On September 8th, news from Jiangsu indicates that, facing the reality of near-saturated traffic flow on its highway network, the region is exploring "substituting computing power for transport capacity," using digital methods to unlock the potential of existing road networks and chart a new path of intensive expansion.

　　Jiangsu's expressway infrastructure has exceeded 5,500 kilometers in operational length, with an average daily outbound traffic flow of nearly 2.45 million vehicles. Locally, an "air-view-ground" three-dimensional perception matrix has been established, integrating high-definition surveillance, radar-vision fusion equipment, and drone inspections. Relying on the "Su Expressway · Little Jasmine" EI road network intelligent agent, real-time recognition and early warning of road surface incidents is achieved at the second level. To filter out invalid alerts, a "triple governance" approach involving machinery, business operations, and manual oversight has been implemented. Additionally, the "One Road, Three Parties" collaborative command platform has been upgraded, introducing a three-tier early warning response system for high traffic volumes, allowing dynamic control measures such as lane-specific speed limits, ramp flow restrictions, and flexible activation of emergency lanes.

　　Data shows that, after the upgrade, traffic congestion duration on Jiangsu's highways has decreased by 48.7%, the average response time for obstacle removal and rescue has been compressed to within 8 minutes, and the proactive detection rate for abnormal incidents has reached 89.3%. This AI-based analysis and control technology has been exported to 20 provinces nationwide, serving 80,000 kilometers of roads, and providing a practical Jiangsu example for ensuring smooth and efficient traffic on high-density road networks across the country.