[1] X. Li, W. Lin, Y. Jin, D. Chen, T. chen, Dynamic Energy Management Strategy of Hybrid Electric Vehicles based on Velocity Prediction, IFAC-PapersOnLine, 54(10) (2021) 363–369.
[2] C. Sun, X. Hu, S.J. Moura, F. Sun, Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles, IEEE Transactions on Control Systems Technology, 23(3) (2015) 1197–1204.
[3] Y. Jia, C. Cai, D. Görges, An LSTM-Based Speed Predictor Based on Traffic Simulation Data for Improving the Performance of Energy-Optimal Adaptive Cruise Control, in: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020, pp. 1–7.
[4] B. Li, W. Zhuang, B. Chen, H. Zhang, S. Yu, J. Zhang, G. Yin, Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads, Chin. J. Mech. Eng., 38(1) (2025) 37.
[5] T. Ersal, I. Kolmanovsky, N. Masoud, N. Ozay, J. Scruggs, R. Vasudevan, G. Orosz, Connected and automated road vehicles: state of the art and future challenges, Vehicle System Dynamics, 58(5) (2020) 672–704.
[6] E. Hyeon, Y. Kim, N. Prakash, A.G. Stefanopoulou, Influence of Speed Forecasting on the Performance of Ecological Adaptive Cruise Control, in: ASME 2019 Dynamic Systems and Control Conference, American Society of Mechanical Engineers Digital Collection, 2019.
[7] J.J.Q. Yu, Online Traffic Speed Estimation for Urban Road Networks with Few Data: A Transfer Learning Approach, 2019 IEEE Intelligent Transportation Systems Conference (ITSC), (2019).
[8] J.B. Kenney, Dedicated Short-Range Communications (DSRC) Standards in the United States, Proceedings of the IEEE, 99(7) (2011) 1162–1182.
[9] S. Lefèvre, C. Sun, R. Bajcsy, C. Laugier, Comparison of parametric and non-parametric approaches for vehicle speed prediction, in: 2014 American Control Conference, 2014, pp. 3494–3499.
[10] Z. Zhou, Z. Yang, Y. Zhang, Y. Huang, H. Chen, Z. Yu, A comprehensive study of speed prediction in transportation system: From vehicle to traffic, iScience, 25(3) (2022) 103909.
[11] K. Liu, Z. Asher, X. Gong, M. Huang, I. Kolmanovsky, Vehicle velocity prediction and energy management strategy part 1: Deterministic and stochastic vehicle velocity prediction using machine learning, SAE Technical Paper, 2019.
[12] S.D. Cairano, D. Bernardini, A. Bemporad, I.V. Kolmanovsky, Stochastic MPC With Learning for Driver-Predictive Vehicle Control and its Application to HEV Energy Management, IEEE Transactions on Control Systems Technology, 22(3) (2014) 1018–1031.
[13] M. Wegener, F. Herrmann, L. Koch, R. Savelsberg, J. Andert, Longitudinal Vehicle Motion Prediction in Urban Settings With Traffic Light Interaction, IEEE Transactions on Intelligent Vehicles, 8(1) (2023) 204–215.
[14] E. Hyeon, D. Shen, D. Karbowski, A. Rousseau, Forecasting Short to Mid-Length Speed Trajectories of Preceding Vehicle Using V2X Connectivity for Eco-Driving of Electric Vehicles, SAE Int. J. Adv. & Curr. Prac. in Mobility, 3(4) (2021) 1801–1809.
[15] E. Hyeon, Y. Kim, T. Ersal, A. Stefanopoulou, Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control, J. Dyn. Sys., Meas., Control, 144(1) (2022).
[16] E. Hyeon, D. Karbowski, A. Rousseau, Potential Energy Saving by Different Cooperative Driving Automation Classes in Car-Following Scenarios *, in: 2023 American Control Conference (ACC), 2023, pp. 1313–1318.
[17] J. Guo, H. He, C. Sun, ARIMA-Based Road Gradient and Vehicle Velocity Prediction for Hybrid Electric Vehicle Energy Management, IEEE Transactions on Vehicular Technology, 68(6) (2019) 5309–5320.
[18] C. Pan, A. Huang, J. Wang, L. Chen, J. Liang, W. Zhou, L. Wang, J. Yang, Energy-optimal adaptive cruise control strategy for electric vehicles based on model predictive control, Energy, 241 (2022) 122793.
[19] C. Pan, Y. Li, J. Wang, J. Liang, H. Jinyama, Research on multi-lane energy-saving driving strategy of connected electric vehicle based on vehicle speed prediction, Green Energy and Intelligent Transportation, 2(6) (2023) 100127.
[20] J. Wang, Z. Li, C. Pan, Energy-efficient trajectory planning with curve splicing based on PSO-LSTM prediction, Control Engineering Practice, 150 (2024) 106009.
[21] S.K. Chada, D. Görges, A. Ebert, R. Teutsch, Deep Learning-Based Vehicle Speed Prediction for Ecological Adaptive Cruise Control in Urban and Highway Scenarios, IFAC-PapersOnLine, 56(2) (2023) 1107–1114.
[22] M.F. Ozkan, Y. Ma, Eco-Driving of Connected and Automated Vehicle With Preceding Driver Behavior Prediction, J. Dyn. Sys., Meas., Control, 143(1) (2021) 011002.
[23] F. Zhang, J. Xi, R. Langari, Real-Time Energy Management Strategy Based on Velocity Forecasts Using V2V and V2I Communications, IEEE Transactions on Intelligent Transportation Systems, 18(2) (2017) 416–430.
[24] E. Hyeon, Speed Forecasting Strategies for the Energy-Optimal Car-Following of Connected and Automated Vehicles, Thesis, 2022.
[25] R. Krajewski, J. Bock, L. Kloeker, L. Eckstein, The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems, in: 2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018, pp. 2118–2125.
[26] A. Zhang, Z.C. Lipton, M. Li, A.J. Smola, Dive into deep learning, Cambridge University Press, 2023.
[27] M. Vajedi, N.L. Azad, Ecological Adaptive Cruise Controller for Plug-In Hybrid Electric Vehicles Using Nonlinear Model Predictive Control, IEEE Transactions on Intelligent Transportation Systems, (2016).
