Reference:
Y. Wang,
S. Zhu,
S. Li,
L. Yang, and
B. De Schutter,
"Hierarchical model predictive control for on-line high-speed railway
delay management and train control in a dynamic operations
environment," IEEE Transactions on Control Systems
Technology, vol. 30, no. 6, pp. 2344-2359, Nov. 2022.
Abstract:
Currently, with the development of driving technologies, driverless
vehicles gradually are becoming more and more available. Therefore,
there would be a long period of time during which self-driving
vehicles and human-driven vehicles coexist. However, for a mixed
platoon, it is hard to control the formation due to the existence of
the manual vehicles resulting in weak robustness and slow consensus
rate on this system of platoons because of uncertainties caused by
human factors for manual vehicles. In order to solve this problem, we
establish models of mixed platoons with mixed types of connected and
automated vehicles (CAVs), human-driven vehicles (HDVs) and HDVs
without the vehicle awareness device (HDVWs). We subsequently design
H_∞ controllers for the mixed platoons to realize the
formation consensus. In addition, we use the H_∞ norm
of mixed platoons as the control objective investigating the
robustness of the control algorithms in alleviating the platoon
uncertainties. Furthermore, conditions are proved to maintain the
stability of the mixed platoons, and the stability is analyzed based
on the variation of the penetration rate of the manual vehicles.
Finally, we formulate conditions for parameters according to the
definition of string stability to avoid the collisions of vehicles.
The results in this study are tested with simulations and suggest that
the presented controllers can ensure the consensus of mixed platoons
under uncertainties.