Research Project Title:
Classifying Traffic Camera Data at-Scale for Transportation System Resilience
abstract:There is a growing need for efficient transportation operations and communications, especially for urban emergency evacuation scenarios such as natural disasters and severe weather conditions. The goal of this SuperUROP project is to build a convolutional neural network using the Python-based Tensorflow framework for traffic-related objects using publicly-available semi-unstructured camera data from MassDOT and CalTrans. The model will be used to classify over a million images for future transportation modeling research about disruptions on critical transportation facilities due to natural events.
"I am participating in the SuperUROP program for the opportunity to apply machine learning techniques (6.036) to real traffic data. I hope to improve my programming skills and machine learning knowledge and contribute to interesting research about urban transportation."