Scene Graph Driven Context Query Generation: A Focus on Diversity and Situation-Specific Queries

This study introduces a novel scenario-based context query generation approach to evaluate data digestion performance of CMPs. Real-world scenes are modeled as context-aware scene graphs using ontology-based knowledge. This approach integrates ontological knowledge, sensor data, and real-world images to comprehensively represent urban road sit-uations. We infer dynamic situations from the scene graph, forming the basis for generating diverse queries. A template-based query generation method ensures a range of queries with varying complexity.