268 citations · 1.7k across the 47 of their papers we have counts for
10 papers · 1 filter
On Social Interactions of Merging Behaviors at Highway On-Ramps in Congested Traffic
Huanjie Wang, Wenshuo Wang, Shihua Yuan +2
Merging at highway on-ramps while interacting with other human-driven vehicles is challenging for autonomous vehicles (AVs). An efficient route to this challenge requires exploring…
Scalable Low-Rank Tensor Learning for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Yixian Chen, Nicolas Saunier +1
Missing value problem in spatiotemporal traffic data has long been a challenging topic, in particular for large-scale and high-dimensional data with complex missing mechanisms and…
Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting
Pu Ren, Xinyu Chen, Lijun Sun +1
There has been increased interest in missing sensor data imputation, which is ubiquitous in the field of structural health monitoring (SHM) due to discontinuous sensing caused by s…
Efficient Connected and Automated Driving System with Multi-agent Graph Reinforcement Learning
Tianyu Shi, Jiawei Wang, Yuankai Wu +2
Connected and automated vehicles (CAVs) have attracted more and more attention recently. The fast actuation time allows them having the potential to promote the efficiency and safe…
Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting
Xinyu Chen, Lijun Sun
Time series prediction has been a long-standing research topic and an essential application in many domains. Modern time series collected from sensor networks (e.g., energy consump…
Inductive Graph Neural Networks for Spatiotemporal Kriging
Yuankai Wu, Dingyi Zhuang, Aurelie Labbe +1
Time series forecasting and spatiotemporal kriging are the two most important tasks in spatiotemporal data analysis. Recent research on graph neural networks has made substantial p…
Routine pattern discovery and anomaly detection in individual travel behavior
Lijun Sun, Xinyu Chen, Zhaocheng He +1
Discovering patterns and detecting anomalies in individual travel behavior is a crucial problem in both research and practice. In this paper, we address this problem by building a…
Incorporating travel behavior regularity into passenger flow forecasting
Zhanhong Cheng, Martin Trepanier, Lijun Sun
Accurate forecasting of passenger flow (i.e., ridership) is critical to the operation of urban metro systems. Previous studies mainly model passenger flow as time series by aggrega…
A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Jinming Yang, Lijun Sun
Sparsity and missing data problems are very common in spatiotemporal traffic data collected from various sensing systems. Making accurate imputation is critical to many application…
Scaling of contact networks for epidemic spreading in urban transit systems
Xinwu Qian, Lijun Sun, Satish V. Ukkusuri
Improved mobility not only contributes to more intensive human activities but also facilitates the spread of communicable disease, thus constituting a major threat to billions of u…