Projects

This project focuses on developing an industry-connected engineering education and research framework through the PRAXIS Next-Generation Engineer Program, led by Yonsei University in collaboration with five partner universities. The work concentrates on enabling undergraduate research teams to identify and solve real-world engineering problems in three strategic technology areas: semiconductors and displays, artificial intelligence, and advanced robotics and manufacturing. The project involves discovering industry-driven technical challenges, restructuring them into feasible research topics, matching student teams with faculty advisors and industry mentors, and supporting the research process through specialized training, research funding, infrastructure, and continuous mentoring. In addition, the program aims to translate research outcomes into prototypes, proof-of-concept demonstrations, patents, publications, technology transfer, follow-up industry collaborations, and career opportunities for participating students. The project ultimately seeks to establish a sustainable university–industry collaboration model that bridges academic knowledge and practical engineering experience while fostering next-generation engineers capable of creating meaningful technological and societal impact.

This research project aims to develop an AI-based origin–destination (OD) prediction framework to support future road policy planning and mobility service innovation. As emerging trends such as autonomous vehicles, electric vehicles, demographic changes, flexible work patterns, and regional mobility disparities reshape travel behavior, conventional demand forecasting methods face limitations in capturing uncertainty and dynamic behavioral changes. To address these challenges, the project proposes a scenario-based and data-driven forecasting framework that integrates heterogeneous mobility data, including telecommunications data, household travel surveys, and customized survey data. By applying advanced AI and data fusion techniques, the framework will estimate future OD demand, analyze changes in mode choice and travel behavior, and evaluate the impacts of emerging mobility services and infrastructure. The research will provide quantitative evidence for future highway policies and services, including autonomous public transport corridors, EV charging, transfer hubs, and demand-responsive mobility systems. Ultimately, the project seeks to enhance the adaptability, efficiency, and sustainability of Korea’s future highway network by supporting evidence-based decision-making under uncertain future mobility scenarios.

This project aims to develop sustainable policy strategies for South Korea's urban rail free-ride system amid rapid population aging and increasing financial pressures on urban rail operators. The research focuses on balancing the social benefits of fare-free travel for older adults with the long-term financial sustainability of public transportation services. The study quantifies the socioeconomic value of fare-free urban rail travel, including improvements in public health, reductions in traffic accidents and environmental costs, and increased local economic activity. Using travel behavior surveys, demand estimates, and socioeconomic data, the research estimates the annual social benefits of the current system and projects how these benefits may evolve under future demographic changes. In addition, the project evaluates alternative policy scenarios, including government cost-sharing mechanisms, adjustments to the eligibility age, and modifications to fare-free travel conditions. By analyzing their impacts on travel demand, operator finances, and social benefits, the research highlights the need for greater financial responsibility from the central government, rather than placing the entire burden on local urban rail operators. Ultimately, the project seeks to establish a sustainable funding and policy framework that preserves mobility rights and social welfare while ensuring the long-term financial stability of urban rail systems.

This project aims to validate the inter-operator fare settlement program and related research outcomes for the Seoul Metropolitan Transit System to improve the reliability and transparency of fare allocation among transit operators. The study involves comprehensive verification of network data, smart card data cleaning procedures, route search algorithms, and fare allocation calculations using real operational data and independent validation codes. Web crawling and algorithmic comparisons are conducted to assess the accuracy and rationality of route generation and settlement results, while inconsistencies and exceptional cases are identified and corrected through iterative feedback with development teams. The project seeks to confirm the reliability of the settlement framework and provide recommendations for enhancing route inference, exception handling, and future implementation of a daily settlement system.