City Traffic Datasets for Metropolis-Scale Forecasting

Datasets intended for forecasting urban traffic at a metropolis scale. The specific number of records, data collection method, and temporal coverage are not provided in the available metadata. The data is hosted on Kaggle, but the author, organization, and last update date are unknown.

Use Cases

• Forecasting city-wide traffic flow based on the described metropolis-scale focus.
• Developing time-series models for urban congestion prediction.
• Benchmarking traffic forecasting algorithms against real-world urban data.

Strengths

• Focuses on metropolis-scale traffic, which is relevant for large-scale urban planning applications.
• Hosted on Kaggle, a platform with established data sharing and community features.

Limitations

• Row count and dataset size are unknown, which limits suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Geography

Metropolis-scale urban areas (inferred from description).