We develop an in-vehicle multimodal AI agent that models five-dimensional human states, task demands, and driving context. It improves autonomous driving experience and supports non-driving tasks through physical human–vehicle collaboration.

Real-time, context-aware Human–AI teaming guidelines and a prototype system for hybrid human–unmanned operations, designed to improve human decision-makers’ situation awareness and trust.

This project aims to develop an AI-based human modeling and digital twin system for user-centered design of autonomous driving environments.

This research presents the development of the RMS (real-time motion sickness scale), a practical evaluation tool that measures motion sickness accurately and in real time within the driving environment. 

This research proposed a system that provides personalized driving experiences in autonomous vehicles by learning the driver's driving tendencies, emotional state, external environment, and driving context. Additionally, the research aims to develop a framework for the comprehensive evaluation and management of this system. To achieve this, the study proposes an X-Meta methodology, which combines meta-learning with explainable artificial intelligence (XAI) algorithms for system design.

This project propose a new framework that integrates data analysis extracted from social media with user experience methodologies, enabling the derivation of use cases that reflect user needs for future services. By analyzing domestic social media data, we aim to derive use cases that incorporate the specific demands of Korean users within autonomous vehicles.

In the project 'Research and Development of Required Technologies and Demonstration Aircraft for Low-Observable Unmanned Squadron,' the first phase was conducted to verify the potential for manned-unmanned collaborative operations of unmanned squadrons. During this phase, a virtual prototype system was developed to demonstrate the operational concept and mission scenarios for manned-unmanned mixed formations, and to analyze mission effectiveness. A UI design proposal was presented based on human factors engineering principles and the user (pilot) context of use.

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A feedback and training system for eco-friendly driving was developed to help drivers achieve comfortable and fuel-efficient driving. Research was conducted to deliver information efficiently and effectively through visual, auditory, and haptic modalities without distracting the driver.

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This project provides a new experience in the forest, allowing individuals to immerse themselves in nature while escaping the routine of everyday life. The goal is to offer relaxation and revitalization. Additionally, the project aims to develop technology that enhances positive emotions by employing media art, participatory interactive art, and emotional visualization, all of which transform inner experiences into works of art.