الفهرس 
Road safety ranking using deep learning and full consistency method in greater cairo region
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Abstract
This is the first research in Egypt that applies deep learning object detection and FUCOM to automatically evaluate and score roads safety in GCR. A deep artificial network object detector is trained to efficiently detect road objects in a front-facing camera image, then FUCOM was used to determine safety weights for ten key safety indicators (KSIs) using a panel-expert survey. QGIS was then used to visualize and spatially analyze the results to demonstrate the effectiveness of the proposed approach. The results indicate that adequate pavement markings and traffic signs, and less billboards and enforcement of heavy vehicles, have the potential to improve roads safety in GCR.