Abstract
Rapid rise in information and communication technology in various walks of life has helped digitization of human services, including transportation. The result of digitization is vast amount of location and time data on humans and goods, which in turn provide a valuable resource for transportation system performance for the managing and operating agencies. A wide variety of transportation performance metrics (TPMs) to characterize, evaluate and improve the performance towards making the operating agencies, and thereby the cities, ‘smart’ must be presented suitably to policy and decision makers. TPMs and data sources are of varying spatiotemporal extent and data formats, necessitating interoperability. Estimating TPMs requires a generic data warehousing framework handling various datasets, preferably, built in-house for the agencies to sustainably move towards smart city goals and meeting federal data reporting mandates. In this study, such a flexible data analytics framework is demonstrated via novel data ingestion and visualization outputs. Several use cases for evaluating efficiency, reliability and sustainability of transportation projects and system are presented.
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