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Hwasoo Yeo

Korea Advanced Institute of Science and Technology · 工学

研究室紹介

Professor Hwasoo Yeo's research lab specializes in intelligent transportation systems, with a focus on traffic flow modeling, travel-time prediction, and the integration of emerging technologies such as autonomous vehicles and big data analytics. The lab investigates critical transportation challenges including oversaturated traffic conditions, capacity drop at highway bottlenecks, and accessibility to healthcare services through advanced geo-spatial analysis. By leveraging trajectory data and machine learning techniques—particularly recurrent neural networks with attention mechanisms—the lab develops data-driven solutions for urban mobility and traffic safety. The research also explores operational strategies such as AV-only lanes to enhance efficiency and safety in mixed-traffic environments.

traffic flow modelingautonomous vehiclestrajectory predictiontravel-time estimationurban mobility

Research Overview

Papers
197
Total Citations
3,246
Papers (5y)
42
Primary Field
工学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
42total
2022
2023
2024
2025
2026
Citations per year (5y)
304total
20222023202420252026

Selected Papers

15
1
Review|126 citations·2015
Short-term Travel-time Prediction on Highway: A Review of the Data-driven Approach
Simon Oh, Young-Ji Byon, Kitae Jang, Hwasoo Yeo
SJR Q1Transport Reviews

Near future travel-time information is one of the most critical factors that travellers consider before making trip decisions. In efforts to provide more reliable future travel-time estimations, transportation engineers have examined various techniques developed in the last three decades. However, there have not been sufficiently systematic and through reviews so far. In order to effectively support various transportation strategies and applications including Intelligent Transportation Systems (

Building and ConstructionEngineering
2
Book Chapter|109 citations·2009
Understanding Stop-and-go Traffic in View of Asymmetric Traffic Theory
Hwasoo Yeo, Alexander Skabardonis
Control and Systems EngineeringEngineering
3
Article|96 citations·2008
Oversaturated Freeway Flow Algorithm for Use in Next Generation Simulation
Hwasoo Yeo, Alexander Skabardonis, John Halkias, James Colyar, Vassili Alexiadis
SJR Q2Transportation Research Record Journal of the Transportation Research Board

Existing simulation models have difficulty in accurately modeling oversaturated traffic conditions on freeways. A new behavioral algorithm for oversaturated freeway flow can be used in microscopic simulation models; it was developed as part of the Next Generation Simulation (NGSIM) project, sponsored by FHWA. The proposed algorithm is an integrated car-following and lane-changing modeling framework that is consistent with the kinematic wave theory. The algorithm can explicitly model mandatory an

Control and Systems EngineeringEngineering
4
Article|96 citations·2018
Enhancing healthcare accessibility measurements using GIS: A case study in Seoul, Korea
Yeeun Kim, Young-Ji Byon, Hwasoo Yeo
SJR Q1PLoS ONEOA

With recent aging demographic trends, the needs for enhancing geo-spatial analysis capabilities and monitoring the status of accessibilities of its citizens with healthcare services have increased. The accessibility to healthcare is determined not only by geographic distances to service locations, but also includes travel time, available modes of transportation, and departure time. Having access to the latest and accurate information regarding the healthcare accessibility allows the municipal go

TransportationSocial Sciences
5
Article|72 citations·2019
Impact of Autonomous-Vehicle-Only Lanes in Mixed Traffic Conditions
Hwapyeong Yu, Sehyun Tak, Minju Park, Hwasoo Yeo
SJR Q2Transportation Research Record Journal of the Transportation Research Board

The introduction of autonomous vehicles (AVs) in the near future will have a significant impact on road traffic. AVs may have advantages in efficiency and convenience, but safety can be compromised in mixed operations of manual vehicles and AVs. To deal with the issues associated with mixed traffic and to avoid its negative effects, a special purpose lane reserved for AVs can be proposed to segregate AVs from manual vehicles. In this research, we analyze the effect on efficiency and safety of AV

Control and Systems EngineeringEngineering
6
Article|66 citations·2012
Estimation of Capacity Drop in Highway Merging Sections
Simon Oh, Hwasoo Yeo
SJR Q2Transportation Research Record Journal of the Transportation Research Board

