268 citations · 1.7k across the 47 of their papers we have counts for
10 papers · 1 filter
Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering
Ziyue Li, Hao Yan, Chen Zhang +3
Passenger clustering based on trajectory records is essential for transportation operators. However, existing methods cannot easily cluster the passengers due to the hierarchical s…
Shareable Driving Style Learning and Analysis with a Hierarchical Latent Model
Chaopeng Zhang, Wenshuo Wang, Zhaokun Chen +3
Driving style is usually used to characterize driving behavior for a driver or a group of drivers. However, it remains unclear how one individual's driving style shares certain com…
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach
Chunwei Yang, Xiaoxu Chen, Lijun Sun +2
Time series analysis is a fundamental task in various application domains, and deep learning approaches have demonstrated remarkable performance in this area. However, many real-wo…
Calibrating Car-Following Models via Bayesian Dynamic Regression
Chengyuan Zhang, Wenshuo Wang, Lijun Sun
Car-following behavior modeling is critical for understanding traffic flow dynamics and developing high-fidelity microscopic simulation models. Most existing impulse-response car-f…
Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering
Ziyue Li, Hao Yan, Chen Zhang +4
Passenger clustering based on travel records is essential for transportation operators. However, existing methods cannot easily cluster the passengers due to the hierarchical struc…
Better Batch for Deep Probabilistic Time Series Forecasting
Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun
Deep probabilistic time series forecasting has gained attention for its ability to provide nonlinear approximation and valuable uncertainty quantification for decision-making. Howe…
Traffic State Estimation from Vehicle Trajectories with Anisotropic Gaussian Processes
Fan Wu, Zhanhong Cheng, Huiyu Chen +2
Accurately monitoring road traffic state is crucial for various applications, including travel time prediction, traffic control, and traffic safety. However, the lack of sensors of…
Anti-circulant dynamic mode decomposition with sparsity-promoting for highway traffic dynamics analysis
Xudong Wang, Lijun Sun
Highway traffic states data collected from a network of sensors can be considered a high-dimensional nonlinear dynamical system. In this paper, we develop a novel data-driven metho…
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization
Mengying Lei, Lijun Sun
Bayesian optimization (BO) primarily uses Gaussian processes (GP) as the key surrogate model, mostly with a simple stationary and separable kernel function such as the squared-expo…
Probabilistic Traffic Forecasting with Dynamic Regression
Vincent Zhihao Zheng, Seongjin Choi, Lijun Sun
This paper proposes a dynamic regression (DR) framework that enhances existing deep spatiotemporal models by incorporating structured learning for the error process in traffic fore…