|M.Sc Student||Tuchner Alon|
|Subject||Vehicle Platoon Formation using Interpolating Control|
|Department||Department of Autonomous Systems and Robotics||Supervisor||ASSOCIATE PROF. Jack Haddad|
The platooning concept can be defined as a collection of vehicles that travel close together, actively coordinated in formation. Some expected advantages of platooning include increased fuel and traffic efficiency, and improved safety and driver comfort. In recent years, cooperative strategies such as Cooperative Adaptive Cruise Control (CACC) demonstrated promising results by forming string stable platoons with small inter-vehicular spacings.
Automatic platooning of vehicles consists of three main phases, a formation phase, a maintenance phase in which the platoon has to maintain string stability while subject to disturbances, and a splitting phase. This work addresses the formation phase of automatic platooning. The objective is to optimally control the throttle of vehicles, with a given arbitrary initial condition, such that desired ground speed and inter-vehicular spacings are reached. The steering of the vehicles is also controlled, because the vehicles should track a desired path while forming the platoon. In order to address the platoon formation problem, a cooperative strategy is formed by constructing a discrete state space model which represents the dynamics of a set of n vehicles. Once this model is set, a control method known as Interpolating Control, which aims at regulating to the origin an uncertain and/or time-varying linear discrete-time system with state and control constraints, is utilized. The performance of this control method is evaluated and compared with other approaches such as Model Predictive Control.
Simulations are conducted which suggest that the Interpolating Control approach can be seen as an alternative to optimization-based control schemes such as Model Predictive Control, especially for problems requiring complex calculations to find the optimal solution, where the Interpolating Control approach can provide a straightforward sub-optimal solution.
In the experimental part of this work, the control algorithms for the platoon formation and path tracking problems are combined, and tested in a laboratory environment, using three mobile robots equipped with wireless routers. Validation of the proposed models and control algorithms is achieved by successful experiments.