아주대학교

교통시스템공학과

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아주대학교 교통시스템공학과

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대학공과대학교통시스템공학과

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김의진Eui-Jin Kim

  • 소속 교통시스템공학과
  • 연구실산학협력원 823호
  • 이메일 euijin@ajou.ac.kr
  • 내선번호2402

관심분야

  • 인공지능, 행동모형, 교통계획

학력

  • 2021.02 서울대학교대학원 박사

경력

    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)

연구활동

  • [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)
해당 데이터는 존재하지 않습니다.