Abstract
Intelligent transportation systems (ITS) are playing increasingly important roles in addressing traffic congestion, safety, and environmental concerns. Archiving and “reusing” the vast amounts of data initially collected by ITS for real-time operations holds the potential to significantly improve a wide range of transportation analyses. Effectively archiving and deriving information from ITS data requires the application of technology and algorithms recently developed and proven in research. This paper describes and summarizes this research, particularly in areas such as data warehousing, complex systems development, traffic data aggregation, traffic data imputation, and traffic data characterization. The paper concludes with a list of key future research needs required to allow expanded use of ITS data archives.
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