Bigdata Analytics and Artificial Intelligence for Smart Intersections

Principal Investigator: Sanjay Ranka

Sponsor: Florida Department of Transportation

Start Date: June 14, 2019

End Date: June 30, 2022

Amount: $749,360


The rapid changes in growth of exploitable and, in many cases, open data have the potential to mitigate traffic congestion and improve safety. Despite significant advances in vehicle technology, traffic engineering practices, and analytics based on crash data, the number of traffic crashes and fatalities are still too many. Many drivers are frustrated due to long (but potentially preventable) delays at intersections. The use of video/LIDAR processing, big data analytics, artificial intelligence, and machine learning can profoundly improve the ability to address these challenges. The collection and exploitation of large data sets is not new to the transportation sector. However, the confluence of ubiquitous digital devices and sensors, significantly lower hardware costs for computing and storage, enhanced sensing and communication technologies, and open-source analytics solutions have enabled novel applications through specific uses and by combining with other data sources. The latter may involve insights into otherwise unobserved patterns that may positively influence individuals and society.

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