Capacity drop, which is defined as discharge flow drop after bottleneck activation, has been frequently observed on urban highways, especially in merging sections. Maintaining high capacity on roadways is a main concern for traffic operators, theorists, and transportation modelers. Accordingly, many researchers have investigated capacity drop, yet highway capacity and discharge flow measurement methods vary, and results are not comparable. A systematic methodology is introduced for finding capac

Control and Systems EngineeringEngineering
7
Article|65 citations·2016
A comparative study of time-based maintenance and condition-based maintenance for optimal choice of maintenance policy
Jeongyun Kim, Yongjun Ahn, Hwasoo Yeo
SJR Q1Structure and Infrastructure Engineering

Cost-effective maintenance of infrastructure systems within an acceptable level of safety and performance is the major concern of managing agencies. Recent maintenance approaches have offered two distinct maintenance policies: time-based maintenance (TBM) and condition-based maintenance (CBM). This paper compares the two policies under different cost environments for stochastically deteriorating infrastructures. The performance of TBM and CBM is evaluated from the viewpoint of condition transiti

Safety, Risk, Reliability and QualityEngineering
8
Article|65 citations·2019
Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction
Seongjin Choi, Jiwon Kim, Hwasoo Yeo
Procedia Computer ScienceOA

As the number of various positioning sensors and location-based devices increase, a huge amount of spatial and temporal information data is collected and accumulated. These data are expressed as trajectory data by connecting the data points in chronological sequence, and these data contain movement information of any moving object. Particularly, in this study, urban vehicle trajectory prediction is studied using trajectory data of vehicles in urban traffic network. In the previous work, Recurren

TransportationSocial Sciences
9
Article|61 citations·2015
An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles
Yongjun Ahn, Hwasoo Yeo
SJR Q1PLoS ONEOA

The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by di

Electrical and Electronic EngineeringEngineering
10
Article|59 citations·2012
Impact of traffic states on freeway crash involvement rates
Hwasoo Yeo, Kitae Jang, Alexander Skabardonis, Seungmo Kang
SJR Q1Accident Analysis & Prevention
Safety, Risk, Reliability and QualityEngineering
11
Review|59 citations·2017
Short-term travel-time prediction on highway: A review on model-based approach
Simon Oh, Young-Ji Byon, Kitae Jang, Hwasoo Yeo
SJR Q2KSCE Journal of Civil Engineering
Building and ConstructionEngineering
12
Article|59 citations·2014
Logistic regression model for discretionary lane changing under congested traffic
Minju Park, Kitae Jang, Jinwoo Lee, Hwasoo Yeo
SJR Q1Transportmetrica A Transport Science

AbstractAssessing the probability of lane-changing (LC) is essential to traffic simulation for more realistic representation of complicated traffic phenomena in congested traffic. Discretionary lane changes (DLC), which are not required for reaching a destination, are decided by drivers for the purpose of faster travel. The probability of DLC is related to the speed difference and density difference between adjacent lanes. To reveal the characteristics of DLC, we aggregated Next Generation Simul

Control and Systems EngineeringEngineering
13
Article|55 citations·2012
Algorithms for bottom-up maintenance optimisation for heterogeneous infrastructure systems
Hwasoo Yeo, Yoonjin Yoon, Samer Madanat
SJR Q1Structure and Infrastructure Engineering

This paper presents a methodology for maintenance optimisation for heterogeneous infrastructure systems, i.e., systems composed of multiple facilities with different characteristics such as environments, materials, and deterioration processes. We present a bottom-up approach: facility-level optimal maintenance policies are first found; these policies are then combined with budget constraints in the system-level optimisation. In the first step, optimal and near-optimal maintenance policies for ea

Civil and Structural EngineeringEngineering
14
Article|53 citations·2021
Transferable traffic signal control: Reinforcement learning with graph centric state representation
Jinwon Yoon, Kyuree Ahn, Jinkyoo Park, Hwasoo Yeo
SJR Q1Transportation Research Part C Emerging Technologies
Building and ConstructionEngineering
15
Article|51 citations·2015
Impact of stop-and-go waves and lane changes on discharge rate in recovery flow
Simon Oh, Hwasoo Yeo
SJR Q1Transportation Research Part B Methodological
Control and Systems EngineeringEngineering

Research Areas

Control and Systems EngineeringBuilding and ConstructionSafety, Risk, Reliability and QualityAutomotive EngineeringTransportationElectrical and Electronic Engineering

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