24 citations · 26 across the 12 of their papers we have counts for
13 papers
TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring
Yuhang Wang, Jingxin Yang, Chuheng Wei +4
Predicting how drivers, vehicles, and road scenes interact and evolve together is central to driver monitoring. Prior work models in-cabin activity or traffic-conditioned driver mo…
DriveMotion: A Large-Scale Multi-Source Benchmark for Driver Motion Sequence Modeling and Forecasting
Yuhang Wang, Chuheng Wei, Jingxin Yang +2
Driver motion can provide cues to ongoing behavior, attention, and near-term driving intent. However, most existing driver-centric datasets focus on recognizing predefined driver b…
Designing Versatile Samples for Learned Trajectory Scoring
Yaguang Li, Jiaru Zhang, Chuheng Wei +2
Many current end-to-end driving policies emit a pool of candidate trajectories and select one, which makes selection a separable component: a scorer can be retrained while the plan…
VISTA-DZ: Visual Semantic Trajectory Adaptation for Personalized Dilemma Zone Prediction
Chuheng Wei, Ziye Qin, Ziran Wang +1
Driver decision making in the dilemma zone at signalized intersections is safety critical, as vehicles approaching a yellow signal must decide whether to stop or proceed within lim…
From Sensing to Decision: A Generic Architecture for Freight Signal Priority Systems
Ziyan Zhang, Xuanpeng Zhao, Chuheng Wei +5
Freight Signal Priority (FSP) systems have emerged as a promising strategy to enhance freight mobility and reduce corridor delays in urban networks. While extensive research has fo…
A Multi-modal Detection System for Infrastructure-based Freight Signal Priority
Ziyan Zhang, Chuheng Wei, Xuanpeng Zhao +6
Freight vehicles approaching signalized intersections require reliable detection and motion estimation to support infrastructure-based Freight Signal Priority (FSP). Accurate and t…
HeCoFuse: Cross-Modal Complementary V2X Cooperative Perception with Heterogeneous Sensors
Chuheng Wei, Ziye Qin, Walter Zimmer +2
Real-world Vehicle-to-Everything (V2X) cooperative perception systems often operate under heterogeneous sensor configurations due to cost constraints and deployment variability acr…
Integrating Multi-Modal Sensors: A Review of Fusion Techniques for Intelligent Vehicles
Chuheng Wei, Ziye Qin, Ziyan Zhang +2
Multi-sensor fusion plays a critical role in enhancing perception for autonomous driving, overcoming individual sensor limitations, and enabling comprehensive environmental underst…
PDB: Not All Drivers Are the Same -- A Personalized Dataset for Understanding Driving Behavior
Chuheng Wei, Ziye Qin, Siyan Li +8
Driving behavior varies across individuals, yet most existing driving datasets do not preserve driver identity or control for factors that may affect driving style. We introduce th…
Investigating Personalized Driving Behaviors in Dilemma Zones: Analysis and Prediction of Stop-or-Go Decisions
Ziye Qin, Siyan Li, Guoyuan Wu +4
Dilemma zones at signalized intersections present a commonly occurring but unsolved challenge for both drivers and traffic operators. Onsets of the yellow lights prompt varied resp…
PointCompress3D: A Point Cloud Compression Framework for Roadside LiDARs in Intelligent Transportation Systems
Walter Zimmer, Ramandika Pranamulia, Xingcheng Zhou +2
In the context of Intelligent Transportation Systems (ITS), efficient data compression is crucial for managing large-scale point cloud data acquired by roadside LiDAR sensors. The…
Feature Corrective Transfer Learning: End-to-End Solutions to Object Detection in Non-Ideal Visual Conditions
Chuheng Wei, Guoyuan Wu, Matthew J. Barth
A significant challenge in the field of object detection lies in the system's performance under non-ideal imaging conditions, such as rain, fog, low illumination, or raw Bayer imag…
KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersections
Chuheng Wei, Guoyuan Wu, Matthew J. Barth +3
Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic management and autonomous driving systems. However, it presents unique challenge…