Publications (10)
The Role of Integrity Monitoring in Connected and Automated Vehicles: Current State-of-Practice and Future Directions
Saswat Priyadarshi Nayak, Matthew Barth
Positioning integrity refers to the trust in the performance of a navigation system. Accurate and reliable position information is needed to meet the requirements of connected and…
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…
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…
Data-Driven Multi-step Demand Prediction for Ride-hailing Services Using Convolutional Neural Network
Chao Wang, Yi Hou, Matthew Barth
Ride-hailing services are growing rapidly and becoming one of the most disruptive technologies in the transportation realm. Accurate prediction of ride-hailing trip demand not only…
Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities
Yimo Yan, Yejia Liao, Guanhao Xu +13
The rapid rise of Large Language Models (LLMs) is transforming traffic and transportation research, with significant advancements emerging between the years 2023 and 2025 -- a peri…
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…
Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network
Zhensong Wei, Chao Wang, Peng Hao +1
Accurate lane localization and lane change detection are crucial in advanced driver assistance systems and autonomous driving systems for safer and more efficient trajectory planni…
A Review on Cooperative Adaptive Cruise Control (CACC) Systems: Architectures, Controls, and Applications
Ziran Wang, Guoyuan Wu, Matthew Barth
Connected and automated vehicles (CAVs) have the potential to address the safety, mobility and sustainability issues of our current transportation systems. Cooperative adaptive cru…
Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data
Mohammad Billah, Farzana Rahman, Arash Maskooki +3
Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, sto…
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…