151 citations · 252 across the 11 of their papers we have counts for
11 papers
Cooperverse: A Mobile-Edge-Cloud Framework for Universal Cooperative Perception with Mixed Connectivity and Automation
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
Cooperative perception (CP) is attracting increasing attention and is regarded as the core foundation to support cooperative driving automation, a potential key solution to address…
VINet: Lightweight, Scalable, and Heterogeneous Cooperative Perception for 3D Object Detection
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
Utilizing the latest advances in Artificial Intelligence (AI), the computer vision community is now witnessing an unprecedented evolution in all kinds of perception tasks, particul…
A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +4
Perceiving the environment is one of the most fundamental keys to enabling Cooperative Driving Automation (CDA), which is regarded as the revolutionary solution to addressing the s…
PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDAR
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
3D object detection plays a fundamental role in enabling autonomous driving, which is regarded as the significant key to unlocking the bottleneck of contemporary transportation sys…
Spatiotemporal Transformer Attention Network for 3D Voxel Level Joint Segmentation and Motion Prediction in Point Cloud
Zhensong Wei, Xuewei Qi, Zhengwei Bai +6
Environment perception including detection, classification, tracking, and motion prediction are key enablers for automated driving systems and intelligent transportation applicatio…
Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR
Zhengwei Bai, Saswat Priyadarshi Nayak, Xuanpeng Zhao +6
Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as a revolutionary promoter for the next-generation transportation systems. How…
Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections
Zhengwei Bai, Peng Hao, Wei Shangguan +2
Taking advantage of both vehicle-to-everything (V2X) communication and automated driving technology, connected and automated vehicles are quickly becoming one of the transformative…
Infrastructure-Based Object Detection and Tracking for Cooperative Driving Automation: A Survey
Zhengwei Bai, Guoyuan Wu, Xuewei Qi +3
Object detection plays a fundamental role in enabling Cooperative Driving Automation (CDA), which is regarded as the revolutionary solution to addressing safety, mobility, and sust…
Cyber Mobility Mirror for Enabling Cooperative Driving Automation in Mixed Traffic: A Co-Simulation Platform
Zhengwei Bai, Guoyuan Wu, Xuewei Qi +3
Endowed with automation and connectivity, Connected and Automated Vehicles are meant to be a revolutionary promoter for Cooperative Driving Automation. Nevertheless, CAVs need high…
Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network
Zhengwei Bai, Baigen Cai, Wei Shangguan +1
Motion Planning, as a fundamental technology of automatic navigation for the autonomous vehicle, is still an open challenging issue in the real-life traffic situation and is mostly…
Deep Reinforcement Learning Based High-level Driving Behavior Decision-making Model in Heterogeneous Traffic
Zhengwei Bai, Baigen Cai, Wei Shangguan +1
High-level driving behavior decision-making is an open-challenging problem for connected vehicle technology, especially in heterogeneous traffic scenarios. In this paper, a deep re…