Vehicle Door Warning Logic for Occluded Rear Approaching Traffic

The detection system is segmented into two independent detection paths: one for stationary objects and one for mobile objects. Each path uses the same sensor but processes data independently with different algorithms. The stationary object detection identifies parked vehicles and other fixed obstacles, while the mobile object detection focuses on moving vehicles. This segmentation allows the system to apply appropriate filtering and validation rules to each type, reducing false detections while maintaining comprehensive coverage.

The system introduces an intermediary classification layer between object detection and warning issuance. When an object is detected ahead of the mobile object, the system uses image recognition and geometric analysis to determine whether it is a projection (such as an outer mirror) or a complete vehicle. This intermediary classification enables nuanced decision-making: projections do not suppress warnings, while complete stationary vehicles do. This resolves the contradiction by providing discriminative information that guides the warning suppression logic.

The system uses exterior cameras to capture visual information and analyze the appearance, shape, and context of detected objects. By examining visual characteristics such as vehicle color, shape contours, and positional relationships, the system can distinguish between actual vehicles and reflection artifacts. The image recognition algorithm identifies patterns consistent with vehicle projections versus complete vehicles, enabling accurate classification even when objects are detected through reflection by stationary objects.