Korea Advanced Institute of Science and Technology · Engineering
Professor Jinwoo Lee's research lab specializes in sustainable transportation systems and smart mobility solutions, focusing on optimizing urban infrastructure for electrified and aerial transportation. The lab develops advanced decision-support frameworks for electric and urban air mobility (UAM) systems, integrating dynamic optimization, queueing theory, and continuum approximation methods to enhance system efficiency and environmental performance. Key research directions include the planning of electric vehicle charging networks, battery electric bus systems, and shared mobility services, with an emphasis on reducing greenhouse gas emissions and improving serviceability. The lab combines analytical modeling with real-world case studies to address operational uncertainties and spatial heterogeneity in urban environments.
Figures are computed from collected data and may differ slightly.
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
Open papers in the app to read, cite, and organize with AI.
