Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional Networks
IEEE Transactions on Intelligent Vehicles, doi: 10.1109/TIV.2023.3341071.Wu, K., Zhou, Y., Shi, H., Li, X., & Ran, B. (2023). [Link]
A Digital Twin Framework for Physical-Virtual Integration in Enhancing Connected Vehicle Corridor Data Pipeline
IEEE Transactions on Intelligent Transportation SystemsWu, K., Li, P., Cheng, Y., Parker, S. T., Noyce, D., Ran, B. & Ye, X. (2025). [Link]
Development of the Data Pipeline for a Connected Vehicle Corridor
ASCE International Conference on Transportation and Development 2023 (pp. 218-230)Wu, K., Cheng, Y., Parker, S. T., Ran, B., & Noyce, D. A. (2023). [Link]
How Does C-V2X Perform in Urban Environments? Results from Real-world Empirical Experiments on Urban Arterials
IEEE Transactions on Intelligent Vehicles, doi: 10.1109/TIV.2023.3326735.Li, P., Wu, K., Cheng, Y., Parker, S., & Noyce, D. A. (2023). [Link]
Predictive Analysis of Vehicular Lane Changes: An Integrated LSTM Approach
Applied Sciences 13 (18), 10157.Liu, H., Wu, K., Fu, S., Shi, H., & Xu, H. (2023). [Link]
Work zone crash occurrence prediction based on planning stage work zone configurations using an artificial neural network
Transportation research record, 2676(11), 377-384.Cheng, Y., Wu, K., Li, H., Parker, S., Ran, B., & Noyce, D. (2022). [Link]
A Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition
IEEE Internet of Things JournalShi, H., Shi, K., Wu, K., Li, W., Zhou, Y., & Ran, B. (2025). [Link]
Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles
Knowledge-Based Systems, 269, 110485.Shi, H., Zhou, Y., Wu, K., Chen, S., Ran, B., & Nie, Q. (2023). [Link]
Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment
Transportation Research Part C: Emerging Technologies, 133, 103421.Shi, H., Zhou, Y., Wu, K., Wang, X., Lin, Y., & Ran, B. (2021). [Link]
A Deep Long Short-Term Memory Network Embedded Model Predictive Control Strategies for Car-Following Control of Connected Automated Vehicles in Mixed Traffic
IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2024.3412329.Zhou, Y., Zhang, Z., Ding, F., Ahn, S., Wu, K., & Ran, B. (2024). [Link]
Hypergraph-based Motion Generation through Multi-modal Interaction Relational Reasoning for Connected and Automated Vehicles
Submitted to Transportation Research Part C: Emerging TechnologiesWu, K., Shi, H., Zhou, Y., Lord, D., Ran, B. & Ye, X. (2024). [Link]
A Deep Learning Enabled Economical Informatization Framework with Sparsely Located Sensors
Submitted to Nature CommunicationsWu, K., Zhou, Y., Wang, X., Shi, H., Li, X., Ye, X., Qu, X., & Ran, B. (2025).
V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors
Submitted to IEEE Transactions on Intelligent Transportation SystemsWu, K., Li, P., Zhou, Y., Gan, R., You, J., Cheng, Y., Zhu, J., Parker, S. T., Noyce, D., Ran, B. & Tu, Z.(2025). [Link]
AI²-Active Safety: AI-enabled Interaction-aware Active Safety Analysis with Vehicle Dynamics
Wu, K., Li, Z., Li, S., Ye, X., Lord, D., & Zhou, Y.(2025). [Link]
Virtual Roads, Smarter Safety: A Digital Twin Framework for Mixed Autonomous Traffic Analysis
Submitted to IEEE Internet of Things JournalZhang, H., Yue, X., Tian, K., Li, S., Wu, K., Li, Z., Lord, D., & Zhou, Y. (2025). [Link]
Generative AI for Autonomous Driving: Frontiers and Opportunities
Wang, Y., Xing, S., Can, C., Li, R., Hua, H., Tian, K., Mo, Z., Gao, X., Wu, K., Zhou, S., et al. (2025). [Link]
AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration
Gao, X., Wu, Y., Luo, X., Wu, K., Chen, X., Wang, Y., Liu, C., Zhou, Y., \& Tu, Z. (2025).
Goal-based Neural Physics Vehicle Trajectory Prediction Model
Submitted to Transportation Research Part C: Emerging TechnologiesGan, R., Shi, H., Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., & Ran, B. (2024). [Link]
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models
Submitted to IEEE Transactions on Intelligent Transportation SystemsGan, R., Li, P., Long, K., Ma, J., An, B., You, J., Wu, K., Ran, B. (2025) [Link]
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision Language Models
You, J., Shi, H., Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li, X., & Ran, B. (2024). [Link]
Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction
You, J., Shi, H., Wu, K., Long, K., Fu, S., Chen, S., & Ran, B. (2024). [Link]
FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction.
