A Traffic Data Management System for Navigation, Collision Detection, and Incident Detection
1994-06
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A Traffic Data Management System for Navigation, Collision Detection, and Incident Detection
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1994-06
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Minnesota Department of Transportation
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Report
Abstract
A traffic data management system is an integral part of an IVHS (Intelligent Vehicle Highway System), which obtains information from road sensors, city maps and event schedules, and generates information to drivers, traffic controllers and researchers. We extend the relational database with abstract data types and triggers to model traffic information in a relational database. Abstract data types are needed to efficiently model spatial and temporal information, since they may create inefficiencies in traditional databases. We use monotonic continuous functions to map the object to disk addresses to save disk space and computation time. A model of spatial data is created to efficiently process moving objects. For IVHS databases, we provide schema that have the relevant abstract data types. We 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 the MoBiLe access method is provided.
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This research was supported by the Center for Transportation Studies and the Minnesota Department of Transportation under the GUIDESTAR project.
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Shekhar, Shashi; Hancock, Peter A.. (1994). A Traffic Data Management System for Navigation, Collision Detection, and Incident Detection. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/241868.
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