An IVHS (Intelligent Vehicle Highway System) information management obtains information from road sensors, city maps and event schedules, and generates information to drivers, traffic controllers and researchers. The authors extend the relational database to model traffic information in a relational database by abstract data types and triggers. Abstract data types are needed for efficient modeling of spatial and temporal information, which create inefficiencies in traditional databases. The authors use monotonic continuous functions to map the object locations to disk addresses to save disk space and computation time. Model of spatial data is created to efficiently process moving objects. Schema for IVHS databases are provided, with the relevant abstract data types. The authors also have a large sample of the relations needed to model IVHS data. Several interesting queries are presented to show the power of the model. Triggers are defined, using rule-definition mechanisms to represent incident detection and warning systems. An efficient physical model with MoBiLe access method is provided.
Abstract