Traffic

A hierarchical control framework is developed to optimize traffic management across large urban networks by balancing traffic demand and improving network-wide efficiency

The LiDAR-based system enhances pedestrian safety by real-time detection and signal timing adjustment.

This system provides real-time queue length estimation using traffic video analysis, improving signal timing and congestion assessments.

The project designs software for traffic signal optimization at various scales, from single intersections to large road networks, focusing on reducing delays and improving flow efficiency.

This project develops techniques for real-time traffic data processing and prediction, leveraging big data and multi-level urban road network models to improve urban traffic management.