most citedCar-Following Models: A Multidisciplinary Review

53 citations · 128 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2023★ 53 cited

Car-Following Models: A Multidisciplinary Review

Tianya Zhang, Ph. D., Peter J. Jin +3

Car-following (CF) algorithms are crucial components of traffic simulations and have been integrated into many production vehicles equipped with Advanced Driving Assistance Systems…

cs.CV2022★ 9 cited

Spatial-Temporal Deep Embedding for Vehicle Trajectory Reconstruction from High-Angle Video

Tianya T. Zhang Ph. D., Peter J. Jin Ph. D., Han Zhou +2

Spatial-temporal Map (STMap)-based methods have shown great potential to process high-angle videos for vehicle trajectory reconstruction, which can meet the needs of various data-d…

cs.CV2022★ 4 cited

Weighted Bayesian Gaussian Mixture Model for Roadside LiDAR Object Detection

Tianya Zhang, Yi Ge, Peter J. Jin

Background modeling is widely used for intelligent surveillance systems to detect moving targets by subtracting the static background components. Most roadside LiDAR object detecti…

cs.CV2022★ 6 cited

Spatial-Temporal Map Vehicle Trajectory Detection Using Dynamic Mode Decomposition and Res-UNet+ Neural Networks

Tianya T. Zhang, Peter J. Jin

This paper presents a machine-learning-enhanced longitudinal scanline method to extract vehicle trajectories from high-angle traffic cameras. The Dynamic Mode Decomposition (DMD) m…

cs.LG2022★ 15 cited

Network Level Spatial Temporal Traffic State Forecasting with Hierarchical-Attention-LSTM (HierAttnLSTM)

Tianya Zhang

Traffic state data, such as speed, volume and travel time collected from ubiquitous traffic monitoring sensors require advanced network level analytics for forecasting and identify…

cs.CV2022★ 41 cited

Roadside Lidar Vehicle Detection and Tracking Using Range And Intensity Background Subtraction

Tianya Zhang, Peter J. Jin

In this paper, we developed the solution of roadside LiDAR object detection using a combination of two unsupervised learning algorithms. The 3D point clouds are firstly converted i…