Traffic centers gather information from traffic sensors at regular intervals, but storing the data for future analysis
becomes an issue. This report details work to improve the speed and effectiveness of traffic databases.
In this project phase, researchers redesigned the data model based on the previous phase's data model and decreased
the storage requirements by one-third. Researchers developed a web-based Graphical User Interface (GUI) for users
to specify the query of interest; the outcome of the performance tuning gave users reasonable response time.
The beneficiaries of this effective database would include the driving public, traffic engineers, and researchers, who
are generally not familiar with the query language used in the database management system. This report summarizes
the detailed reference, such as benchmark query, sample data, table schema, conversion code, and other information.
Kaur, Sarbjit Sing; Eriksson, Martin; Papanikolopoulos, Nikolaos P..
Automatic Detection of Driver Fatigue - Phase 3.
Minnesota Department of Transportation.
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