Adaptive Edge Intelligence for Intersection Safety: Real-Time Dilemma Zone Management via DV-EISOS

Dilemma zone (DZ) protection is vital for intersection safety, yet legacy detectors often lack the spatial resolution and responsiveness needed to track fast-changing vehicle dynamics. This paper presents DV-EISOS, an edge-deployed, vision-driven system for real-time DZ detection and adaptive signal control. Running on Jetson AGX Orin, DV-EISOS integrates YOLOv8 for vehicle detection, ByteTrack for multi-object tracking, homography-based mapping, and time-to-intersection logic to convert RTSP camera feeds into actionable kinematic metrics with millisecond-level latency. Through an NTCIP/SNMP interface, the system issues yellow-phase extensions only when approaching vehicles are assessed as high risk. A field deployment at a signalized intersection in Bellevue, WA demonstrated accurate speed estimation (RMSE < 2 mph), timely phase adaptation, and responses to ~10% of potential DZ events. These results indicate that edge AI can deliver scalable, low-latency safety control using existing cameras in real-world urban environments.