Urban Traffic Flow Patterns in Sao Paulo

Time-series data captures traffic behavior patterns in Brazil's largest city. The dataset is hosted on the UCI Machine Learning Repository and includes platform tags indicating its use for transportation planning. Specific details on the number of records and collection period are not provided.

Use Cases

• Predict traffic flow levels based on time-series patterns and urban features.
• Analyze congestion trends in Sao Paulo using recorded traffic behavior metrics.
• Model the relationship between time of day and urban traffic intensity for planning.

Strengths

• Hosted on the curated UCI Machine Learning Repository, indicating a level of vetting.
• Focuses on a major global metropolis, providing data from a complex urban environment.

Limitations

• Unknown sample size and temporal coverage limit assessment of statistical power.
• Lack of documented column names and specific data features restricts detailed analysis.

Provenance

Source

UCI Machine Learning Repository

Geography

Sao Paulo, Brazil