Dataset for the Study of Urban Morphology and Morning Traffic Congestion in Beer Sheva

This dataset was collected as part of a seminar research project at Tel Aviv University examining the relationship between urban morphology and morning traffic congestion in residential neighborhoods in Beer Sheva, Israel. The dataset combines street network metrics derived from OpenStreetMap using OSMnx with traffic measurements collected from the Google Maps API. Variables include network connectivity measures, topological indicators, demographic characteristics, and congestion metrics calculated from observed travel times during morning peak hours. Traffic data collection was performed using the Google Maps Traffic Scraper (gmaps-scraper):https://github.com/gilfriedman/gmaps-scraper Street network extraction, neighborhood exit identification, and network analysis were performed using the Traffic Network Analyzer:https://github.com/gilfriedman/traffic-network-analyzer The dataset was created for the research project "Urban Morphology and Morning Traffic Congestion in Beer Sheva" conducted within the Smart Cities seminar course at Tel Aviv University.