Our goal is to optimize traffic flow in large cities
by developing an urban traffic brain system that provides traffic control intelligence
through large-scale traffic simulation and cloud-edge based real-time traffic analysis
Main Goal
Average travel time reduction rate: over 15%
Number of optimized signal intersections: over 200
Support cloud-edge based distributed processing of multi-agent signal optimization
Number of signal optimization visual analysis modules: over 2
Congestion propagation prediction accuracy: over 0.85 (F1-score )
Traffic demand estimation error: under 10% (MAPE)
Research Area
Development of traffic network signal optimization technology and scalable simulation technology to verify the ripple effect of the entire city through edge-cloud collaboration
Development of traffic situation recognition and prediction technology through edge-cloud and edge-edge collaborations
Cloud-based data collection, conversion, and management using various public and private traffic data
Visual tool support for edge-to-cloud collaborative traffic monitoring and city-wide ripple effect analysis of signal optimization
Cloud-edge virtualization technology that enables dynamic expansion of urban traffic brain
The results of the development of the urban traffic brain are applied to local government signal control and traffic infrastructure to practice
Service
UNIQ is the cloud-edge based City-traffic Brain technology that solves the traffic congestion problem.
Traffic Signal Optimization
Large-scale traffic network optimization using artificial intelligence technology
