objects such as roads, buses, and buildings are managed by GMOD. Within each environment, a graph as well as the algorithm is proposed for the shortest path searching, e.g., trip planning for pedestrians, indoor navigation. A complete navigation algorithm is provided to find a route through several environments. As a second step, such a route is used to produce a moving object with different transportation modes. To simulate human behavior in a realistic scenario, some rules are defined to model movement patterns such as commuting, searching the nearest interesting place. The tool is extended to create comprehensive and scalable benchmark datasets for GMOD. A set of benchmark queries is proposed and optimization techniques are also developed. We conduct an extensive experimental study to evaluate the performance of GMOD and demonstrate the effectiveness and efficiency of proposed approaches.