2021.03~2022.05 서울대학교 BK21인프라스피어 교육연구단, 박사후연구원
2022.06~2023.02 National University of Singapore, Research Fellow
대표논문
[논문]
김의진, 강민지, 박신형,
Deep survival analysis model for incidentclearance time prediction,
Journal of Intelligent Transportation Systems,
pp. 2315126-2315126
(2월, 2024)
[논문]
주양준, 김의진, 김동규, Peter Y. Park,
A generalized driving risk assessment on high-speed highways using field theory,
Analytic Methods in Accident Research,
pp. 100303-100303
(12월, 2023)
[논문]
김의진, Prateek Bansal,
A deep generative model for feasible and diverse population synthesis,
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES,
Vol.148,
pp. 104053-104053
(3월, 2023)
[논문]
신용근, 김동규, 김의진,
Activity-based TOD Typology for Seoul Transit Station Areas Using Smart-card Data,
Journal of Transport Geography,
Vol.150,
pp. 103459-103459
(12월, 2022)
[논문]
신용우, 김동규, 김의진,
Impact of Driver Behavior and Vehicle Type on Safety of Vehicle Platoon Under Lane Change Situation,
TRANSPORTATION RESEARCH RECORD,
pp. 0-0
(10월, 2022)
[논문]
Prateek Bansal, 김의진, Semra Ozdemir,
Discrete choice experiments with eye-tracking: How far we have come and ways forward,
Journal of Choice Modelling,
pp. 100478-100478
(6월, 2024)
[논문]
김의진, Prateek Bansal,
A new flexible and partially monotonic discrete choice model,
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL,
pp. 102947-102947
(5월, 2024)
[논문]
김의진, 강민지, 박신형,
Deep survival analysis model for incidentclearance time prediction,
Journal of Intelligent Transportation Systems,
pp. 2315126-2315126
(2월, 2024)
[논문]
주양준, 김의진, 김동규, Peter Y. Park,
A generalized driving risk assessment on high-speed highways using field theory,
Analytic Methods in Accident Research,
pp. 100303-100303
(12월, 2023)
[논문]
김의진, Prateek Bansal,
A deep generative model for feasible and diverse population synthesis,
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES,
Vol.148,
pp. 104053-104053
(3월, 2023)
[논문]
신용근, 김동규, 김의진,
Activity-based TOD Typology for Seoul Transit Station Areas Using Smart-card Data,
Journal of Transport Geography,
Vol.150,
pp. 103459-103459
(12월, 2022)
[논문]
신용우, 김동규, 김의진,
Impact of Driver Behavior and Vehicle Type on Safety of Vehicle Platoon Under Lane Change Situation,
TRANSPORTATION RESEARCH RECORD,
pp. 0-0
(10월, 2022)
[논문]
윤현수, 김의진, 함승우, 김동규,
Price incentive strategy for the E-scooter sharing service using deep reinforcement learning,
Journal of Intelligent Transportation Systems,
pp. 0-0
(10월, 2022)
[논문]
조정훈, 김동규, 김의진,
Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition,
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,
Vol.600,
pp. 127488-127488
(8월, 2022)
[논문]
김의진, 김동규, 손기민,
Imputing qualitative attributes for trip chains extracted from smart card data using a conditional generative adversarial network,
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES,
Vol.137,
pp. 103616-103616
(4월, 2022)
[논문]
김의진, 김영서, 장성훈, 김동규,
Tourists’ preference on the combination of travel modes under Mobility-as-a-Service environment,
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE,
Vol.150,
pp. 236-255
(8월, 2021)
[논문]
김영서, 김의진, 장성훈, 김동규,
A Comparative Analysis of the Users of Private Cars and Public Transportation for Intermodal Options under Mobility-as-a-Service in Seoul,
Travel Behaviour and Society,
Vol.24,
pp. 68-80
(7월, 2021)
[논문]
김의진, 김영서, 김동규,
Interpretable machine-learning models for estimating trip purpose in smart card data,
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-MUNICIPAL ENGINEER,
Vol.174,
No.2,
pp. 108-117
(6월, 2021)
[논문]
김의진, 김동규, 박신형, 정구, 권오훈,
Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway,
PLoS One,
Vol.16,
No.5,
pp. e0251866-e0251866
(5월, 2021)
[논문]
김의진,
Analysis of Travel Mode Choice in Seoul Using an Interpretable Machine Learning Approach,
JOURNAL OF ADVANCED TRANSPORTATION,
Vol.2021,
pp. 6685004-6685004
(3월, 2021)
[논문]
김의진, 고승영, 김동규, 정구홍,
Spatiotemporal Filtering Method for Detecting Kinematic Waves in a Connected Environment,
PLoS One,
Vol.15,
No.12,
pp. e0244329-e0244329
(12월, 2020)
[논문]
함승우, 김의진, 고승영, 박호철, 김동규,
Investigating the Influential Factors for Practical Application of Multi-Class Vehicle Detection for Images from Unmanned Aerial Vehicle using Deep Learning Models,
TRANSPORTATION RESEARCH RECORD,
Vol.2674,
No.12,
pp. 1-15
(10월, 2020)
[논문]
김의진, 고승영, 박호철, 김동규,
A Hybrid Approach Based on Variational Mode Decomposition for Analyzing and Predicting Urban Travel Speed,
JOURNAL OF ADVANCED TRANSPORTATION,
Vol.2019,
pp. 3958127-3958127
(12월, 2019)
[논문]
김의진, 고승영, 박호철, 함승우, 김동규,
Extracting Vehicle Trajectories Using Unmanned Aerial Vehicles in Congested Traffic Conditions,
JOURNAL OF ADVANCED TRANSPORTATION,
Vol.2019,
pp. 9060797-9060797
(4월, 2019)
해당 데이터는 존재하지 않습니다.
해당 데이터는 존재하지 않습니다.
[학술회의]
서민수, 김의진, 이규성, 임승유,
드론 영상 기반 차량검지 및 추적을 위한 YOLO 모형 학습전략,
대한교통학회 제89회 학술발표회,
(10월, 2023)
[학술회의]
서민수, 이규성, 김의진,
장기 예측에서 기계 학습과 통계모형의 비교: 차량 보유 선택의 맥락에서,
대한교통학회 제89회 학술발표회,
(10월, 2023)
[학술회의]
임승유, 김의진,
베이지안 네트워크를 활용한 통행 의사결정 구조 분석,
대한교통학회 제89회 학술발표회,
(10월, 2023)