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Zhe Fu
Zhe Fu
Verified email at berkeley.edu
Title
Cited by
Cited by
Year
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
452021
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
62023
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
52021
Learning energy-efficient driving behaviors by imitating experts
AR Kreidieh, Z Fu, AM Bayen
2022 IEEE 25th International Conference on Intelligent Transportation …, 2022
32022
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
12024
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
2024
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
2024
Massive CAV Experiment in Nashville Pits Machine Learning against Traffic Jams
Z Fu, K Manke, A Bayen
https://doi.org/10.1287/orms.2023.02.05, 2023
2023
UC Berkeley Develops New User-Friendly Tool to Expedite the Evaluation of Connected Automated Vehicle Technologies
Z Fu, H Liu, XY Lu
2020
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