 | Beijing's Tongzhou District demonstrates how AI can turn isolated, fixed-time traffic signals into a coordinated and adaptive control network. This U4SSC case study situates the project within Beijing's 2024 "AI+ Strategy" and explains how real-time camera and detector data are used to optimise signal timing across intersections, road corridors and wider areas. The system switches among single-point adaptive control during off-peak periods, segmented "green-wave" coordination during transition periods, and regional coordination with peripheral traffic diversion during peak hours, while also applying targeted measures on congestion-prone roads. Post-deployment analysis reported a 15.6 per cent increase in average vehicle speed and a 32.5 per cent reduction in average travel time on major urban roads, alongside fewer conflicts and less congestion. The project is also developing into a broader Tongzhou "city brain". Remaining limitations concern the completeness and accuracy of data and the system's response to exceptional conditions. The case offers a practical model of dynamic, network-level traffic management while reinforcing the continuing need for data quality and human oversight.
More information available at: https://u4ssc.itu.int/
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