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Leveraging big data - Predicting traffic risk and providing early warning due to adverse weather conditions

Authors: Sreekumar Nampoothiri*, SUNY - Albany
Topics: Urban and Regional Planning, Climatology and Meteorology, Transportation Geography
Keywords: Big data, traffic, weather, early warning
Session Type: Paper
Presentation File: No File Uploaded


Big data has become a ubiquitous term in most major areas of life today. The transportation sector had been one of the early adopters in using the potentials of big data by developing applications that can detect the amount and speed of traffic on different roads and provide the information to users and facility managers. Past research has shown direct relationships among speed, volume, congestion, adverse weather conditions, and traffic incidents. However, these have been derived mostly from static data that were spatially and temporally sparse or collected on a specific facility for research purposes. The availability of big data has presented an opportunity to not only do such analyses with higher resolution but to perform deeper analyses that can potentially bring out more nuanced insights. This research combines traffic and weather conditions data for three different types of road segments in the Capital Region of New York at different time-of-day and seasonal granularity to understand weather conditions and the link between these conditions and traffic speed in order to provide timely advanced warning to travelers. In addition, the research demonstrates that the big data indeed provide an advantage over the simple datasets that are commonly available. The findings are expected to improve traffic risk prediction during severe weather conditions and provide early warnings.

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