Atsushi Yano
Papers
1
Total Citations
4
H-Index
1
About
Atsushi Yano is a researcher focused on real-time systems and autonomous driving, with particular expertise in scheduling and timing analysis for safety-critical applications. His most cited work, "Work-in-Progress: Multi-Deadline DAG Scheduling Model for Autonomous Driving Systems" (2024), addresses a critical challenge in Autoware—an autonomous driving platform built on ROS 2. Yano identified that existing cause-effect chain models for end-to-end latency analysis fail to capture the intricate dependencies in Autoware's task graphs. To solve this, he proposed a multi-deadline Directed Acyclic Graph (DAG) scheduling model that more accurately represents real-world timing constraints, ensuring safer and more predictable autonomous operations. Though early in his career, his work has already garnered attention (4 citations), highlighting its relevance to the growing field of autonomous systems. Yano's contributions bridge the gap between theoretical scheduling models and practical implementation, offering a foundation for future research in real-time guarantees for complex robotic systems. His research promises to enhance the reliability of autonomous driving, making him a rising voice in embedded and cyber-physical systems.
Research Focus
Key Achievements
Top Papers
- 1