What are the main challenges in traffic forecasting?

What are the main challenges in traffic forecasting?

Some key challenges include data quality, real-time processing, and the unpredictability of human behavior.

How does data quality affect traffic forecasting?

Data quality impacts the accuracy of predictions; poor data can lead to incorrect forecasts and misinformed decisions.

What role does machine learning play in overcoming these challenges?

Machine learning helps by analyzing large datasets to identify patterns, improving prediction accuracy over time.

Can you give examples of real-world applications of traffic forecasting?

Sure! Applications include smart traffic lights, route optimization for delivery services, and urban planning.