SmartWays is an academic mini-project focused on optimizing urban traffic flow through machine learning techniques and dynamic signal scheduling.
- ML-Based Congestion Prediction - Utilizes real-time or historical traffic data to estimate congestion levels.
- Automated Traffic Light Switching - Adjusts signal transitions automatically based on predicted congestion.
- Priority Round-Robin Scheduling - Ensures fair and efficient lane-wise traffic distribution.
- Dynamic Quantum Adjustment - Allocates green-signal duration adaptively to match traffic density.
- Emergency & High-Density Lane Prioritization - Gives priority to critical lanes to reduce delays and prevent bottlenecks.