Control Architecture for Cooperative Autonomous Vehicles Driving in Platoons at Highway Speeds

The situation in which a vehicle has to avoid a collision with an obstacle can be difficult to realise in optimum conditions when the roads are crowded. This paper uses the advantages of vehicle grouping and vehicle-to-vehicle (V2V) communication, and proposes a control architecture, which ensures a safe merging between the vehicles from two platoons. The architecture is formed by three layers, with the following tasks:
i)
to analyse the environment and to decide the best action for a certain vehicle,
ii)
to plan the new trajectory, and
iii)
to follow it at an imposed velocity or distance to the vehicle in front. The vehicles are equipped with a trajectory planner designed using two methods: the first one is based on a polynomial equation, and the second one is based on the model predictive control (MPC) algorithm. Each vehicle is also equipped with a trajectory follower, which has a cooperative adaptive cruise control (CACC) functionality based on a distributed model predictive control (DMPC) formulation. Also, the paper proposes a solution to compensate the data-packet-dropouts that are induced by the wireless communication network used to exchange information between vehicles. Moreover, to accommodate various realistic scenarios in the same control framework, the cost function for the DMPC algorithm was designed to take into account different communication topologies. The proposed architecture was tested in a simulation scenario, in which two platoons have to merge in order to avoid a fixed obstacle and the results show its efficiency.