You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z., Shi, H., Wu, K., Long, K., Fu, S., Chen, S., & Ran, B. (2024). [Link]
Real-World Data Inspired Interactive Connected Traffic Scenario Generation
You, J., Li, P., Cheng, Y., Wu, K., Gan, R., Parker, S., & Ran, B. (2024) [Link]
Integrating Spatiotemporal Vision Transformer into Digital Twins for High-Resolution Heat Stress Forecasting in Campus Environments.
Submitted to Journal of Planning Education and ResearchGong, W., Ye, X., Wu, K., Jamonnak, S., Zhang, W., Yang, Y., & Huang, X. (2025).
A Digital Twin-Driven Recommendation System for Adaptive Campus Course Timetabling.
Wu, K., Ye, X., Jamonnak, S., Feng, X. (2025).
Embed Bus Bunching In Neural Network based Bus Arrival Time Prediction: A Dual Attention Deep Learning Approach
Wu, K., Zhang, H., Ou, J., Lu, J., An, C., & Nie, Q. (2024).
Vision-Language Control for Safe Autonomous Driving
Wu, K., Zhou, Y., Tu, Z., Li, Z., et al. (2025).
Explainable and Generalizable Relational Reasoning for Multi-Agent Multi-modal Interaction
Wu, K., Shi, H., Zhou, Y., & Ran, B. (2025).
Hypergraph-based Interaction-aware Motion Planning
Wu, K., Li, S., Zhou, Y., et al. (2025).
LLM-Driven Digital Twin Framework for Behavior Modeling and Scenario Generation in Autonomous Driving.
Wu, K., Li, P., Zhou, Y., Gan, R., You, J., Tu, Z., et al. (2025).
LLM-Enhanced Universal and Interpretable Human Mobility Prediction
Wu, K., Zhou, S., Ye, X., Zhou, Y. (2025).
On the Collision Risk of Stochastic Traffic: Analytical Approximation in 2D and 3D Space for Generic Vehicles
Zhang, H., Li, Z., Wu, K., Lord, D., Tu, Z., Zhou, Y. (2025).
Prototype of a Cost-Effective Roadside Device System for Vehicle Positioning in Cooperative Autonomous Driving.
Wu, K., Cheng, Y., Gan, R., You, J., Ran, B., Parker, S. T. (2025).
Eco-Focused Control Optimization of Mixed Traffic Flow Within Vehicular Networks for Sustainable Transport
Yuan, T., Shi, H., Li, Z., Wu, K., Liu, H., & Ran, B. (2024).
Hypergraph-based Motion Generation through Multi-modal Interaction Relational Reasoning for Connected and Automated Vehicles
Poster Presentation of ACP30 Vehicle-Highway Automation, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.Wu, K., Shi, H., Zhou, Y., Lord, D., Ran, B. & Ye, X. (2024).
V2X-LLM: Improving Vehicle-to-Everything Integration and Understanding with Large Language Models
Podium Presentation of AED50 ChatGPT and Beyond: A Large Language Model–Based Transportation Perspective, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.Wu, K., Li, P., Cheng, Y., You, J., Gan, R., Zhu, J., Parker, S. T., Noyce, D., & Ran, B. (2024).
Real-World Data Inspired Interactive Connected Traffic Scenario Generation
Poster Presentation of ACP30 Vehicle-Highway Automation, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.You, J., Li, P., Cheng, Y., Wu, K., Gan, R., Parker, S., & Ran, B. (2024).
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision Language Models
Poster Presentation of ACP30 Vehicle-Highway Automation, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.You, J., Shi, H., Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li, X., & Ran, B. (2024).
Goal-based Neural Physics Vehicle Trajectory Prediction Model
Poster Presentation of AED50 Advances in Artificial Intelligence for Traffic Management and Safety, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.Gan, R., Shi, H., Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., & Ran, B. (2024).
Crossfusor: A Cross-Attention Transformer Enhanced Conditional Diffusion Model for Car-Following Trajectory Prediction
Poster Presentation of ACP30, Transportation Research Board 104th Annual Meeting. Washington, D.C. Jan 2025.You, J., Shi, H., Wu, K., Long, K., Fu, S., Chen, S., & Ran, B. (2024).
Data Pipeline of a Connected Vehicle Corridor: A Leap Towards Digital Twin
Podium Presentation of CAV Impacts Track, Advancing CAV Deployment Resilience Through Virtual Twin Establishment, ASCE International Conference on Transportation and Development 2024. Atlanta, Georgia, June 2024.Wu, K., Cheng, Y., Li, P., Parker, S. T., Ran, B., & Noyce, D. A. (2024).
Development of the Data Pipeline for a Connected Vehicle Corridor
Podium Presentation of CAV Impacts Track, CAV Data-Empowered Traffic System Operation Innovations, ASCE International Conference on Transportation and Development 2023. Austin, Texas, June 2023.Wu, K., Cheng, Y., Parker, S. T., Ran, B., & Noyce, D. A. (2023). [Link]
Multimodal Interaction-Aware 2D Vehicle Trajectory Prediction based on Diffusion Graph Convolutional Networks
Poster Presentation of AED50 Safe and Smart Transportation Systems Powered by Artificial Intelligence, Transportation Research Board 103th Annual Meeting. Washington, D.C., Jan 2024.Wu, K., Zhou, Y., Shi, H., Li, X., & Ran, B. (2024).
