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09/11/2023
Fairness- and uncertainty-aware data generation for data-driven design
The design dataset is the backbone of data-driven design. Ideally, the d...
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08/02/2023
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach
Time series analysis is a fundamental task in various application domain...
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07/30/2023
Interactive Car-Following: Matters but NOT Always
Following a leading vehicle is a daily but challenging task because it r...
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07/07/2023
Calibrating Car-Following Models via Bayesian Dynamic Regression
Car-following behavior modeling is critical for understanding traffic fl...
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06/23/2023
Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering
Passenger clustering based on travel records is essential for transporta...
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05/26/2023
Better Batch for Deep Probabilistic Time Series Forecasting
Deep probabilistic time series forecasting has gained significant attent...
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03/04/2023
Traffic State Estimation with Anisotropic Gaussian Processes from Vehicle Trajectories
Accurately monitoring road traffic state and speed is crucial for variou...
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02/28/2023
Bayesian Kernelized Tensor Factorization as Surrogate for Bayesian Optimization
Bayesian optimization (BO) primarily uses Gaussian processes (GP) as the...
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02/14/2023
Anti-circulant dynamic mode decomposition with sparsity-promoting for highway traffic dynamics analysis
Highway traffic states data collected from a network of sensors can be c...
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01/17/2023
Enhancing Deep Traffic Forecasting Models with Dynamic Regression
A common assumption in deep learning-based multivariate and multistep tr...
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12/10/2022
Spatiotemporal Residual Regularization with Dynamic Mixtures for Traffic Forecasting
Existing deep learning-based traffic forecasting models are mainly train...
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12/03/2022
Laplacian Convolutional Representation for Traffic Time Series Imputation
Spatiotemporal traffic data imputation is of great significance in intel...
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11/28/2022
Discovering Dynamic Patterns from Spatiotemporal Data with Time-Varying Low-Rank Autoregression
The problem of broad practical interest in spatiotemporal data analysis,...
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10/15/2022
On Trustworthy Decision-Making Process of Human Drivers from the View of Perceptual Uncertainty Reduction
Humans are experts in making decisions for challenging driving tasks wit...
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10/07/2022
Bayesian Calibration of the Intelligent Driver Model
Accurate calibration of car-following models is essential for investigat...
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08/21/2022
Bayesian Complementary Kernelized Learning for Multidimensional Spatiotemporal Data
Probabilistic modeling of multidimensional spatiotemporal data is critic...
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08/16/2022
Social Interactions for Autonomous Driving: A Review and Perspective
No human drives a car in a vacuum; she/he must negotiate with other road...
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08/04/2022
Bayesian calibration of traffic flow fundamental diagrams using Gaussian processes
Modeling the relationship between vehicle speed and density on the road ...
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06/24/2022
Toward multi-target self-organizing pursuit in a partially observable Markov game
The multiple-target self-organizing pursuit (SOP) problem has wide appli...
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06/14/2022
Probabilistic forecasting of bus travel time with a Bayesian Gaussian mixture model
Accurate forecasting of bus travel time and its uncertainty is critical ...
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03/20/2022
Nonstationary Temporal Matrix Factorization for Multivariate Time Series Forecasting
Modern time series datasets are often high-dimensional, incomplete/spars...
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02/19/2022
Bayesian inference for link travel time correlation of a bus route
Estimation of link travel time correlation of a bus route is essential t...
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11/02/2021
Robust Dynamic Bus Control: A Distributional Multi-agent Reinforcement Learning Approach
Bus system is a critical component of sustainable urban transportation. ...
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10/08/2021
Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection
Spatiotemporal traffic data (e.g., link speed/flow) collected from senso...
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09/24/2021
Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging
Spatiotemporal kriging is an important application in spatiotemporal dat...
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09/17/2021
Dynamic Spatiotemporal Graph Convolutional Neural Networks for Traffic Data Imputation with Complex Missing Patterns
Missing data is an inevitable and ubiquitous problem for traffic data co...
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09/10/2021
Spatially Focused Attack against Spatiotemporal Graph Neural Networks
Spatiotemporal forecasting plays an essential role in various applicatio...
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09/06/2021
Individual Mobility Prediction via Attentive Marked Temporal Point Processes
Individual mobility prediction is an essential task for transportation d...
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08/31/2021
Scalable Spatiotemporally Varying Coefficient Modeling with Bayesian Kernelized Tensor Regression
As a regression technique in spatial statistics, spatiotemporally varyin...
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06/02/2021
Quantifying out-of-station waiting time in oversaturated urban metro systems
Metro systems in megacities such as Beijing, Shenzhen and Guangzhou are ...
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05/21/2021
Low-Rank Hankel Tensor Completion for Traffic Speed Estimation
This paper studies the traffic state estimation (TSE) problem using spar...
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05/02/2021
Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning
The bus system is a critical component of sustainable urban transportati...
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04/30/2021
Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation
Spatiotemporal traffic time series (e.g., traffic volume/speed) collecte...
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01/02/2021
Real-time forecasting of metro origin-destination matrices with high-order weighted dynamic mode decomposition
Forecasting the short-term ridership among origin-destination pairs (OD ...
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09/18/2020
Industrial Topics in Urban Labor System
Categorization is an essential component for us to understand the world ...
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08/14/2020
On Social Interactions of Merging Behaviors at Highway On-Ramps in Congested Traffic
Merging at highway on-ramps while interacting with other human-driven ve...
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08/07/2020
Scalable Low-Rank Autoregressive Tensor Learning for Spatiotemporal Traffic Data Imputation
Missing value problem in spatiotemporal traffic data has long been a cha...
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07/06/2020
Towards Efficient Connected and Automated Driving System via Multi-agent Graph Reinforcement Learning
Connected and automated vehicles (CAVs) have attracted more and more att...
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06/18/2020
Low-Rank Autoregressive Tensor Completion for Multivariate Time Series Forecasting
Time series prediction has been a long-standing research topic and an es...
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06/13/2020
Inductive Graph Neural Networks for Spatiotemporal Kriging
Time series forecasting and spatiotemporal kriging are the two most impo...
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04/05/2020
Routine pattern discovery and anomaly detection in individual travel behavior
Discovering patterns and detecting anomalies in individual travel behavi...
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04/02/2020
Incorporating travel behavior regularity into passenger flow forecasting
Accurate forecasting of passenger flow (i.e., ridership) is critical to ...
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03/23/2020
A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation
Sparsity and missing data problems are very common in spatiotemporal tra...
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10/14/2019
Bayesian Temporal Factorization for Multidimensional Time Series Prediction
Large-scale and multidimensional spatiotemporal data sets are becoming u...
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01/23/2019
