67 citations · 177 across the 28 of their papers we have counts for
28 papers
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…
Dual LiDAR-Based Traffic Movement Count Estimation at a Signalized Intersection: Deployment, Data Collection, and Preliminary Analysis
Saswat Priyadarshi Nayak, Guoyuan Wu, Kanok Boriboonsomsin +1
Traffic Movement Count (TMC) at intersections is crucial for optimizing signal timings, assessing the performance of existing traffic control measures, and proposing efficient lane…
Real-time Learning of Driving Gap Preference for Personalized Adaptive Cruise Control
Zhouqiao Zhao, Xishun Liao, Amr Abdelraouf +4
Advanced Driver Assistance Systems (ADAS) are increasingly important in improving driving safety and comfort, with Adaptive Cruise Control (ACC) being one of the most widely used.…
Overtaking-enabled Eco-approach Control at Signalized Intersections for Connected and Automated Vehicles
Haoxuan Dong, Weichao Zhuang, Guoyuan Wu +3
Preceding vehicles typically dominate the movement of following vehicles in traffic systems, thereby significantly influencing the efficacy of eco-driving control that concentrates…
Integrated Simulation Platform for Quantifying the Traffic-Induced Environmental and Health Impacts
Xuanpeng Zhao, Guoyuan Wu, Akula Venkatram +4
Air quality and human exposure to mobile source pollutants have become major concerns in urban transportation. Existing studies mainly focus on mitigating traffic congestion and re…
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…
Driver Digital Twin for Online Prediction of Personalized Lane Change Behavior
Xishun Liao, Xuanpeng Zhao, Ziran Wang +5
Connected and automated vehicles (CAVs) are supposed to share the road with human-driven vehicles (HDVs) in a foreseeable future. Therefore, considering the mixed traffic environme…
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…
Assessment of U.S. Department of Transportation Lane-Level Map for Connected Vehicle Applications
Wang Hu, David Oswald, Guoyuan Wu +1
High-definition (Hi-Def) digital maps are an indispensable automated driving technology that is developing rapidly. There are various commercial or governmental map products in the…
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…
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…
Evaluating Cybersecurity Risks of Cooperative Ramp Merging in Mixed Traffic Environments
Xuanpeng Zhao, Ahmed Abdo, Xishun Liao +2
Connected and Automated Vehicle (CAV) technology has the potential to greatly improve transportation mobility, safety, and energy efficiency. However, ubiquitous vehicular connecti…
A Game Theory Based Ramp Merging Strategy for Connected and Automated Vehicles in the Mixed Traffic: A Unity-SUMO Integrated Platform
Xishun Liao, Xuanpeng Zhao, Guoyuan Wu +4
Ramp merging is considered as one of the major causes of traffic congestion and accidents because of its chaotic nature. With the development of connected and automated vehicle (CA…
Eco-Routing Navigation System for Electric Vehicles
Guoyuan Wu, Kanok Boriboonsomsin, Matthew J. Barth
The goal of this project is to determine the feasibility of calculating a travel route for an electric vehicle (EV) that will require the least amount of energy for the trip, and t…
MOVESTAR: An Open-Source Vehicle Fuel and Emission Model based on USEPA MOVES
Ziran Wang, Guoyuan Wu, George Scora
In this paper, we introduce an open-source model "MOVESTAR" to calculate the fuel consumption and pollutant emissions of motor vehicles. This model is developed based on U.S. Envir…
A Review and Outlook of Energy Consumption Estimation Models for Electric Vehicles
Yuche Chen, Guoyuan Wu, Ruixiao Sun +3
Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can a…
End-to-End Vision-Based Adaptive Cruise Control (ACC) Using Deep Reinforcement Learning
Zhensong Wei, Yu Jiang, Xishun Liao +5
This paper presented a deep reinforcement learning method named Double Deep Q-networks to design an end-to-end vision-based adaptive cruise control (ACC) system. A simulation envir…
Optimal Control-Based Eco-Ramp Merging System for Connected and Automated Electric Vehicles
Zhouqiao Zhao, Guoyuan Wu, Ziran Wang +1
Our current transportation system suffers from a number of problems in terms of safety, mobility, and environmental sustainability. The emergence of innovative intelligent transpor…
The State-of-the-Art of Coordinated Ramp Control with Mixed Traffic Conditions
Zhouqiao Zhao, Ziran Wang, Guoyuan Wu +2
Ramp metering, a traditional traffic control strategy for conventional vehicles, has been widely deployed around the world since the 1960s. On the other hand, the last decade has w…
Early Findings from Field Trials of Heavy-Duty Truck Connected Eco-Driving System
Ziran Wang, Yuan-Pu Hsu, Alexander Vu +9
In recent years, the development of connected and automated vehicle (CAV) technology has inspired numerous advanced applications targeted at improving existing transportation syste…