The Enhancement of the Data Pipeline of a Connected Vehicle Corridor: A Leap Towards Digital Twin Implementation
Poster Presentation of AED30 Information Systems and Technology, Transportation Research Board 103th Annual Meeting. Washington, D.C., Jan 2024.Wu, K., Cheng, Y., Li, P., Parker, S. T., Ran, B., & Noyce, D. A. (2024).
How Does C-V2X Perform in Urban Environments? Results from Real-world Empirical Experiments on Urban Arterials
Poster Presentation of AED20 Applications and Innovations in Urban Travel Data, Transportation Research Board 103th Annual Meeting. Washington, D.C., Jan 2024.Li, P., Wu, K., Cheng, Y., Huang, Z., Gan, R., Parker, S., & Noyce, D. A. (2024).
Development of the Data Pipeline for a Connected Vehicle Corridor
Poster Presentation of AED30 Information Systems and Technology, Transportation Research Board 102th Annual Meeting. Washington, D.C., Jan 2023.Wu, K., Cheng, Y., Parker, S. T., Ran, B., & Noyce, D. A. (2023).
Work zone crash occurrence prediction based on planning stage work zone configurations using an artificial neural network
Poster Presentation of ACS20 Advancing New Methods and Data, Transportation Research Board 101th Annual Meeting. Washington, D.C., Jan 2022.Cheng, Y., Wu, K., Li, H., Parker, S. T., Ran, B., & Noyce, D. (2022).
Using High-Resolution Archived Operational Traffic Data for Transportation Management during COVID-19 Pandemic
Poster Presentation of ACP70 Advances in Traffic Monitoring Research and Practice, Transportation Research Board 100th Annual Meeting. Washington, D.C., Jan 2021.Cheng, Y., Wu, K., Parker, S. T., Schneider, E., Riehl J., & Noyce, D. (2021).
Intelligent Road Side Unit (RSU) Network for Automated Driving
US Patent Application 2022343755 A1Ran, B., Cheng, Y., Chen, T., Li, S., Shi, K., Yao, Y., Wu, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., Li, X. [Link]
Autonomous Vehicle and Cloud Control System
US Patent Application 2022375335 A1Ran, B., Cheng, Y., Chen, T., Yao, Y., Wu, K., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., Li, X. [Link]
Intelligent Information Conversion for Automatic Driving
US Patent Application 2022219731 A1Ran, B., Wu, R., Li, H., Cheng, Y., Zhou, K., Tuo, X., Zhang, W., Xu, C., Li, X., Wu, K. [Link]
Function Allocation for Automated Driving Systems
US Patent Application 2021394797 A1Ran, B., Chen, T., Dong, S., Cheng, Y., Zhang, M., Li, X., Li, S., Shi, K., Shi, H., Yao, Y., Mo, Y., Liu, H., Wu, K., Yi, R. [Link]
Systematic Intelligent System
US Patent Application 2022171400 A1Chen, T., Ran, B., Dong, S., Wu, K., Cheng, Y., Li, L., Li, S., Li, X., Mo, Y., Yao, Y., Shi, K., Shi, H., Li, H. [Link]
Intelligent Roadside Toolbox
US Patent Application 2021311491 A1Li, S., Ran, B., Cheng, Y., Chen, T., Li, X., Dong, S., Shi, K., Shi, H., Yao, Y., Yi, R., Wu, K., Zhou, Y. [Link]
Collaborative Automated Driving System
US Patent Application 2022270476 A1Ran, B., Chen, T., Li, X., Cheng, Y., Li, S., Dong, S., Yao, Y., Shi, K., Shi, H., Wu, K., Fu, S. [Link]
Function Allocation for Automated Driving Systems
US Patent Application 2022111858 A1Ran, B., Mao, P., Lu, W., Yi, Z., Li, L., Cheng, Y., Xu, L., Zheng, Y., Chen, T., Shi, H., Wu, K. [Link]
Device Allocation System
US Patent Application 2021314752 A1Ran, B., Dong, S., Cheng, Y., Chen, T., Li, S., Li, X., Shi, K., Shi, H., Wu, K., Yao, Y., Yi, R. [Link]
Mobile Intelligent Road Infrastructure System
US Patent Application 2022281484 A1Ran, B., Lu, W., Chen, T., Cheng, Y., Li, L., Liang, B., Yao, Y., Shi, K., Wu, K. [Link]
Connected Reference Marker System
WIPO Patent Application WO 2022265899 A2Ran, B., Shi, K., Lu, W., Cheng, Y., Zhang, H., Shi, H., Chen, T., Liang, B., Yao, Y., Wu, K., Fu, S. [Link]
Autonomous vehicle cloud system
US Patent Application 20240005779 A1Ran, B., Zheng, Y., Wang, C., Cheng, Y., Yao, Y., Wu, K., Chen, T., Shi, H., Li, S., Shi, K., Zhang, Z., Ding, F., Tan, H., Wu, Y., Dong, S., Ye, L., Li, X. [Link]