9 citations · 9 across the 7 of their papers we have counts for
7 papers
PRISA: Proactive Infrastructure LiDAR Framework for Intersection Safety Assessment
Tam Bang, Hussam Abubakr, Emiliano de la Garza Villarreal +6
Urban intersections are among the most hazardous locations in road networks, posing significant risks to vehicles and vulnerable road users (VRUs) such as pedestrians and cyclists.…
CLIFE: Camera-LiDAR Fusion Framework for Edge-Deployable Roadside VRU Perception
Tam Bang, Hoang H. Nguyen, Lei Cheng +6
Reliable roadside perception of vulnerable road users (VRUs) remains challenging under occlusions, variable lighting, and diverse weather conditions, particularly under strict edge…
hia-gat: A Heterogeneous Interaction-Aware Graph Attention Network For Frame-Level Traffic Conflict Risk Prediction On Freeways
Mahshid Malazizi, Seyedmehdi Khaleghian, Mina Sartipi +3
This paper formulates frame-level freeway risk assessment as a multi-agent scene graph-level binary classification problem, where each video or trajectory frame is labeled risky if…
Improving VANET Simulation Channel Model in an Urban Environment via Calibration Using Real-World Communication Data
Ahmed Gammaa, Seyedmehdi Khaleghian, Toan Tran +1
Wireless communication channels in Vehicular Ad-hoc NETworks (VANETs) suffer from packet losses, which severely influences the performance of their applications. There are several…
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-Refinement
Lei Cheng, Lihao Guo, Tianya Zhang +5
Accurate multi-sensor calibration is essential for deploying robust perception systems in applications such as autonomous driving and intelligent transportation. Existing LiDAR-cam…
Semantic Segmentation for Real-World and Synthetic Vehicle's Forward-Facing Camera Images
Tuan T. Nguyen, Phan Le, Yasir Hassan +1
In this paper, we present the submission to the 5th Annual Smoky Mountains Computational Sciences Data Challenge, Challenge 3. This is the solution for semantic segmentation proble…
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…