ARCHIVES

1. Ahmed Fahmin, Muhammad Aamir Cheema, Mohammed Eunus Ali, Adel Nadjaran Toosi, Hua Lu, Huan Li, David Taniar, Hesham A.
Rakha, and Bojie Shen. 2024. Eco-Friendly Route Planning Algorithms: Taxonomies, Literature Review and Future Directions. ACM
Comput. Surv. 57, 1, Article 21 (January 2025), 42 pages. https://doi.org/10.1145/3691624
2. H. Li, A. Ravey, A. N'Diaye and A. Djerdir, "A Review of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicle," 2017
IEEE Vehicle Power and Propulsion Conference (VPPC), Belfort, France, 2017, pp. 1-6, doi: 10.1109/VPPC.2017.8330970.
3. Ahn, Kyoungho, and Hesham A. Rakha. 2022. "Developing a Hydrogen Fuel Cell Vehicle (HFCV) Energy Consumption Model for
Transportation Applications" Energies 15, no. 2: 529. https://doi.org/10.3390/en15020529
4. Ahn, Kyoungho, and Hesham A. Rakha. 2024. "Simple Energy Model for Hydrogen Fuel Cell Vehicles: Model Development and
Testing" Energies 17, no. 24: 6360. https://doi.org/10.3390/en17246360
5. C. Sun, X. Shen and S. Moura, "Robust Optimal ECO-driving Control with Uncertain Traffic Signal Timing," 2018 Annual AmericanControl Conference (ACC), Milwaukee, WI, USA, 2018, pp. 5548-5553, doi: 10.23919/ACC.2018.8430781.
6. Shuaidong Zhao, Kuilin Zhang, “Online predictive connected and automated eco-driving on signalized arterials considering traffic control
devices and road geometry constraints under uncertain traffic conditions,” Transportation Research Part B: Methodological, Volume
145,2021, Pages 80-117, ISSN 0191-2615, https://doi.org/10.1016/j.trb.2020.12.009.
7. Qi, Pengyang, Chaofeng Pan, Xing Xu, Jian Wang, Jun Liang, and Weiqi Zhou. 2025. "A Review of Dynamic Traffic Flow Prediction
Methods for Global Energy-Efficient Route Planning" Sensors 25, no. 17: 5560. https://doi.org/10.3390/s25175560
8. Jie Li, Abbas Fotouhi, Yonggang Liu, Yuanjian Zhang, Zheng Chen, “Review on eco-driving control for connected and automated
vehicles,” Renewable and Sustainable Energy Reviews, Volume 189, Part B, 2024, 114025, ISSN 1364-0321,
https://doi.org/10.1016/j.rser.2023.114025.
9. Bo Liu, Chao Sun, Bo Wang, Weiqiang Liang, Qiang Ren, Junqiu Li, Fengchun Sun, “Bi-level convex optimization of eco-driving for
connected Fuel Cell Hybrid Electric Vehicles through signalized intersections,” Energy, Volume 252, 2022, 123956, ISSN 0360-5442,
https://doi.org/10.1016/j.energy.2022.123956.
10. Wenjie Li, Lixing Yang, Li Wang, Xuesong Zhou, Ronghui Liu, Ziyou Gao, “Eco-reliable path finding in time-variant and stochastic
networks,” Energy, Volume 121, 2017,Pages 372-387, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2017.01.008.
11. Z. Yi and P. H. Bauer, "Optimal Stochastic Eco-Routing Solutions for Electric Vehicles," in IEEE Transactions on Intelligent
Transportation Systems, vol. 19, no. 12, pp. 3807-3817, Dec. 2018, doi: 10.1109/TITS.2017.2781260.
12. M. Salazar, A. Houshmand, C. G. Cassandras and M. Pavone, "Optimal Routing and Energy Management Strategies for Plug-in Hybrid
Electric Vehicles," 2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 2019, pp. 733-739, doi:
10.1109/ITSC.2019.8917131.
13. Weiliang Zeng, Tomio Miwa, Takayuki Morikawa, “Eco-routing problem considering fuel consumption and probabilistic travel time
budget,” Transportation Research Part D: Transport and Environment, Volume 78, 2020, 102219, ISSN 1361-9209,
https://doi.org/10.1016/j.trd.2019.102219.
14. Menglin Li, Long Yin, Mei Yan, Jingda Wu, Hongwe He, Chunchun Jia, “Hierarchical intelligent energy-saving control strategy for fuel
cell hybrid electric buses based on traffic flow predictions,” Energy, Volume 304, 2024, 132144, ISSN 0360-5442,
https://doi.org/10.1016/j.energy.2024.132144.
15. Leech, David R., and Hwan-Sik Yoon. 2025. "Model-Based Deep Reinforcement Learning for Energy Efficient Routing of a Connected
and Automated Vehicle" Sustainability 17, no. 13: 5727. https://doi.org/10.3390/su17135727
16. Soomin Woo, Eric Yongkeun Choi, Scott J. Moura, Francesco Borrelli, “Saving energy with eco-friendly routing of an electric vehicle
fleet,” Transportation Research Part E: Logistics and Transportation Review, Volume 189, 2024, 103644, ISSN 1366-5545,
https://doi.org/10.1016/j.tre.2024.103644.
