Soongsil University
Performance guarantees for Software-Defined Vehicles
Building the tools and theoretical foundations necessary to guarantee the functionality and real-time performance of software-defined vehicles in the real world, using simulations in cloud infrastructure.
Kanghee Kim
Soongsil University
Professor
Ongoing Research
- Probabilistic Timing Analysis for Autonomous Driving Stack
- Point Cloud Map Compression for Connected Intelligent Vehicles
- F1Tenth Premium with Autoware
Selected Publications
- “3-D Point Cloud Map Compression for Connected Intelligent Vehicles,” Youngjoon Choi, Hannah Baek, Jinseop Jeong, Kanghee Kim*, In IEEE Internet Computing, vol. 28, no. 1, pp. 53 – 60, 2024 (URL: https://www.computer.org/csdl/magazine/ic/2024/01/10360852/1SU1usYH840)
- “Minimizing Probabilistic End-to-end Latencies of Autonomous Driving Systems,” Taeho Han and Kanghee Kim*, In Proceedings of the 29th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’23), TX, US, May 2023 (URL: https://ieeexplore.ieee.org/document/10155682)
- “Probabilistically Guaranteeing End-to-end Latencies in Autonomous Vehicle Computing Systems,” Hyoeun Lee, Youngjoon Choi, Taeho Han, and Kanghee Kim*, In IEEE Transactions on Computers, vol. 71, no. 12, pp. 3361 – 3374, 2022 (URL: https://ieeexplore.ieee.org/document/9714832)