13 citations · 38 across the 14 of their papers we have counts for
15 papers
CDA-SimBoost: A Unified Framework Bridging Real Data and Simulation for Infrastructure-Based CDA Systems
Zhaoliang Zheng, Xu Han, Yuxin Bao +5
Cooperative Driving Automation (CDA) has garnered increasing research attention, yet the role of intelligent infrastructure remains insufficiently explored. Existing solutions offe…
InSPE: Rapid Evaluation of Heterogeneous Multi-Modal Infrastructure Sensor Placement
Zhaoliang Zheng, Yun Zhang, Zongling Meng +3
Infrastructure sensing is vital for traffic monitoring at safety hotspots (e.g., intersections) and serves as the backbone of cooperative perception in autonomous driving. While ve…
V2X-ReaLO: An Open Online Framework and Dataset for Cooperative Perception in Reality
Hao Xiang, Zhaoliang Zheng, Xin Xia +6
Cooperative perception enabled by Vehicle-to-Everything (V2X) communication holds significant promise for enhancing the perception capabilities of autonomous vehicles, allowing the…
Traffic Regulation-aware Path Planning with Regulation Databases and Vision-Language Models
Xu Han, Zhiwen Wu, Xin Xia +1
This paper introduces and tests a framework integrating traffic regulation compliance into automated driving systems (ADS). The framework enables ADS to follow traffic laws and mak…
V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction
Zewei Zhou, Hao Xiang, Zhaoliang Zheng +11
Vehicle-to-everything (V2X) technologies offer a promising paradigm to mitigate the limitations of constrained observability in single-vehicle systems. Prior work primarily focuses…
CooPre: Cooperative Pretraining for V2X Cooperative Perception
Seth Z. Zhao, Hao Xiang, Chenfeng Xu +3
Existing Vehicle-to-Everything (V2X) cooperative perception methods rely on accurate multi-agent 3D annotations. Nevertheless, it is time-consuming and expensive to collect and ann…
V2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perception
Hao Xiang, Zhaoliang Zheng, Xin Xia +15
Recent advancements in Vehicle-to-Everything (V2X) technologies have enabled autonomous vehicles to share sensing information to see through occlusions, greatly boosting the percep…
V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception
Runsheng Xu, Xin Xia, Jinlong Li +10
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks th…
The OpenCDA Open-source Ecosystem for Cooperative Driving Automation Research
Runsheng Xu, Hao Xiang, Xu Han +4
Advances in Single-vehicle intelligence of automated driving have encountered significant challenges because of limited capabilities in perception and interaction with complex traf…
Automated Driving Systems Data Acquisition and Processing Platform
Xin Xia, Zonglin Meng, Xu Han +5
This paper presents an automated driving system (ADS) data acquisition and processing platform for vehicle trajectory extraction, reconstruction, and evaluation based on connected…
V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perception
Hao Xiang, Runsheng Xu, Xin Xia +3
Recent advancements in Vehicle-to-Everything communication technology have enabled autonomous vehicles to share sensory information to obtain better perception performance. With th…
Model-Agnostic Multi-Agent Perception Framework
Runsheng Xu, Weizhe Chen, Hao Xiang +2
Existing multi-agent perception systems assume that every agent utilizes the same model with identical parameters and architecture. The performance can be degraded with different p…
V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer
Runsheng Xu, Hao Xiang, Zhengzhong Tu +3
In this paper, we investigate the application of Vehicle-to-Everything (V2X) communication to improve the perception performance of autonomous vehicles. We present a robust coopera…
Too Afraid to Drive: Systematic Discovery of Semantic DoS Vulnerability in Autonomous Driving Planning under Physical-World Attacks
Ziwen Wan, Junjie Shen, Jalen Chuang +4
In high-level Autonomous Driving (AD) systems, behavioral planning is in charge of making high-level driving decisions such as cruising and stopping, and thus highly securitycritic…
OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication
Runsheng Xu, Hao Xiang, Xin Xia +3
Employing Vehicle-to-Vehicle communication to enhance perception performance in self-driving technology has attracted considerable attention recently; however, the absence of a sui…