SIL Environment Development Engineer, Autonomous Driving

Our team specializes in developing and advancing cutting-edge Software-in-the-Loop (SIL) environments to accelerate the evolution of autonomous driving technology. We utilize two key SIL environments, ClosedSILS and OpenSILS, leveraging their unique characteristics to efficiently evaluate and validate software. Additionally, we focus on addressing shared challenges, such as improving processing speeds, which are essential for enhancing development efficiency.

In ClosedSILS, the simulator is connected to the autonomous driving software in real time, forming a feedback loop that enables dynamic evaluation of vehicle dynamics and control logic. This environment is designed with precision in mind, as we strive to improve the accuracy of simulation models while ensuring that generated signals are correctly linked to actual vehicle behavior. Furthermore, we are implementing computational optimizations and load reduction techniques to accelerate the simulation process. These enhancements aim to boost both the speed and reliability of testing, thereby significantly improving the overall development workflow.

OpenSILS, on the other hand, leverages on-road driving log data to validate software behavior in an offline setting. A key focus here is achieving high fidelity in reproducing real-world phenomena, such as communication delays or processing delays caused by CPU load observed in physical environments. OpenSILS doesn't simply replay log data—it integrates adjustments based on the load and timing conditions recorded during real-world operation. This approach enables the environment to replicate situations under conditions that closely mirror those of the original vehicle. By doing so, we can analyze issues that occurred during physical testing, pinpoint underlying causes, and effectively drive improvements in software development.

A shared challenge across both ClosedSILS and OpenSILS is the need for faster processing. By optimizing real-time capabilities within the simulation environments, we aim to deliver highly efficient testing platforms that drastically accelerate software development cycles. These ongoing initiatives address critical issues of safety and reliability in autonomous driving technology while laying the foundation for future-focused development.

Our activities integrate simulation modeling, real-world data analysis, embedded system design, and comprehensive software development, creating an optimal environment for autonomous driving innovation. Working in this challenging yet rewarding setting will enable engineers to grow their skills while contributing to foundational advancements in next-generation mobility technology.

Commitment to Improving Accuracy: A deep understanding of simulation models and a drive to enhance the linkage precision between simulated signals and actual vehicle behavior