How is real-time data used in traffic prediction?

How is real-time data used in traffic prediction?

Real-time data is crucial for traffic prediction as it helps analyze current conditions, such as vehicle speeds and congestion.

What types of real-time data are typically collected?

Common types include GPS data from vehicles, traffic camera feeds, and sensor data from roadways.

How does this data improve traffic management?

It allows for dynamic routing, timely updates to drivers, and better resource allocation for traffic control.

Are there any challenges in using real-time data?

Yes, challenges include data accuracy, integration from multiple sources, and ensuring privacy.