5 papers
PMA-Diffusion: A Physics-guided Mask-Aware Diffusion Framework for TSE from Sparse Observations
Lindong Liu, Zhixiong Jin, Seongjin Choi
High-resolution highway traffic state information is essential for Intelligent Transportation Systems, but typical traffic data acquired from loop detectors and probe vehicles are…
Deep Learning Methods for Adjusting Global MFD Speed Estimations to Local Link Configurations
Zhixiong Jin, Dimitrios Tsitsokas, Nikolas Geroliminis +1
In large-scale traffic optimization, models based on Macroscopic Fundamental Diagram (MFD) are recognized for their efficiency in broad network analyses. However, they fail to refl…
DRIFT open dataset: A drone-derived intelligence for traffic analysis in urban environment
Hyejin Lee, Seokjun Hong, Jeonghoon Song +7
Reliable traffic data are essential for understanding urban mobility and developing effective traffic management strategies. This study introduces the DRone-derived Intelligence Fo…
A Gentle Introduction and Tutorial on Deep Generative Models in Transportation Research
Seongjin Choi, Zhixiong Jin, Seung Woo Ham +2
Deep Generative Models (DGMs) have rapidly advanced in recent years, becoming essential tools in various fields due to their ability to learn complex data distributions and generat…
A Real-time Evaluation Framework for Pedestrian's Potential Risk at Non-Signalized Intersections Based on Predicted Post-Encroachment Time
Tengfeng Lin, Zhixiong Jin, Seongjin Choi +1
Addressing pedestrian safety at intersections is one of the paramount concerns in the field of transportation research, driven by the urgency of reducing traffic-related injuries a…