17. M. A. S. Kamal, M. Mukai, J. Murata and T. Kawabe, "Model Predictive Control of Vehicles on Urban Roads for Improved Fuel
Economy," in IEEE Transactions on Control Systems Technology, vol. 21, no. 3, pp. 831-841, May 2013, doi:
10.1109/TCST.2012.2198478.
18. N. Sulaiman, M.A. Hannan, A. Mohamed, E.H. Majlan, W.R. Wan Daud, “A review on energy management system for fuel cell hybrid
electric vehicle: Issues and challenges,” Renewable and Sustainable Energy Reviews, Volume 52, 2015, Pages 802-814, ISSN 1364-0321,
https://doi.org/10.1016/j.rser.2015.07.132.
19. Xiaohua Wu, Pengfei Ma, Lingxue Zhou, Zhanfeng Fan, Qingbo Zhu, Xiaofeng Yin, Quan Ouyang, “Collaborative optimization of
velocity planning and energy management for fuel cell hybrid buses at multiple intersections and bus stations,” Energy, Volume 326,
2025,135912, ISSN 0360-5442, https://doi.org/10.1016/j.energy.2025.135912.
20. Xiaowei Chen, Jiawei Xue, Zengxiang Lei, Xinwu Qian, Satish V. Ukkusuri, “Online eco-routing for electric vehicles using combinatorial
multi-armed bandit with estimated covariance,” Transportation Research Part D: Transport and Environment, Volume 111, 2022, 103447,
ISSN 1361-9209, https://doi.org/10.1016/j.trd.2022.103447.
21. Jovanovic, Aleksandar, Slavica Gavric, and Aleksandar Stevanovic. 2024. "Evaluating Google Maps’ Eco-Routes: A Metaheuristic-
Driven Microsimulation Approach" Geographies 4, no. 4: 732-752. https://doi.org/10.3390/geographies4040040
22. Wang, Wei, Zhuo Hao, Fufan Qu, Wenbo Li, Liguang Wu, Xin Li, Pengyu Wang, and Yangyang Ma. 2023. "Review of Energy
Management Methods for Fuel Cell Vehicles: From the Perspective of Driving Cycle Information" Sensors 23, no. 20: 8571.
https://doi.org/10.3390/s23208571
23. Sun, Y., Xia, C., Yin, B. et al. Adaptive Energy Management Strategy of Fuel Cell Electric Vehicle. Int.J Automot. Technol. 23, 1393–
1403 (2022). https://doi.org/10.1007/s12239-022-0122-y
24. Wang, Y., Wu, J., He, H. et al. Data-driven energy management for electric vehicles using offline reinforcement learning. Nat Commun 16,
2835 (2025). https://doi.org/10.1038/s41467-025-58192-9
25. Liu, H. Sustainable road network design considering hydrogen fuel cell vehicles. Sci Rep 13, 21947 (2023).
https://doi.org/10.1038/s41598-023-49264-1
26. Warsini Handayani, Xuan Zhu, Fang Lee Cooke, “Hydrogen demand estimation for sustainable transport: A comprehensive review,”
Renewable and Sustainable Energy Reviews, Volume 225, 2026, 116172, ISSN 1364-0321, https://doi.org/10.1016/j.rser.2025.116172.
27. Ömer Faruk Günaydın, Salih Topçu, Aslı Aksoy, “ Hydrogen fuel cell vehicles: Overview and current status of hydrogen mobility,”
International Journal of Hydrogen Energy, Volume 142, 2025, Pages 918-936, ISSN 0360-3199,
https://doi.org/10.1016/j.ijhydene.2025.01.412.
28. Faghihian, Hamed, and Arman Sargolzaei. 2023. "Energy Efficiency of Connected Autonomous Vehicles: A Review" Electronics 12, no.
19: 4086. https://doi.org/10.3390/electronics12194086
29. Dong, Hongquan, Lingying Zhao, Hao Zhou, and Haolin Li. 2023. "Hierarchical Optimization Based on Deep Reinforcement Learning
for Connected Fuel Cell Hybrid Vehicles through Signalized Intersections" Processes 11, no. 9: 2689. https://doi.org/10.3390/pr11092689
30. Yi, Fengyan, Wei Guo, Hongtao Gong, Yang Shen, Jiaming Zhou, Wenhao Yu, Dagang Lu, Chunchun Jia, Caizhi Zhang, and Farui Gong.
2024. "Research on Speed Planning and Energy Management Strategy for Fuel Cell Hybrid Bus in Green Wave Scenarios at Traffic Light
Intersections Based on Deep Reinforcement Learning" Sustainability 16, no. 24: 11156. https://doi.org/10.3390/su162411156.