Jinwoo Lee
KAIST 건설환경공학부 · 공학
Jinwoo Lee 교수의 연구실은 지속 가능한 이동수단과 스마트 인프라 설계를 중심으로 한 교통 시스템 최적화 연구를 수행합니다. 주로 전기버스, 도시 공중 이동(UAM), 공유 이동 서비스 및 전기차 충전 인프라의 계획 및 운영 최적화에 초점을 맞추며, 환경적 영향 감소와 시스템 효율성 향상을 동시에 추구합니다. 동적 프로그래밍, 연속근사법, 큐잉 이론 등을 활용한 수리적 모델링과 실증 사례 기반 분석을 융합한 혁신적인 의사결정 지원 프레임워크를 개발하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
We present a methodology for the joint optimization of flexible pavement maintenance, rehabilitation and reconstruction (MR&R) activities. The majority of existing Pavement Management Systems do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damages in the underlying layers (base, sub-base or subgrade). We
Shared mobility is a service that allows users to share various transportation modes and use them with reservations when necessary. It started with private automotive car-sharing and ride-sharing services. Currently, it operates on a wider range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting the usage intention of both current and pr
This paper presents an optimized decision-support framework for the planning and operation of Urban Air Mobility (UAM) systems. Alleviating traffic congestion in metropolitan areas has been a persistent challenge for decades, leading to increased interest in aerial mobility solutions. Recent advancements in distributed electric propulsion, battery technology, and autonomous navigation have made electric vertical take-off and landing (eVTOL) aircraft a feasible option for intercity transport. For
The high contribution of greenhouse gas (GHG) emissions by the transportation sector calls for the development of emission reduction efforts. In this paper, we examine how efficient bus transit networks can contribute to these reduction measures. Utilizing continuum approximation methods and a case study in Barcelona, we show that efforts to decrease the costs of a transit system can lead to GHG emission reductions as well. We demonstrate GHG emission comparisons between an optimized bus network
Battery electric buses (BEB) have attracted attention as future eco-friendly public transit. However, planning a large-scale BEB system is challenging, with additional constraints related to charging facilities and batteries. We present a bi-objective decision-making framework to minimize the overall cost and greenhouse gas emissions, robust to operational uncertainty and applicable to various real-world scenarios. We propose a tractable queuing-theoretic solution method to determine three optim