Ph. D. Project
Robustness of specific switching control laws for platooning
2023/10/01 - 2026/09/30
Vehicular platoon control can effectively achieve group consensus, reduced fuel consumption, improve vehicular running safety and increase road capacity. However, this emerging technology faces several challenges like unreliable vehicle-to-vehicle communications, sensitivity to road traffic and to additions/reductions in platoon size. A small gap results in a short inter-vehicular distance, which is fuel efficient when the vehicles are moving at constant speeds due to air drag reductions, but when the vehicles accelerate and brake a lot, a bigger time gap is more fuel efficient. Similarly, a poor communication network motivates a higher inter-vehicular gap for safety while a smaller gap can be maintained with reliable communications. All these issues motivate platoons that switch the control strategy according to the scenario [1,2]. However, while the string stability of a given control scheme is well studied [3], guarantees on a switching control are rarely examined. Our objective in this Ph.D. is to theoretically analyze the performances of such switching control laws.

[1] T. R. Gonçalves, R.F. Cunha, V. S. Varma, S. E. Elayoubi and M. Cao, Reducing fuel consumption in platooning systems through reinforcement learning, IFAC ICONS 2022.
[2] Li, Y., Tang, C., Li, K., Peeta, S., He, X., and Wang, Y. (2018). Nonlinear finite-time consensus-based connected vehicle platoon control under fixed and switching communication topologies. Transportation Research Part C: Emerging Technologies, 93, 525-543.
[3] Ploeg, J., Shukla, D. P., Van De Wouw, N., and Nijmeijer, H. (2013). Controller synthesis for string stability of vehicle platoons. IEEE Transactions on Intelligent Transportation Systems, 15(2), 854-865.
Autonomous vehicle, decentralized control, platooning
Duration : 36 months.
Employer : Université de Lorraine
Place : CRAN, site ENSEM, Nancy.
Salary : Ph.D contract
Profil : Good background mathematical tools, optimization and optimal control. Knowledge of graph theory and decentralized control will be appreciated
Control Identification Diagnosis
Ph.D contract by University of Lorraine