6 papers
Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation
Xiaowei Mao, Huihu Ding, Yan Lin +6
Imputing missing values in spatial-temporal traffic data is essential for intelligent transportation systems. Among advanced imputation methods, score-based diffusion models have d…
RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
Haochen Lv, Yan Lin, Shengnan Guo +5
Accurate traffic flow forecasting is crucial for intelligent transportation services such as navigation and ride-hailing. In such applications, uncertainty estimation in forecastin…
TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model
Yichen Liu, Yan Lin, Shengnan Guo +3
Vehicle GPS trajectories record how vehicles move over time, storing valuable travel semantics, including movement patterns and travel purposes. Learning travel semantics effective…
Traj-MLLM: Can Multimodal Large Language Models Reform Trajectory Data Mining?
Shuo Liu, Di Yao, Yan Lin +2
Building a general model capable of analyzing human trajectories across different geographic regions and different tasks becomes an emergent yet important problem for various appli…
TransferTraj: A Vehicle Trajectory Learning Model for Region and Task Transferability
Tonglong Wei, Yan Lin, Zeyu Zhou +6
Vehicle GPS trajectories provide valuable movement information that supports various downstream tasks and applications. A desirable trajectory learning model should be able to tran…
A Survey and Benchmarking of Spatial-Temporal Traffic Data Imputation Models
Shengnan Guo, Tonglong Wei, Yiheng Huang +6
Traffic data imputation is a critical preprocessing step in intelligent transportation systems, underpinning the reliability of downstream transportation services. Despite substant…