: Evaluating city-wide congestion patterns in San Francisco during the period of January to August 2022.
: Using loop detector counts (volume and occupancy) from San Francisco streets and highways to train machine learning models. File: SFMDH_2022_Loops_Jan-Aug.zip ...
The data is typically associated with research papers or projects that utilize real-world traffic data for: : Evaluating city-wide congestion patterns in San Francisco
: Calibrating simulation tools like SUMO (Simulation of Urban MObility) or AIMSUN using high-resolution sensor data. File: SFMDH_2022_Loops_Jan-Aug.zip ...