Jaehyuck Lim
Ph.D. Student, Cho Chun Shik Graduate School of Mobility, KAIST
I am Jaehyuck Lim, a Ph.D. student at the KAIST Cho Chun Shik Graduate School of Mobility, TUPA Lab (Advisor: Prof. Inhi Kim). Majoring in Transportation Engineering, I primarily conduct research on humanoid-based sim-to-real transfer and human factor-centric traffic safety using immersive simulators.
Research
Humanoid
Sim-to-Real Transfer
Simulator-based Traffic Safety
News
Research
My research spans robot learning and traffic safety, connected by simulation as a common tool. (← Add a short overview paragraph here.)
Humanoid
Brief description of your humanoid research — what you study and your goal. (← Content to be updated.)
Sim-to-Real Transfer
Brief description of your sim-to-real transfer research — bridging simulation and the real world. (← Content to be updated.)
Simulator-based Traffic Safety
I build virtual road, traffic, weather, and vehicle environments to analyze driver behavior and safety experimentally, without exposing drivers to real-world danger. This approach makes it possible to recreate hazardous situations without actual crashes, and to present the exact same scenario repeatedly to every participant, so that comparisons between conditions are clear. It also allows road facilities or in-vehicle systems that have not yet been deployed on real roads to be evaluated in advance. As a result, this line of research is well suited to the early-stage design of new traffic-safety technologies and to the exploration of risk factors. The main topics I work on are as follows.
Road and Traffic Facility Safety
One or two sentences describing this study. (← To be updated.)
Driver State and Human Factors
One or two sentences describing this study. (← To be updated.)
Advanced Driver Assistance Systems and Autonomous Driving
One or two sentences describing this study. (← To be updated.)
Projects
Ongoing
Generative AI Leading Talent Cultivation Program
생성형 AI 선도 인재 양성 프로그램
Generative AI Leading Talent Cultivation Program
생성형 AI 선도 인재 양성 프로그램
Formally titled Development of Industry-Specific Physical AI Foundation Models and Cultivation of Next-Generation Convergence Talent, this IITP program runs from April 2026 to December 2029. Lotte Innovate leads the consortium, with KAIST, Yonsei University, and Inha University as joint research organizations, and Lotte affiliates — Korea Seven, Lotte E&C, Lotte Global Logistics, Lotte World, and others — serving as the field-demonstration and validation ground.
The core idea is to extend generative AI beyond the language and vision digital domain into the physical world — perception, reasoning, planning, action, and operation. The goal is to build an industry-specialized Physical AI foundation model while simultaneously training convergence-type talent, then dispatching and hiring top students into the affiliates so that research and industry feed each other.
- Period
- Apr 2026 – Dec 2029
- Role
- Lead Researcher
- Funding
- IITP
- Consortium
- Lotte Innovate; KAIST, Yonsei University, Inha University
Development of Virtual Environment and Demonstration Technology
for Automated Driving based on Metaverse
메타버스 기반 자율주행 가상환경 및 실증 기술 개발
Development of Virtual Environment and Demonstration Technology for Automated Driving based on Metaverse
메타버스 기반 자율주행 가상환경 및 실증 기술 개발
Part of MOLIT's autonomous-driving innovation program, this project (April 2023 – December 2027) builds a multi-purpose, variably extensible virtual test environment for Lv.4/4+ automated driving that serves three uses at once: training AV AI, verifying AV performance, and evaluating and certifying AVs. KATRI, the Korea Automobile Testing & Research Institute, leads the consortium; KAIST joins as a co-research organization alongside MORAI, Nota, NAVER LABS, and other industry partners.
The problem it addresses is that simulation today is built for developers, not for the people who have to certify a vehicle: scenarios are limited, formats are proprietary, and living-lab demonstration cannot be rehearsed safely. The target is a standardized, modular, open platform running large-scale parallel tests on hybrid cloud, with Korean road content and living-lab data behind it.
- Period
- Apr 2023 – Dec 2027
- Role
- Participating Researcher
- Funding
- MOLIT
- Consortium
- KATRI; KAIST, MORAI, Nota, NAVER LABS, and other partners
Past
No past projects yet.
Papers
Journal Papers
4Micro mobility safety challenges: a study on drivers overtaking bicycles and E-scooters in relation to road conditions and prior riding experience
The impact of information delivery systems in tunnels depending on lighting intensity and speed limit
Enhancing mutual understanding of e-scooter user's perspective in overtaking maneuver through replaying own driving trajectory
Advancements and prospects in multisensor fusion for autonomous driving
Conference Papers
4E-Scooter Alarm Warning System for Pothole Detection: A Simulation Study
The Impact of Head-Up Display Warnings on Aggressive Driving: Visual and Behavior Insights
Micromobility Safety Challenges: A Study on Drivers Overtaking Bicycles and E-Scooters According to Road Conditions and Cross-Modal Experience
The impact of information delivery systems in tunnels depending on lighting intensity and speed limit
Curriculum Vitae
Download my full curriculum vitae (PDF).
Download CVContact
193 Munji-ro, Yuseong-gu, Daejeon 34051, Republic of Korea