4 citations · 10 across the 10 of their papers we have counts for
10 papers
MIC-BEV: Multi-Infrastructure Camera Bird's-Eye-View Transformer with Relation-Aware Fusion for 3D Object Detection
Yun Zhang, Zhaoliang Zheng, Johnson Liu +5
Infrastructure-based perception plays a crucial role in intelligent transportation systems, offering global situational awareness and enabling cooperative autonomy. However, existi…
QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception
Seth Z. Zhao, Huizhi Zhang, Zhaowei Li +11
Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating occlusions and expanding the fi…
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…
AgentAlign: Misalignment-Adapted Multi-Agent Perception for Resilient Inter-Agent Sensor Correlations
Zonglin Meng, Yun Zhang, Zhaoliang Zheng +2
Cooperative perception has attracted wide attention given its capability to leverage shared information across connected automated vehicles (CAVs) and smart infrastructures to addr…
UniMSF: A Unified Multi-Sensor Fusion Framework for Intelligent Transportation System Global Localization
Wei Liu, Jiaqi Zhu, Guirong Zhuo +8
Intelligent transportation systems (ITS) localization is of significant importance as it provides fundamental position and orientation for autonomous operations like intelligent ve…
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…