Jaehyun Mo
Papers
1
Total Citations
3
H-Index
1
About
Jaehyun Mo is a researcher focused on advancing automotive safety through intelligent vehicle systems, particularly in the domain of collision avoidance and autonomous driving validation. His primary research areas include vision-based driver assistance technologies, robust testing methodologies for safety-critical systems, and the development of driverless validation frameworks. Mo’s major contribution lies in his work on the oncoming vehicle collision avoidance system, where he proposed a novel driverless test method to rigorously validate and improve system performance under realistic scenarios. His 2018 paper, "Development of Robust Validation Method through Driverless Test for Vision-based Oncoming Vehicle Collision Avoidance System," has garnered 3 citations, reflecting its niche but important impact on the field of automated vehicle safety testing. By integrating front-camera sensing with systematic validation protocols, Mo’s research helps bridge the gap between simulation and real-world deployment, offering a pathway toward more reliable collision avoidance systems. His work is particularly relevant for researchers and engineers developing next-generation autonomous vehicle technologies, where robust validation remains a critical challenge.
Research Focus
Key Achievements
Top Papers
- 1