Makerere University On-Campus Mobility and Traffic Flow Dataset

This dataset contains 100,000 synthesized mobility and traffic-flow records generated to simulate on-campus movement patterns at Makerere University. It captures interactions between different campus zones, including academic buildings, services, entry gates, and junctions. Each record provides a timestamped observation of movement from an origin zone to a destination zone, along with the flow count and the mode of movement ,that is, car, motorcycle, bicycle, or pedestrian and contextual variables include weekday, weather conditions, semester phase, event presence, and gate entry or exit status.The dataset was created to support research in intelligent transportation systems, urban mobility modeling, anomaly detection and campus operations planning. It reflects structured, realistic flow behaviors across time such as peak-hour congestion, service area traffic and exam period spikes making it suitable for machine learning, statistical modeling, visualization and simulation studies. All records are fully synthetic and anonymized, containing no personally identifiable information.With its size, consistency and rich contextual features, this dataset can enable studies related to traffic prediction, temporal mobility analytics, campus route optimization, and smart campus management technologies. The CSV format ensures easy integration with Python or database workflows.