Knowledge Graph-Based Methods for Automated Driving

1. Knowledge graph-based methods for automated driving2. An overview of knowledge representation learning based on ER knowledge graph3. Emerging technologies and tools for knowledge gathering in automated driving4. Awareness of safety regulations and standards for automated driving5. Reliability and ethics developments in knowledge graphs for automated driving6. Role of knowledge graph-based methods in human-AI systems for automated driving7. Knowledge-infused learning: A roadmap to autonomous vehicles8. Integrated machine learning architectures for a knowledge graph embeddings (KGEs) approach9. Future trends and directions for knowledge graph embeddings based on visualization methodologies10. A brief study on evaluation metrics for knowledge graph embeddings11. Design, construction, and recent advancements in temporal knowledge graph for automateddriving12. Knowledge graph-based question answering (KG-QA) using natural language processing13. An integrated framework for knowledge graphs based on battery management14. Ontology-based information integration standards for the automotive industry15. Emerging graphical data management methodologies for automated driving16. Knowledge graphs vs collision avoidance systems: Pros and cons17. Autonomous vehicle collision prediction systems: AI in action with knowledge graphs18. Risk assessment based on dynamic behavior for autonomous systems using knowledge graphs19. Case studies on knowledge graphs in automated driving