Zhe Fu
Zhe Fu
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Zitiert von
Zitiert von
Evaluating smart charging strategies using real-world data from optimized plugin electric vehicles
SI Spencer, Z Fu, E Apostolaki-Iosifidou, TE Lipman
Transportation Research Part D: Transport and Environment 100, 103023, 2021
Cooperative driving for speed harmonization in mixed-traffic environments
Z Fu, AR Kreidieh, H Wang, JW Lee, ML Delle Monache, AM Bayen
2023 IEEE Intelligent Vehicles Symposium (IV), 1-8, 2023
Traffic control via connected and automated vehicles: An open-road field experiment with 100 cavs
JW Lee, H Wang, K Jang, A Hayat, M Bunting, A Alanqary, W Barbour, ...
arXiv preprint arXiv:2402.17043, 2024
Traffic smoothing via connected & automated vehicles: A modular, hierarchical control design deployed in a 100-cav flow smoothing experiment
JW Lee, H Wang, K Jang, A Hayat, M Bunting, A Alanqary, W Barbour, ...
IEEE Control Systems Magazine, 2024
Economic and environmental benefits for electricity grids from spatiotemporal optimization of electric vehicle charging
S Woo, Z Fu, E Apostolaki-Iosifidou, TE Lipman
Energies 14 (24), 8204, 2021
Learning energy-efficient driving behaviors by imitating experts
AR Kreidieh, Z Fu, AM Bayen
2022 IEEE 25th International Conference on Intelligent Transportation …, 2022
Hierarchical speed planner for automated vehicles: A framework for lagrangian variable speed limit in mixed autonomy traffic
H Wang, Z Fu, J Lee, HNZ Matin, A Alanqary, D Urieli, S Hornstein, ...
arXiv preprint arXiv:2402.16993, 2024
Towards Understanding Worldwide Cross-cultural Differences in Implicit Driving Cues: Review, Comparative Analysis, and Research Roadmap
Y Dong, C Liu, Y Wang, Z Fu
arXiv preprint arXiv:2405.01119, 2024
Massive CAV Experiment in Nashville Pits Machine Learning against Traffic Jams
Z Fu, K Manke, A Bayen, 2023
UC Berkeley Develops New User-Friendly Tool to Expedite the Evaluation of Connected Automated Vehicle Technologies
Z Fu, H Liu, XY Lu
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