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The sheer amount of video data that transportation researchers collect is overwhelming their ability to analyze and manage it. NREC wants to change this. (Above) Automatic car and sign detection.


NREC and FHWA are developing techniques for automatically analyzing large amounts of video collected from vehicles traveling on highways.

NREC engineers are applying powerful, flexible machine learning and image processing methods to analyze the vast collections of video, radar, ladar, and other sensor data that have been recorded on roads and highways. 

These techniques allow transportation researchers to automatically identify vehicles, detect road conditions, and extract other useful information from enormous highway datasets without the need for manual coding. 

The Federal Highway Administration (FHWA) awarded a $1 million grant to fund this two-year program.

Principal investigators: Dr. Brett Browning, Dr. J. Andrew (Drew) Bagnell
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