Bio
Dr. Guanhao Xu is currently an Advanced Mobility R&D Staff in the Applied Research for Mobility Systems group. His research mainly focuses on urban mobility, traffic operations, network simulation, and traffic signal design. He is currently working on 4 projects:
EEMS114 Real-Twin: a project sponsored by the DOE VTO EEMS program that aims to automatically generate relevant scenarios based on user-specified technology and available real-world data and implement these scenarios into different traffic and vehicle simulation tools and/or XIL to assess the performance and impact of the technologies. In this project, he leads the development of tools that automate the generation and calibration of scenarios for microscopic traffic simulation.
EEMS124 Real-Twin/Real-Sim deployment: a project sponsored by the DOE VTO EEMS program that aims to develop a library of digital twin scenarios for energy-focused connected and automated vehicles (CAV) simulation and evaluation, utilizing cross-lab, EEMS developed capabilities including ORNL’s Real-Sim/ Real-Twin and ANL’s APaCK-V, and through anything-in-the-loop (XIL) evaluation to broadly understand the energy and mobility impacts of various CAV and traffic control strategies. In this project, he leads the development of elevation import tool for digital twin and works on the construction of 3D digital twin based on real world data.
ELT286 Volvo SuperTruck 3: a project sponsored by the DOE VTO EERE program that aims to develop a virtual simulation of the actual vehicle demonstration of Volvo’s electrified medium-duty (MD) and heavy-duty (HD) vehicle technologies into diverse geographies and climates to assess the overall impacts of Volvo’s commercial vehicle electrification approach to freight system efficiency. In this project, he takes the lead on constructing traffic simulation for a 400-mile highway corridor (I-81).
EEMS107 UA FOA: a project sponsored by the DOE VTO EEMS program that aims to improve network-wide fuel economy and enable traffic signal optimization using infrastructure and vehicle-based sensing and connectivity. In this project, he works on design, construct, and perform vehicle-in-the-loop simulation tests for signal optimization of a real-world corridor.
Before coming to ORNL, he worked on the project Microsimulation of the Emergency Evacuation of Rocky Mountain National Park sponsored by the U.S. Department of the Interior. In this project, he utilized agent-based microsimulation in AIMSUN to analyze the impact of different evacuation strategies and real-world conditions on evacuation speed when an emergency occurs at Rocky Mountain National Park.
Awards
The 27th 91°µÍø International Conference on Intelligent Transportation Systems (91°µÍø ITSC 2024) Best Application Paper Award
Education
The Pennsylvania State University Civil Engineering Ph.D. 2022
University of Illinois at Urbana-Champaign Civil Engineering M.S. 2018
Southeast University, China Transportation Engineering B.E. 2016
Publications
Online energy consumption forecast for battery electric buses using a learning-free algebraic method
Other Publications
- Xu, G., Wang, X., Yao, R., Liao, Y., Sun, J., Cheng, X., Fan, H., Wang, Z., Ozpineci, B., Sprinkle, J., Hao, P., & Barth, M. (2024, September). Improving dynamic wireless charging system performance for electric vehicles through variable speed limit control integration. In The 27th 91°µÍø International Conference on Intelligent Transportation Systems (ITSC).
- Xu, G., & Gayah, V. V. (2024). On the Impact of Bus Dwelling on Macroscopic Fundamental Diagrams. In International Conference on Transportation and Development 2024 (pp. 599-612).
- Xu, H., Yuan, J., Zhou, A., Xu, G., Li, W., & Ye, X. (2024). GenAI-powered Multi-Agent Paradigm for Smart Urban Mobility: Opportunities and Challenges for Integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with Intelligent Transportation Systems. arXiv preprint .
- Xu, G., & Gayah, V. V. (2023). Non-unimodal and non-concave relationships in the network Macroscopic Fundamental Diagram caused by hierarchical streets. Transportation Research Part B: Methodological, 173, 203-227.
- Wang, Z., Zhou, A., Cook, A., Shao, Y., Xu, G., & Chen, M. (2023, October). Energy-Centric Cooperative Onramp Merging Strategy: An Analytical Solution. In 2023 91°µÍø International Automated Vehicle Validation Conference (IAVVC) (pp. 1-7). 91°µÍø.
- Xu, G., Zhang, P., Gayah, V. V., & Hu, X. (2023). Opposing hysteresis patterns in flow and outflow macroscopic fundamental diagrams and their implications. Transportation Research Record, 03611981231155421.
- Wang, Z., Cook, A., Shao, Y., Xu, G., & Chen, J. M. (2023, June). Cooperative Merging Speed Planning: A Vehicle-Dynamics-Free Method. In 2023 91°µÍø Intelligent Vehicles Symposium (IV) (pp. 1-8). 91°µÍø.
- Yu, Z., Xu, G., Gayah, V. V., & Christofa, E. (2020). Incorporating phase rotation into a person-based signal timing optimization algorithm. 91°µÍø Transactions on Intelligent Transportation Systems, 23(1), 513-521.
- Xu, G., Yu, Z., & Gayah, V. V. (2020). Analytical method to approximate the impact of turning on the macroscopic fundamental diagram. Transportation research record, 2674(9), 933-947.