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Abstract

A railroad crossing blockage detection and notification system gathers emergency call data and/or infrastructure sensor data and uses the data to generate a blockage score that is representative of a likelihood of a railroad blockage at a railroad crossing. The system may include and use a machine learning model to generate the blockage score. Using historical train collision data, the machine learning model may be trained on emergency call data and/or on infrastructure sensor data available in proximity to railroad crossing. The system may receive current emergency call data and/or infrastructure sensor data, may apply the data to the machine learning model to generate a likelihood of a blockage, and may notify emergency communication centers (ECCs), network operations centers (NOCs), emergency responders, and/or train systems of the potential blockage. In response to a potential blockage, a train may be slowed down or stopped to reduce the likelihood of a collision.

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