Tengfeng Lin
박사과정 · 2022 입학Ph.D. Student · since 2022
보행자 안전 · 상충 지표 · 궤적 예측 · 군중 시뮬레이션Pedestrian safety · Conflict measures · Trajectory prediction · Crowd simulation
논문 실적Publication record10
2026
- Integrating deep learning–based motion prediction into extreme value theory: Incorporating motion heterogeneity and interaction behavior into crash risk estimation
Tengfeng Lin, Tiantian Chen, Inhi Kim
저널journalAnalytic Methods in Accident Research
- When feeling safe becomes risky: A VR-EEG-computer vision framework for analyzing cyclist safety in dynamic traffic environment
Lurong Xu, Tengfeng Lin, Steve O’Hern, Alexa Delbosc, Zhuo Chen, Inhi Kim, Shuli Luo
저널journalAccident Analysis & Prevention
- Evaluation of Pedestrian Future Conflict at Non-Signalized Intersections Based on Probabilistic Trajectory Prediction
Tengfeng Lin, Zhixiong Jin, Hwasoo Yeo, Inhi Kim
저널journalIEEE Transactions on Intelligent Transportation Systems
2025
- Predicted lane-based time to collision: A novel surrogate safety measure for pedestrian potential risk evaluation at non-signalized intersections
T Lin, Z Jin, S Choi, H Yeo
저널journalTransportation Research Interdisciplinary Perspectives
- Breaking the Sound Barrier: Investigating Noise Challenges in the Development of Advanced Air Mobility
BNT Alabi, S Cha, T Lin, D Jeong, A Suchshenko, H Yeo, K Choi
저널journalTransportation Research Record
2024
- A Real-time Evaluation Framework for Pedestrian's Potential Risk at Non-Signalized Intersections Based on Predicted Post-Encroachment Time
T Lin, Z Jin, S Choi, H Yeo
저널journalarXiv preprint arXiv:2404.15635
- Overcoming Data Sparsity in Traffic Speed Prediction: A Variational Autoencoder Approach on Large-Scale Road Networks
T Lin, H Yeo, I Kim
저널journal한국 ITS 학회 학술대회
- Variational Autoencoder Spatial Temporal Graph Convolutional Network: 결측 데이터 기반 속도 예측을 위한 딥러닝 프레임워크 (A Deep Learning Framework for Missing Data-Based Speed Prediction)
T Lin, H Yeo, I Kim
저널journal한국 ITS 학회 춘계학술대회
2023
- Deep Learning and Geometry Flow Vector Using Estimating Vehicle Cuboid Technology in a Monovision Environment
B Noh, T Lin, S Lee, T Jeong
저널journalSensors
2022
- A framework for pedestrian sub-classification and arrival time prediction at signalized intersection using preprocessed Lidar data
T Lin, Z Jin, S Choi, H Yeo
저널journalarXiv preprint arXiv:2201.05877